research article examples for students

How To Write A Research Paper

Research Paper Example

Research Paper Example - Examples for Different Formats

Published on: Jun 12, 2021

Last updated on: Feb 6, 2024

Research Paper Example for Different Formats

A research paper typically consists of several key parts, including an introduction, literature review, methodology, results, and annotated bibliography .

When writing a research paper (whether quantitative research or qualitative research ), it is essential to know which format to use to structure your content. Depending on the requirements of the institution, there are mainly four format styles in which a writer drafts a research paper:

Letâs look into each format in detail to understand the fundamental differences and similarities.

Research Paper Example APA

If your instructor asks you to provide a research paper in an APA format, go through the example given below and understand the basic structure. Make sure to follow the format throughout the paper.

APA Research Paper Sample (PDF)

Research Paper Example MLA

Another widespread research paper format is MLA. A few institutes require this format style as well for your research paper. Look at the example provided of this format style to learn the basics.

MLA Research Paper Sample (PDF)

Research Paper Example Chicago

Unlike MLA and APA styles, Chicago is not very common. Very few institutions require this formatting style research paper, but it is essential to learn it. Look at the example given below to understand the formatting of the content and citations in the research paper.

Chicago Research Paper Sample (PDF)

Research Paper Example Harvard

Learn how a research paper through Harvard formatting style is written through this example. Carefully examine how the cover page and other pages are structured.

Harvard Research Paper Sample (PDF)

Examples for Different Research Paper Parts

A research paper is based on different parts. Each part plays a significant role in the overall success of the paper. So each chapter of the paper must be drafted correctly according to a format and structure.

Below are examples of how different sections of the research paper are drafted.

Research Proposal Example

A research proposal is a plan that describes what you will investigate, its significance, and how you will conduct the study.

Research Proposal Sample (PDF)

Abstract Research Paper Example

An abstract is an executive summary of the research paper that includes the purpose of the research, the design of the study, and significant research findings.

It is a small section that is based on a few paragraphs. Following is an example of the abstract to help you draft yours professionally.

Abstract Research Paper Sample (PDF)

Literature Review Research Paper Example

A literature review in a research paper is a comprehensive summary of the previous research on your topic. It studies sources like books, articles, journals, and papers on the relevant research problem to form the basis of the new research.

Writing this section of the research paper perfectly is as important as any part of it.

Literature Review in Research Sample (PDF)

Methods Section of Research Paper Example

The method section comes after the introduction of the research paper that presents the process of collecting data. Basically, in this section, a researcher presents the details of how your research was conducted.

Methods Section in Research Sample (PDF)

Research Paper Conclusion Example

The conclusion is the last part of your research paper that sums up the writerâs discussion for the audience and leaves an impression. This is how it should be drafted:

Research Paper Conclusion Sample (PDF)

Research Paper Examples for Different Fields

The research papers are not limited to a particular field. They can be written for any discipline or subject that needs a detailed study.

In the following section, various research paper examples are given to show how they are drafted for different subjects.

Science Research Paper Example

Are you a science student that has to conduct research? Here is an example for you to draft a compelling research paper for the field of science.

Science Research Paper Sample (PDF)

History Research Paper Example

Conducting research and drafting a paper is not only bound to science subjects. Other subjects like history and arts require a research paper to be written as well. Observe how research papers related to history are drafted.

History Research Paper Sample (PDF)

Psychology Research Paper Example

If you are a psychology student, look into the example provided in the research paper to help you draft yours professionally.

Psychology Research Paper Sample (PDF)

Research Paper Example for Different Levels

Writing a research paper is based on a list of elements. If the writer is not aware of the basic elements, the process of writing the paper will become daunting. Start writing your research paper taking the following steps:

Choose a topic
Form a strong thesis statement
Conduct research
Develop a research paper outline

Once you have a plan in your hand, the actual writing procedure will become a piece of cake for you.

No matter which level you are writing a research paper for, it has to be well structured and written to guarantee you better grades.

If you are a college or a high school student, the examples in the following section will be of great help.

Research Paper Outline (PDF)

Research Paper Example for College

Pay attention to the research paper example provided below. If you are a college student, this sample will help you understand how a winning paper is written.

College Research Paper Sample (PDF)

Research Paper Example for High School

Expert writers of CollegeEssay.org have provided an excellent example of a research paper for high school students. If you are struggling to draft an exceptional paper, go through the example provided.

High School Research Paper Sample (PDF)

Examples are essential when it comes to academic assignments. If you are a student and aim to achieve good grades in your assignments, it is suggested to get help from CollegeEssay.org .

We are the best writing company that delivers essay help for students by providing free samples and writing assistance.

Professional writers have your back, whether you are looking for guidance in writing a lab report, college essay, or research paper.

Simply hire a writer by placing your order at the most reasonable price. You can also take advantage of our essay writer to enhance your writing skills.

Nova A. (Literature, Marketing)

As a Digital Content Strategist, Nova Allison has eight years of experience in writing both technical and scientific content. With a focus on developing online content plans that engage audiences, Nova strives to write pieces that are not only informative but captivating as well.

Paper Due? Why Suffer? That’s our Job!

Keep reading

Privacy Policy
Cookies Policy
Terms of Use
Refunds & Cancellations
Our Writers
Success Stories
Our Guarantees
Affiliate Program
Referral Program
AI Essay Writer

Disclaimer: All client orders are completed by our team of highly qualified human writers. The essays and papers provided by us are not to be used for submission but rather as learning models only.

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Publications
Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

Advanced Search
Journal List
J Korean Med Sci
v.37(16); 2022 Apr 25

A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g001.jpg

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

An external file that holds a picture, illustration, etc.
Object name is jkms-37-e121-g002.jpg

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

EXAMPLE 1. Descriptive research question (quantitative research)
- Presents research variables to be assessed (distinct phenotypes and subphenotypes)
“BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
EXAMPLE 2. Relationship research question (quantitative research)
- Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
“Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
EXAMPLE 3. Comparative research question (quantitative research)
- Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
“BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
EXAMPLE 4. Exploratory research question (qualitative research)
- Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
“Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
EXAMPLE 5. Relationship research question (quantitative research)
- Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
“Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

EXAMPLE 1. Working hypothesis (quantitative research)
- A hypothesis that is initially accepted for further research to produce a feasible theory
“As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
“In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
EXAMPLE 2. Exploratory hypothesis (qualitative research)
- Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
“We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
“Conclusion
Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
“We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
EXAMPLE 4. Statistical hypothesis (quantitative research)
- An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
“Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
“Statistical Analysis
( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

EXAMPLE 1. Background, hypotheses, and aims are provided
“Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
“ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
“This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
EXAMPLE 2. Background, hypotheses, and aims are provided
“We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
“ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
EXAMPLE 3. Background, aim, and hypothesis are provided
“In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
“This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
“ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

Conceptualization: Barroga E, Matanguihan GJ.
Methodology: Barroga E, Matanguihan GJ.
Writing - original draft: Barroga E, Matanguihan GJ.
Writing - review & editing: Barroga E, Matanguihan GJ.

Research Paper Guide

Research Paper Example

Research Paper Examples - Free Sample Papers for Different Formats!

Research Paper Example for Different Formats

Following a specific formatting style is essential while writing a research paper . Knowing the conventions and guidelines for each format can help you in creating a perfect paper. Here we have gathered examples of research paper for most commonly applied citation styles :

Social Media and Social Media Marketing: A Literature Review

APA Research Paper Example

APA (American Psychological Association) style is commonly used in social sciences, psychology, and education. This format is recognized for its clear and concise writing, emphasis on proper citations, and orderly presentation of ideas.

Here are some research paper examples in APA style:

Research Paper Example APA 7th Edition

Research Paper Example MLA

MLA (Modern Language Association) style is frequently employed in humanities disciplines, including literature, languages, and cultural studies. An MLA research paper might explore literature analysis, linguistic studies, or historical research within the humanities.

Here is an example:

Found Voices: Carl Sagan

Research Paper Example Chicago

Chicago style is utilized in various fields like history, arts, and social sciences. Research papers in Chicago style could delve into historical events, artistic analyses, or social science inquiries.

Here is a research paper formatted in Chicago style:

Chicago Research Paper Sample

Research Paper Example Harvard

Harvard style is widely used in business, management, and some social sciences. Research papers in Harvard style might address business strategies, case studies, or social policies.

View this sample Harvard style paper here:

Harvard Research Paper Sample

Examples for Different Research Paper Parts

A research paper has different parts. Each part is important for the overall success of the paper. Chapters in a research paper must be written correctly, using a certain format and structure.

The following are examples of how different sections of the research paper can be written.

Research Proposal

The research proposal acts as a detailed plan or roadmap for your study, outlining the focus of your research and its significance. It's essential as it not only guides your research but also persuades others about the value of your study.

Example of Research Proposal

An abstract serves as a concise overview of your entire research paper. It provides a quick insight into the main elements of your study. It summarizes your research's purpose, methods, findings, and conclusions in a brief format.

Research Paper Example Abstract

Literature Review

A literature review summarizes the existing research on your study's topic, showcasing what has already been explored. This section adds credibility to your own research by analyzing and summarizing prior studies related to your topic.

Literature Review Research Paper Example

Methodology

The methodology section functions as a detailed explanation of how you conducted your research. This part covers the tools, techniques, and steps used to collect and analyze data for your study.

Methods Section of Research Paper Example

How to Write the Methods Section of a Research Paper

The conclusion summarizes your findings, their significance and the impact of your research. This section outlines the key takeaways and the broader implications of your study's results.

Research Paper Conclusion Example

Research Paper Examples for Different Fields

Research papers can be about any subject that needs a detailed study. The following examples show research papers for different subjects.

History Research Paper Sample

Preparing a history research paper involves investigating and presenting information about past events. This may include exploring perspectives, analyzing sources, and constructing a narrative that explains the significance of historical events.

View this history research paper sample:

Many Faces of Generalissimo Fransisco Franco

Sociology Research Paper Sample

In sociology research, statistics and data are harnessed to explore societal issues within a particular region or group. These findings are thoroughly analyzed to gain an understanding of the structure and dynamics present within these communities.

Here is a sample:

A Descriptive Statistical Analysis within the State of Virginia

Science Fair Research Paper Sample

A science research paper involves explaining a scientific experiment or project. It includes outlining the purpose, procedures, observations, and results of the experiment in a clear, logical manner.

Here are some examples:

Science Fair Paper Format

What Do I Need To Do For The Science Fair?

Psychology Research Paper Sample

Writing a psychology research paper involves studying human behavior and mental processes. This process includes conducting experiments, gathering data, and analyzing results to understand the human mind, emotions, and behavior.

Here is an example psychology paper:

The Effects of Food Deprivation on Concentration and Perseverance

Art History Research Paper Sample

Studying art history includes examining artworks, understanding their historical context, and learning about the artists. This helps analyze and interpret how art has evolved over various periods and regions.

Check out this sample paper analyzing European art and impacts:

European Art History: A Primer

Research Paper Example Outline

Before you plan on writing a well-researched paper, make a rough draft. An outline can be a great help when it comes to organizing vast amounts of research material for your paper.

Here is an outline of a research paper example:

Here is a downloadable sample of a standard research paper outline:

Research Paper Outline

Want to create the perfect outline for your paper? Check out this in-depth guide on creating a research paper outline for a structured paper!

Good Research Paper Examples for Students

Here are some more samples of research paper for students to learn from:

Fiscal Research Center - Action Plan

Qualitative Research Paper Example

Research Paper Example Introduction

How to Write a Research Paper Example

Research Paper Example for High School

Now that you have explored the research paper examples, you can start working on your research project. Hopefully, these examples will help you understand the writing process for a research paper.

If you're facing challenges with your writing requirements, you can hire our essay writing service .

Our team is experienced in delivering perfectly formatted, 100% original research papers. So, whether you need help with a part of research or an entire paper, our experts are here to deliver.

So, why miss out? Place your ‘ write my research paper ’ request today and get a top-quality research paper!

Write Essay Within 60 Seconds!

Nova Allison is a Digital Content Strategist with over eight years of experience. Nova has also worked as a technical and scientific writer. She is majorly involved in developing and reviewing online content plans that engage and resonate with audiences. Nova has a passion for writing that engages and informs her readers.

Paper Due? Why Suffer? That’s our Job!

Keep reading

Our Mission

Illustration concept of people solving research problems and puzzles

The 10 Most Significant Education Studies of 2021

From reframing our notion of “good” schools to mining the magic of expert teachers, here’s a curated list of must-read research from 2021.

It was a year of unprecedented hardship for teachers and school leaders. We pored through hundreds of studies to see if we could follow the trail of exactly what happened: The research revealed a complex portrait of a grueling year during which persistent issues of burnout and mental and physical health impacted millions of educators. Meanwhile, many of the old debates continued: Does paper beat digital? Is project-based learning as effective as direct instruction? How do you define what a “good” school is?

Other studies grabbed our attention, and in a few cases, made headlines. Researchers from the University of Chicago and Columbia University turned artificial intelligence loose on some 1,130 award-winning children’s books in search of invisible patterns of bias. (Spoiler alert: They found some.) Another study revealed why many parents are reluctant to support social and emotional learning in schools—and provided hints about how educators can flip the script.

1. What Parents Fear About SEL (and How to Change Their Minds)

When researchers at the Fordham Institute asked parents to rank phrases associated with social and emotional learning , nothing seemed to add up. The term “social-emotional learning” was very unpopular; parents wanted to steer their kids clear of it. But when the researchers added a simple clause, forming a new phrase—”social-emotional & academic learning”—the program shot all the way up to No. 2 in the rankings.

What gives?

Parents were picking up subtle cues in the list of SEL-related terms that irked or worried them, the researchers suggest. Phrases like “soft skills” and “growth mindset” felt “nebulous” and devoid of academic content. For some, the language felt suspiciously like “code for liberal indoctrination.”

But the study suggests that parents might need the simplest of reassurances to break through the political noise. Removing the jargon, focusing on productive phrases like “life skills,” and relentlessly connecting SEL to academic progress puts parents at ease—and seems to save social and emotional learning in the process.

2. The Secret Management Techniques of Expert Teachers

In the hands of experienced teachers, classroom management can seem almost invisible: Subtle techniques are quietly at work behind the scenes, with students falling into orderly routines and engaging in rigorous academic tasks almost as if by magic.

That’s no accident, according to new research . While outbursts are inevitable in school settings, expert teachers seed their classrooms with proactive, relationship-building strategies that often prevent misbehavior before it erupts. They also approach discipline more holistically than their less-experienced counterparts, consistently reframing misbehavior in the broader context of how lessons can be more engaging, or how clearly they communicate expectations.

Focusing on the underlying dynamics of classroom behavior—and not on surface-level disruptions—means that expert teachers often look the other way at all the right times, too. Rather than rise to the bait of a minor breach in etiquette, a common mistake of new teachers, they tend to play the long game, asking questions about the origins of misbehavior, deftly navigating the terrain between discipline and student autonomy, and opting to confront misconduct privately when possible.

3. The Surprising Power of Pretesting

Asking students to take a practice test before they’ve even encountered the material may seem like a waste of time—after all, they’d just be guessing.

But new research concludes that the approach, called pretesting, is actually more effective than other typical study strategies. Surprisingly, pretesting even beat out taking practice tests after learning the material, a proven strategy endorsed by cognitive scientists and educators alike. In the study, students who took a practice test before learning the material outperformed their peers who studied more traditionally by 49 percent on a follow-up test, while outperforming students who took practice tests after studying the material by 27 percent.

The researchers hypothesize that the “generation of errors” was a key to the strategy’s success, spurring student curiosity and priming them to “search for the correct answers” when they finally explored the new material—and adding grist to a 2018 study that found that making educated guesses helped students connect background knowledge to new material.

Learning is more durable when students do the hard work of correcting misconceptions, the research suggests, reminding us yet again that being wrong is an important milestone on the road to being right.

4. Confronting an Old Myth About Immigrant Students

Immigrant students are sometimes portrayed as a costly expense to the education system, but new research is systematically dismantling that myth.

In a 2021 study , researchers analyzed over 1.3 million academic and birth records for students in Florida communities, and concluded that the presence of immigrant students actually has “a positive effect on the academic achievement of U.S.-born students,” raising test scores as the size of the immigrant school population increases. The benefits were especially powerful for low-income students.

While immigrants initially “face challenges in assimilation that may require additional school resources,” the researchers concluded, hard work and resilience may allow them to excel and thus “positively affect exposed U.S.-born students’ attitudes and behavior.” But according to teacher Larry Ferlazzo, the improvements might stem from the fact that having English language learners in classes improves pedagogy , pushing teachers to consider “issues like prior knowledge, scaffolding, and maximizing accessibility.”

5. A Fuller Picture of What a ‘Good’ School Is

It’s time to rethink our definition of what a “good school” is, researchers assert in a study published in late 2020.⁣ That’s because typical measures of school quality like test scores often provide an incomplete and misleading picture, the researchers found.

The study looked at over 150,000 ninth-grade students who attended Chicago public schools and concluded that emphasizing the social and emotional dimensions of learning—relationship-building, a sense of belonging, and resilience, for example—improves high school graduation and college matriculation rates for both high- and low-income students, beating out schools that focus primarily on improving test scores.⁣

“Schools that promote socio-emotional development actually have a really big positive impact on kids,” said lead researcher C. Kirabo Jackson in an interview with Edutopia . “And these impacts are particularly large for vulnerable student populations who don’t tend to do very well in the education system.”

The findings reinforce the importance of a holistic approach to measuring student progress, and are a reminder that schools—and teachers—can influence students in ways that are difficult to measure, and may only materialize well into the future.⁣

6. Teaching Is Learning

One of the best ways to learn a concept is to teach it to someone else. But do you actually have to step into the shoes of a teacher, or does the mere expectation of teaching do the trick?

In a 2021 study , researchers split students into two groups and gave them each a science passage about the Doppler effect—a phenomenon associated with sound and light waves that explains the gradual change in tone and pitch as a car races off into the distance, for example. One group studied the text as preparation for a test; the other was told that they’d be teaching the material to another student.

The researchers never carried out the second half of the activity—students read the passages but never taught the lesson. All of the participants were then tested on their factual recall of the Doppler effect, and their ability to draw deeper conclusions from the reading.

The upshot? Students who prepared to teach outperformed their counterparts in both duration and depth of learning, scoring 9 percent higher on factual recall a week after the lessons concluded, and 24 percent higher on their ability to make inferences. The research suggests that asking students to prepare to teach something—or encouraging them to think “could I teach this to someone else?”—can significantly alter their learning trajectories.

7. A Disturbing Strain of Bias in Kids’ Books

Some of the most popular and well-regarded children’s books—Caldecott and Newbery honorees among them—persistently depict Black, Asian, and Hispanic characters with lighter skin, according to new research .

Using artificial intelligence, researchers combed through 1,130 children’s books written in the last century, comparing two sets of diverse children’s books—one a collection of popular books that garnered major literary awards, the other favored by identity-based awards. The software analyzed data on skin tone, race, age, and gender.

Among the findings: While more characters with darker skin color begin to appear over time, the most popular books—those most frequently checked out of libraries and lining classroom bookshelves—continue to depict people of color in lighter skin tones. More insidiously, when adult characters are “moral or upstanding,” their skin color tends to appear lighter, the study’s lead author, Anjali Aduki, told The 74 , with some books converting “Martin Luther King Jr.’s chocolate complexion to a light brown or beige.” Female characters, meanwhile, are often seen but not heard.

Cultural representations are a reflection of our values, the researchers conclude: “Inequality in representation, therefore, constitutes an explicit statement of inequality of value.”

8. The Never-Ending ‘Paper Versus Digital’ War

The argument goes like this: Digital screens turn reading into a cold and impersonal task; they’re good for information foraging, and not much more. “Real” books, meanwhile, have a heft and “tactility” that make them intimate, enchanting—and irreplaceable.

But researchers have often found weak or equivocal evidence for the superiority of reading on paper. While a recent study concluded that paper books yielded better comprehension than e-books when many of the digital tools had been removed, the effect sizes were small. A 2021 meta-analysis further muddies the water: When digital and paper books are “mostly similar,” kids comprehend the print version more readily—but when enhancements like motion and sound “target the story content,” e-books generally have the edge.

Nostalgia is a force that every new technology must eventually confront. There’s plenty of evidence that writing with pen and paper encodes learning more deeply than typing. But new digital book formats come preloaded with powerful tools that allow readers to annotate, look up words, answer embedded questions, and share their thinking with other readers.

We may not be ready to admit it, but these are precisely the kinds of activities that drive deeper engagement, enhance comprehension, and leave us with a lasting memory of what we’ve read. The future of e-reading, despite the naysayers, remains promising.

9. New Research Makes a Powerful Case for PBL

Many classrooms today still look like they did 100 years ago, when students were preparing for factory jobs. But the world’s moved on: Modern careers demand a more sophisticated set of skills—collaboration, advanced problem-solving, and creativity, for example—and those can be difficult to teach in classrooms that rarely give students the time and space to develop those competencies.

Project-based learning (PBL) would seem like an ideal solution. But critics say PBL places too much responsibility on novice learners, ignoring the evidence about the effectiveness of direct instruction and ultimately undermining subject fluency. Advocates counter that student-centered learning and direct instruction can and should coexist in classrooms.

Now two new large-scale studies —encompassing over 6,000 students in 114 diverse schools across the nation—provide evidence that a well-structured, project-based approach boosts learning for a wide range of students.

In the studies, which were funded by Lucas Education Research, a sister division of Edutopia , elementary and high school students engaged in challenging projects that had them designing water systems for local farms, or creating toys using simple household objects to learn about gravity, friction, and force. Subsequent testing revealed notable learning gains—well above those experienced by students in traditional classrooms—and those gains seemed to raise all boats, persisting across socioeconomic class, race, and reading levels.

10. Tracking a Tumultuous Year for Teachers

The Covid-19 pandemic cast a long shadow over the lives of educators in 2021, according to a year’s worth of research.

The average teacher’s workload suddenly “spiked last spring,” wrote the Center for Reinventing Public Education in its January 2021 report, and then—in defiance of the laws of motion—simply never let up. By the fall, a RAND study recorded an astonishing shift in work habits: 24 percent of teachers reported that they were working 56 hours or more per week, compared to 5 percent pre-pandemic.

The vaccine was the promised land, but when it arrived nothing seemed to change. In an April 2021 survey conducted four months after the first vaccine was administered in New York City, 92 percent of teachers said their jobs were more stressful than prior to the pandemic, up from 81 percent in an earlier survey.

It wasn’t just the length of the work days; a close look at the research reveals that the school system’s failure to adjust expectations was ruinous. It seemed to start with the obligations of hybrid teaching, which surfaced in Edutopia ’s coverage of overseas school reopenings. In June 2020, well before many U.S. schools reopened, we reported that hybrid teaching was an emerging problem internationally, and warned that if the “model is to work well for any period of time,” schools must “recognize and seek to reduce the workload for teachers.” Almost eight months later, a 2021 RAND study identified hybrid teaching as a primary source of teacher stress in the U.S., easily outpacing factors like the health of a high-risk loved one.

New and ever-increasing demands for tech solutions put teachers on a knife’s edge. In several important 2021 studies, researchers concluded that teachers were being pushed to adopt new technology without the “resources and equipment necessary for its correct didactic use.” Consequently, they were spending more than 20 hours a week adapting lessons for online use, and experiencing an unprecedented erosion of the boundaries between their work and home lives, leading to an unsustainable “always on” mentality. When it seemed like nothing more could be piled on—when all of the lights were blinking red—the federal government restarted standardized testing .

Change will be hard; many of the pathologies that exist in the system now predate the pandemic. But creating strict school policies that separate work from rest, eliminating the adoption of new tech tools without proper supports, distributing surveys regularly to gauge teacher well-being, and above all listening to educators to identify and confront emerging problems might be a good place to start, if the research can be believed.

Open access
Published: 10 March 2020

Research and trends in STEM education: a systematic review of journal publications

Yeping Li 1 ,
Ke Wang 2 ,
Yu Xiao 1 &
Jeffrey E. Froyd 3

International Journal of STEM Education volume 7 , Article number: 11 ( 2020 ) Cite this article

163k Accesses

149 Citations

5 Altmetric

Metrics details

With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments in STEM education scholarship. We examined those selected journal publications both quantitatively and qualitatively, including the number of articles published, journals in which the articles were published, authorship nationality, and research topic and methods over the years. The results show that research in STEM education is increasing in importance internationally and that the identity of STEM education journals is becoming clearer over time.

Introduction

A recent review of 144 publications in the International Journal of STEM Education ( IJ - STEM ) showed how scholarship in science, technology, engineering, and mathematics (STEM) education developed between August 2014 and the end of 2018 through the lens of one journal (Li, Froyd, & Wang, 2019 ). The review of articles published in only one journal over a short period of time prompted the need to review the status and trends in STEM education research internationally by analyzing articles published in a wider range of journals over a longer period of time.

With global recognition of the growing importance of STEM education, we have witnessed the urgent need to support research and scholarship in STEM education (Li, 2014 , 2018a ). Researchers and educators have responded to this on-going call and published their scholarly work through many different publication outlets including journals, books, and conference proceedings. A simple Google search with the term “STEM,” “STEM education,” or “STEM education research” all returned more than 450,000,000 items. Such voluminous information shows the rapidly evolving and vibrant field of STEM education and sheds light on the volume of STEM education research. In any field, it is important to know and understand the status and trends in scholarship for the field to develop and be appropriately supported. This applies to STEM education.

Conducting systematic reviews to explore the status and trends in specific disciplines is common in educational research. For example, researchers surveyed the historical development of research in mathematics education (Kilpatrick, 1992 ) and studied patterns in technology usage in mathematics education (Bray & Tangney, 2017 ; Sokolowski, Li, & Willson, 2015 ). In science education, Tsai and his colleagues have conducted a sequence of reviews of journal articles to synthesize research trends in every 5 years since 1998 (i.e., 1998–2002, 2003–2007, 2008–2012, and 2013–2017), based on publications in three main science education journals including, Science Education , the International Journal of Science Education , and the Journal of Research in Science Teaching (e.g., Lin, Lin, Potvin, & Tsai, 2019 ; Tsai & Wen, 2005 ). Erduran, Ozdem, and Park ( 2015 ) reviewed argumentation in science education research from 1998 to 2014 and Minner, Levy, and Century ( 2010 ) reviewed inquiry-based science instruction between 1984 and 2002. There are also many literature reviews and syntheses in engineering and technology education (e.g., Borrego, Foster, & Froyd, 2015 ; Xu, Williams, Gu, & Zhang, 2019 ). All of these reviews have been well received in different fields of traditional disciplinary education as they critically appraise and summarize the state-of-art of relevant research in a field in general or with a specific focus. Both types of reviews have been conducted with different methods for identifying, collecting, and analyzing relevant publications, and they differ in terms of review aim and topic scope, time period, and ways of literature selection. In this review, we systematically analyze journal publications in STEM education research to overview STEM education scholarship development broadly and globally.

The complexity and ambiguity of examining the status and trends in STEM education research

A review of research development in a field is relatively straight forward, when the field is mature and its scope can be well defined. Unlike discipline-based education research (DBER, National Research Council, 2012 ), STEM education is not a well-defined field. Conducting a comprehensive literature review of STEM education research require careful thought and clearly specified scope to tackle the complexity naturally associated with STEM education. In the following sub-sections, we provide some further discussion.

Diverse perspectives about STEM and STEM education

STEM education as explicated by the term does not have a long history. The interest in helping students learn across STEM fields can be traced back to the 1990s when the US National Science Foundation (NSF) formally included engineering and technology with science and mathematics in undergraduate and K-12 school education (e.g., National Science Foundation, 1998 ). It coined the acronym SMET (science, mathematics, engineering, and technology) that was subsequently used by other agencies including the US Congress (e.g., United States Congress House Committee on Science, 1998 ). NSF also coined the acronym STEM to replace SMET (e.g., Christenson, 2011 ; Chute, 2009 ) and it has become the acronym of choice. However, a consensus has not been reached on the disciplines included within STEM.

To clarify its intent, NSF published a list of approved fields it considered under the umbrella of STEM (see http://bit.ly/2Bk1Yp5 ). The list not only includes disciplines widely considered under the STEM tent (called “core” disciplines, such as physics, chemistry, and materials research), but also includes disciplines in psychology and social sciences (e.g., political science, economics). However, NSF’s list of STEM fields is inconsistent with other federal agencies. Gonzalez and Kuenzi ( 2012 ) noted that at least two US agencies, the Department of Homeland Security and Immigration and Customs Enforcement, use a narrower definition that excludes social sciences. Researchers also view integration across different disciplines of STEM differently using various terms such as, multidisciplinary, interdisciplinary, and transdisciplinary (Vasquez, Sneider, & Comer, 2013 ). These are only two examples of the ambiguity and complexity in describing and specifying what constitutes STEM.

Multiple perspectives about the meaning of STEM education adds further complexity to determining the extent to which scholarly activity can be categorized as STEM education. For example, STEM education can be viewed with a broad and inclusive perspective to include education in the individual disciplines of STEM, i.e., science education, technology education, engineering education, and mathematics education, as well as interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines (English, 2016 ; Li, 2014 ). On the other hand, STEM education can be viewed by others as referring only to interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines (Honey, Pearson, & Schweingruber, 2014 ; Johnson, Peters-Burton, & Moore, 2015 ; Kelley & Knowles, 2016 ; Li, 2018a ). These multiple perspectives allow scholars to publish articles in a vast array and diverse journals, as long as journals are willing to take the position as connected with STEM education. At the same time, however, the situation presents considerable challenges for researchers intending to locate, identify, and classify publications as STEM education research. To tackle such challenges, we tried to find out what we can learn from prior reviews related to STEM education.

Guidance from prior reviews related to STEM education

A search for reviews of STEM education research found multiple reviews that could suggest approaches for identifying publications (e.g., Brown, 2012 ; Henderson, Beach, & Finkelstein, 2011 ; Kim, Sinatra, & Seyranian, 2018 ; Margot & Kettler, 2019 ; Minichiello, Hood, & Harkness, 2018 ; Mizell & Brown, 2016 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). The review conducted by Brown ( 2012 ) examined the research base of STEM education. He addressed the complexity and ambiguity by confining the review with publications in eight journals, two in each individual discipline, one academic research journal (e.g., the Journal of Research in Science Teaching ) and one practitioner journal (e.g., Science Teacher ). Journals were selected based on suggestions from some faculty members and K-12 teachers. Out of 1100 articles published in these eight journals from January 1, 2007, to October 1, 2010, Brown located 60 articles that authors self-identified as connected to STEM education. He found that the vast majority of these 60 articles focused on issues beyond an individual discipline and there was a research base forming for STEM education. In a follow-up study, Mizell and Brown ( 2016 ) reviewed articles published from January 2013 to October 2015 in the same eight journals plus two additional journals. Mizell and Brown used the same criteria to identify and include articles that authors self-identified as connected to STEM education, i.e., if the authors included STEM in the title or author-supplied keywords. In comparison to Brown’s findings, they found that many more STEM articles were published in a shorter time period and by scholars from many more different academic institutions. Taking together, both Brown ( 2012 ) and Mizell and Brown ( 2016 ) tended to suggest that STEM education mainly consists of interdisciplinary or cross-disciplinary combinations of the individual STEM disciplines, but their approach consisted of selecting a limited number of individual discipline-based journals and then selecting articles that authors self-identified as connected to STEM education.

In contrast to reviews on STEM education, in general, other reviews focused on specific issues in STEM education (e.g., Henderson et al., 2011 ; Kim et al., 2018 ; Margot & Kettler, 2019 ; Minichiello et al., 2018 ; Schreffler, Vasquez III, Chini, & James, 2019 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ). For example, the review by Henderson et al. ( 2011 ) focused on instructional change in undergraduate STEM courses based on 191 conceptual and empirical journal articles published between 1995 and 2008. Margot and Kettler ( 2019 ) focused on what is known about teachers’ values, beliefs, perceived barriers, and needed support related to STEM education based on 25 empirical journal articles published between 2000 and 2016. The focus of these reviews allowed the researchers to limit the number of articles considered, and they typically used keyword searches of selected databases to identify articles on STEM education. Some researchers used this approach to identify publications from journals only (e.g., Henderson et al., 2011 ; Margot & Kettler, 2019 ; Schreffler et al., 2019 ), and others selected and reviewed publications beyond journals (e.g., Minichiello et al., 2018 ; Thibaut et al., 2018 ; Wu & Rau, 2019 ).

The discussion in this section suggests possible reasons contributing to the absence of a general literature review of STEM education research and development: (1) diverse perspectives in existence about STEM and STEM education that contribute to the difficulty of specifying a scope of literature review, (2) its short but rapid development history in comparison to other discipline-based education (e.g., science education), and (3) difficulties in deciding how to establish the scope of the literature review. With respect to the third reason, prior reviews have used one of two approaches to identify and select articles: (a) identifying specific journals first and then searching and selecting specific articles from these journals (e.g., Brown, 2012 ; Erduran et al., 2015 ; Mizell & Brown, 2016 ) and (b) conducting selected database searches with keywords based on a specific focus (e.g., Margot & Kettler, 2019 ; Thibaut et al., 2018 ). However, neither the first approach of selecting a limited number of individual discipline-based journals nor the second approach of selecting a specific focus for the review leads to an approach that provides a general overview of STEM education scholarship development based on existing journal publications.

Current review

Two issues were identified in setting the scope for this review.

What time period should be considered?

What publications will be selected for review?

Time period

We start with the easy one first. As discussed above, the acronym STEM did exist until the early 2000s. Although the existence of the acronym does not generate scholarship on student learning in STEM disciplines, it is symbolic and helps focus attention to efforts in STEM education. Since we want to examine the status and trends in STEM education, it is reasonable to start with the year 2000. Then, we can use the acronym of STEM as an identifier in locating specific research articles in a way as done by others (e.g., Brown, 2012 ; Mizell & Brown, 2016 ). We chose the end of 2018 as the end of the time period for our review that began during 2019.

Focusing on publications beyond individual discipline-based journals

As mentioned before, scholars responded to the call for scholarship development in STEM education with publications that appeared in various outlets and diverse languages, including journals, books, and conference proceedings. However, journal publications are typically credited and valued as one of the most important outlets for research exchange (e.g., Erduran et al., 2015 ; Henderson et al., 2011 ; Lin et al., 2019 ; Xu et al., 2019 ). Thus, in this review, we will also focus on articles published in journals in English.

The discourse above on the complexity and ambiguity regarding STEM education suggests that scholars may publish their research in a wide range of journals beyond individual discipline-based journals. To search and select articles from a wide range of journals, we thought about the approach of searching selected databases with keywords as other scholars used in reviewing STEM education with a specific focus. However, existing journals in STEM education do not have a long history. In fact, IJ-STEM is the first journal in STEM education that has just been accepted into the Social Sciences Citation Index (SSCI) (Li, 2019a ). Publications in many STEM education journals are practically not available in several important and popular databases, such as the Web of Science and Scopus. Moreover, some journals in STEM education were not normalized due to a journal’s name change or irregular publication schedule. For example, the Journal of STEM Education was named as Journal of SMET Education when it started in 2000 in a print format, and the journal’s name was not changed until 2003, Vol 4 (3 and 4), and also went fully on-line starting 2004 (Raju & Sankar, 2003 ). A simple Google Scholar search with keywords will not be able to provide accurate information, unless you visit the journal’s website to check all publications over the years. Those added complexities prevented us from taking the database search as a viable approach. Thus, we decided to identify journals first and then search and select articles from these journals. Further details about the approach are provided in the “ Method ” section.

Research questions

Given a broader range of journals and a longer period of time to be covered in this review, we can examine some of the same questions as the IJ-STEM review (Li, Froyd, & Wang, 2019 ), but we do not have access to data on readership, articles accessed, or articles cited for the other journals selected for this review. Specifically, we are interested in addressing the following six research questions:

What were the status and trends in STEM education research from 2000 to the end of 2018 based on journal publications?

What were the patterns of publications in STEM education research across different journals?

Which countries or regions, based on the countries or regions in which authors were located, contributed to journal publications in STEM education?

What were the patterns of single-author and multiple-author publications in STEM education?

What main topics had emerged in STEM education research based on the journal publications?

What research methods did authors tend to use in conducting STEM education research?

Based on the above discussion, we developed the methods for this literature review to follow careful sequential steps to identify journals first and then identify and select STEM education research articles published in these journals from January 2000 to the end of 2018. The methods should allow us to obtain a comprehensive overview about the status and trends of STEM education research based on a systematic analysis of related publications from a broad range of journals and over a longer period of time.

Identifying journals

We used the following three steps to search and identify journals for inclusion:

We assumed articles on research in STEM education have been published in journals that involve more than one traditional discipline. Thus, we used Google to search and identify all education journals with their titles containing either two, three, or all four disciplines of STEM. For example, we did Google search of all the different combinations of three areas of science, mathematics, technology Footnote 1 , and engineering as contained in a journal’s title. In addition, we also searched possible journals containing the word STEAM in the title.

Since STEM education may be viewed as encompassing discipline-based education research, articles on STEM education research may have been published in traditional discipline-based education journals, such as the Journal of Research in Science Teaching . However, there are too many such journals. Yale’s Poorvu Center for Teaching and Learning has listed 16 journals that publish articles spanning across undergraduate STEM education disciplines (see https://poorvucenter.yale.edu/FacultyResources/STEMjournals ). Thus, we selected from the list some individual discipline-based education research journals, and also added a few more common ones such as the Journal of Engineering Education .

Since articles on research in STEM education have appeared in some general education research journals, especially those well-established ones. Thus, we identified and selected a few of those journals that we noticed some publications in STEM education research.

Following the above three steps, we identified 45 journals (see Table 1 ).

Identifying articles

In this review, we will not discuss or define the meaning of STEM education. We used the acronym STEM (or STEAM, or written as the phrase of “science, technology, engineering, and mathematics”) as a term in our search of publication titles and/or abstracts. To identify and select articles for review, we searched all items published in those 45 journals and selected only those articles that author(s) self-identified with the acronym STEM (or STEAM, or written as the phrase of “science, technology, engineering, and mathematics”) in the title and/or abstract. We excluded publications in the sections of practices, letters to editors, corrections, and (guest) editorials. Our search found 798 publications that authors self-identified as in STEM education, identified from 36 journals. The remaining 9 journals either did not have publications that met our search terms or published in another language other than English (see the two separate lists in Table 1 ).

Data analysis

To address research question 3, we analyzed authorship to examine which countries/regions contributed to STEM education research over the years. Because each publication may have either one or multiple authors, we used two different methods to analyze authorship nationality that have been recognized as valuable from our review of IJ-STEM publications (Li, Froyd, & Wang, 2019 ). The first method considers only the corresponding author’s (or the first author, if no specific indication is given about the corresponding author) nationality and his/her first institution affiliation, if multiple institution affiliations are listed. Method 2 considers every author of a publication, using the following formula (Howard, Cole, & Maxwell, 1987 ) to quantitatively assign and estimate each author’s contribution to a publication (and thus associated institution’s productivity), when multiple authors are included in a publication. As an example, each publication is given one credit point. For the publication co-authored by two, the first author would be given 0.6 and the second author 0.4 credit point. For an article contributed jointly by three authors, the three authors would be credited with scores of 0.47, 0.32, and 0.21, respectively.

After calculating all the scores for each author of each paper, we added all the credit scores together in terms of each author’s country/region. For brevity, we present only the top 10 countries/regions in terms of their total credit scores calculated using these two different methods, respectively.

To address research question 5, we used the same seven topic categories identified and used in our review of IJ-STEM publications (Li, Froyd, & Wang, 2019 ). We tested coding 100 articles first to ensure the feasibility. Through test-coding and discussions, we found seven topic categories could be used to examine and classify all 798 items.

K-12 teaching, teacher, and teacher education in STEM (including both pre-service and in-service teacher education)

Post-secondary teacher and teaching in STEM (including faculty development, etc.)

K-12 STEM learner, learning, and learning environment

Post-secondary STEM learner, learning, and learning environments (excluding pre-service teacher education)

Policy, curriculum, evaluation, and assessment in STEM (including literature review about a field in general)

Culture and social and gender issues in STEM education

History, epistemology, and perspectives about STEM and STEM education

To address research question 6, we coded all 798 publications in terms of (1) qualitative methods, (2) quantitative methods, (3) mixed methods, and (4) non-empirical studies (including theoretical or conceptual papers, and literature reviews). We assigned each publication to only one research topic and one method, following the process used in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). When there was more than one topic or method that could have been used for a publication, a decision was made in choosing and assigning a topic or a method. The agreement between two coders for all 798 publications was 89.5%. When topic and method coding discrepancies occurred, a final decision was reached after discussion.

Results and discussion

In the following sections, we report findings as corresponding to each of the six research questions.

The status and trends of journal publications in STEM education research from 2000 to 2018

Figure 1 shows the number of publications per year. As Fig. 1 shows, the number of publications increased each year beginning in 2010. There are noticeable jumps from 2015 to 2016 and from 2017 to 2018. The result shows that research in STEM education had grown significantly since 2010, and the most recent large number of STEM education publications also suggests that STEM education research gained its own recognition by many different journals for publication as a hot and important topic area.

The distribution of STEM education publications over the years

Among the 798 articles, there were 549 articles with the word “STEM” (or STEAM, or written with the phrase of “science, technology, engineering, and mathematics”) included in the article’s title or both title and abstract and 249 articles without such identifiers included in the title but abstract only. The results suggest that many scholars tended to include STEM in the publications’ titles to highlight their research in or about STEM education. Figure 2 shows the number of publications per year where publications are distinguished depending on whether they used the term STEM in the title or only in the abstract. The number of publications in both categories had significant increases since 2010. Use of the acronym STEM in the title was growing at a faster rate than using the acronym only in the abstract.

The trends of STEM education publications with vs. without STEM included in the title

Not all the publications that used the acronym STEM in the title and/or abstract reported on a study involving all four STEM areas. For each publication, we further examined the number of the four areas involved in the reported study.

Figure 3 presents the number of publications categorized by the number of the four areas involved in the study, breaking down the distribution of these 798 publications in terms of the content scope being focused on. Studies involving all four STEM areas are the most numerous with 488 (61.2%) publications, followed by involving one area (141, 17.7%), then studies involving both STEM and non-STEM (84, 10.5%), and finally studies involving two or three areas of STEM (72, 9%; 13, 1.6%; respectively). Publications that used the acronym STEAM in either the title or abstract were classified as involving both STEM and non-STEM. For example, both of the following publications were included in this category.

Dika and D’Amico ( 2016 ). “Early experiences and integration in the persistence of first-generation college students in STEM and non-STEM majors.” Journal of Research in Science Teaching , 53 (3), 368–383. (Note: this article focused on early experience in both STEM and Non-STEM majors.)

Sochacka, Guyotte, and Walther ( 2016 ). “Learning together: A collaborative autoethnographic exploration of STEAM (STEM+ the Arts) education.” Journal of Engineering Education , 105 (1), 15–42. (Note: this article focused on STEAM (both STEM and Arts).)

Publication distribution in terms of content scope being focused on. (Note: 1=single subject of STEM, 2=two subjects of STEM, 3=three subjects of STEM, 4=four subjects of STEM, 5=topics related to both STEM and non-STEM)

Figure 4 presents the number of publications per year in each of the five categories described earlier (category 1, one area of STEM; category 2, two areas of STEM; category 3, three areas of STEM; category 4, four areas of STEM; category 5, STEM and non-STEM). The category that had grown most rapidly since 2010 is the one involving all four areas. Recent growth in the number of publications in category 1 likely reflected growing interest of traditional individual disciplinary based educators in developing and sharing multidisciplinary and interdisciplinary scholarship in STEM education, as what was noted recently by Li and Schoenfeld ( 2019 ) with publications in IJ-STEM.

Publication distribution in terms of content scope being focused on over the years

Patterns of publications across different journals

Among the 36 journals that published STEM education articles, two are general education research journals (referred to as “subject-0”), 12 with their titles containing one discipline of STEM (“subject-1”), eight with journal’s titles covering two disciplines of STEM (“subject-2”), six covering three disciplines of STEM (“subject-3”), seven containing the word STEM (“subject-4”), and one in STEAM education (“subject-5”).

Table 2 shows that both subject-0 and subject-1 journals were usually mature journals with a long history, and they were all traditional subscription-based journals, except the Journal of Pre - College Engineering Education Research , a subject-1 journal established in 2011 that provided open access (OA). In comparison to subject-0 and subject-1 journals, subject-2 and subject-3 journals were relatively newer but still had quite many years of history on average. There are also some more journals in these two categories that provided OA. Subject-4 and subject-5 journals had a short history, and most provided OA. The results show that well-established journals had tended to focus on individual disciplines or education research in general. Multidisciplinary and interdisciplinary education journals were started some years later, followed by the recent establishment of several STEM or STEAM journals.

Table 2 also shows that subject-1, subject-2, and subject-4 journals published approximately a quarter each of the publications. The number of publications in subject-1 journals is interested, because we selected a relatively limited number of journals in this category. There are many other journals in the subject-1 category (as well as subject-0 journals) that we did not select, and thus it is very likely that we did not include some STEM education articles published in subject-0 or subject-1 journals that we did not include in our study.

Figure 5 shows the number of publications per year in each of the five categories described earlier (subject-0 through subject-5). The number of publications per year in subject-5 and subject-0 journals did not change much over the time period of the study. On the other hand, the number of publications per year in subject-4 (all 4 areas), subject-1 (single area), and subject-2 journals were all over 40 by the end of the study period. The number of publications per year in subject-3 journals increased but remained less than 30. At first sight, it may be a bit surprising that the number of publications in STEM education per year in subject-1 journals increased much faster than those in subject-2 journals over the past few years. However, as Table 2 indicates these journals had long been established with great reputations, and scholars would like to publish their research in such journals. In contrast to the trend in subject-1 journals, the trend in subject-4 journals suggests that STEM education journals collectively started to gain its own identity for publishing and sharing STEM education research.

STEM education publication distribution across different journal categories over the years. (Note: 0=subject-0; 1=subject-1; 2=subject-2; 3=subject-3; 4=subject-4; 5=subject-5)

Figure 6 shows the number of STEM education publications in each journal where the bars are color-coded (yellow, subject-0; light blue, subject-1; green, subject-2; purple, subject-3; dark blue, subject-4; and black, subject-5). There is no clear pattern shown in terms of the overall number of STEM education publications across categories or journals, but very much individual journal-based performance. The result indicates that the number of STEM education publications might heavily rely on the individual journal’s willingness and capability of attracting STEM education research work and thus suggests the potential value of examining individual journal’s performance.

Publication distribution across all 36 individual journals across different categories with the same color-coded for journals in the same subject category

The top five journals in terms of the number of STEM education publications are Journal of Science Education and Technology (80 publications, journal number 25 in Fig. 6 ), Journal of STEM Education (65 publications, journal number 26), International Journal of STEM Education (64 publications, journal number 17), International Journal of Engineering Education (54 publications, journal number 12), and School Science and Mathematics (41 publications, journal number 31). Among these five journals, two journals are specifically on STEM education (J26, J17), two on two subjects of STEM (J25, J31), and one on one subject of STEM (J12).

Figure 7 shows the number of STEM education publications per year in each of these top five journals. As expected, based on earlier trends, the number of publications per year increased over the study period. The largest increase was in the International Journal of STEM Education (J17) that was established in 2014. As the other four journals were all established in or before 2000, J17’s short history further suggests its outstanding performance in attracting and publishing STEM education articles since 2014 (Li, 2018b ; Li, Froyd, & Wang, 2019 ). The increase was consistent with the journal’s recognition as the first STEM education journal for inclusion in SSCI starting in 2019 (Li, 2019a ).

Publication distribution of selected five journals over the years. (Note: J12: International Journal of Engineering Education; J17: International Journal of STEM Education; J25: Journal of Science Education and Technology; J26: Journal of STEM Education; J31: School Science and Mathematics)

Top 10 countries/regions where scholars contributed journal publications in STEM education

Table 3 shows top countries/regions in terms of the number of publications, where the country/region was established by the authorship using the two different methods presented above. About 75% (depending on the method) of contributions were made by authors from the USA, followed by Australia, Canada, Taiwan, and UK. Only Africa as a continent was not represented among the top 10 countries/regions. The results are relatively consistent with patterns reported in the IJ-STEM study (Li, Froyd, & Wang, 2019 )

Further examination of Table 3 reveals that the two methods provide not only fairly consistent results but also yield some differences. For example, Israel and Germany had more publication credit if only the corresponding author was considered, but South Korea and Turkey had more publication credit when co-authors were considered. The results in Table 3 show that each method has value when analyzing and comparing publications by country/region or institution based on authorship.

Recognizing that, as shown in Fig. 1 , the number of publications per year increased rapidly since 2010, Table 4 shows the number of publications by country/region over a 10-year period (2009–2018) and Table 5 shows the number of publications by country/region over a 5-year period (2014–2018). The ranks in Tables 3 , 4 , and 5 are fairly consistent, but that would be expected since the larger numbers of publications in STEM education had occurred in recent years. At the same time, it is interesting to note in Table 5 some changes over the recent several years with Malaysia, but not Israel, entering the top 10 list when either method was used to calculate author's credit.

Patterns of single-author and multiple-author publications in STEM education

Since STEM education differs from traditional individual disciplinary education, we are interested in determining how common joint co-authorship with collaborations was in STEM education articles. Figure 8 shows that joint co-authorship was very common among these 798 STEM education publications, with 83.7% publications with two or more co-authors. Publications with two, three, or at least five co-authors were highest, with 204, 181, and 157 publications, respectively.

Number of publications with single or different joint authorship. (Note: 1=single author; 2=two co-authors; 3=three co-authors; 4=four co-authors; 5=five or more co-authors)

Figure 9 shows the number of publications per year using the joint authorship categories in Fig. 8 . Each category shows an increase consistent with the increase shown in Fig. 1 for all 798 publications. By the end of the time period, the number of publications with two, three, or at least five co-authors was the largest, which might suggest an increase in collaborations in STEM education research.

Publication distribution with single or different joint authorship over the years. (Note: 1=single author; 2=two co-authors; 3=three co-authors; 4=four co-authors; 5=five or more co-authors)

Co-authors can be from the same or different countries/regions. Figure 10 shows the number of publications per year by single authors (no collaboration), co-authors from the same country (collaboration in a country/region), and co-authors from different countries (collaboration across countries/regions). Each year the largest number of publications was by co-authors from the same country, and the number increased dramatically during the period of the study. Although the number of publications in the other two categories increased, the numbers of publications were noticeably fewer than the number of publications by co-authors from the same country.

Publication distribution in authorship across different categories in terms of collaboration over the years

Published articles by research topics

Figure 11 shows the number of publications in each of the seven topic categories. The topic category of goals, policy, curriculum, evaluation, and assessment had almost half of publications (375, 47%). Literature reviews were included in this topic category, as providing an overview assessment of education and research development in a topic area or a field. Sample publications included in this category are listed as follows:

DeCoito ( 2016 ). “STEM education in Canada: A knowledge synthesis.” Canadian Journal of Science , Mathematics and Technology Education , 16 (2), 114–128. (Note: this article provides a national overview of STEM initiatives and programs, including success, criteria for effective programs and current research in STEM education.)

Ring-Whalen, Dare, Roehrig, Titu, and Crotty ( 2018 ). “From conception to curricula: The role of science, technology, engineering, and mathematics in integrated STEM units.” International Journal of Education in Mathematics Science and Technology , 6 (4), 343–362. (Note: this article investigates the conceptions of integrated STEM education held by in-service science teachers through the use of photo-elicitation interviews and examines how those conceptions were reflected in teacher-created integrated STEM curricula.)

Schwab et al. ( 2018 ). “A summer STEM outreach program run by graduate students: Successes, challenges, and recommendations for implementation.” Journal of Research in STEM Education , 4 (2), 117–129. (Note: the article details the organization and scope of the Foundation in Science and Mathematics Program and evaluates this program.)

Frequencies of publications’ research topic distributions. (Note: 1=K-12 teaching, teacher and teacher education; 2=Post-secondary teacher and teaching; 3=K-12 STEM learner, learning, and learning environment; 4=Post-secondary STEM learner, learning, and learning environments; 5=Goals and policy, curriculum, evaluation, and assessment (including literature review); 6=Culture, social, and gender issues; 7=History, philosophy, Epistemology, and nature of STEM and STEM education)

The topic with the second most publications was “K-12 teaching, teacher and teacher education” (103, 12.9%), followed closely by “K-12 learner, learning, and learning environment” (97, 12.2%). The results likely suggest the research community had a broad interest in both teaching and learning in K-12 STEM education. The top three topics were the same in the IJ-STEM review (Li, Froyd, & Wang, 2019 ).

Figure 11 also shows there was a virtual tie between two topics with the fourth most cumulative publications, “post-secondary STEM learner & learning” (76, 9.5%) and “culture, social, and gender issues in STEM” (78, 9.8%), such as STEM identity, students’ career choices in STEM, and inclusion. This result is different from the IJ-STEM review (Li, Froyd, & Wang, 2019 ), where “post-secondary STEM teacher & teaching” and “post-secondary STEM learner & learning” were tied as the fourth most common topics. This difference is likely due to the scope of journals and the length of the time period being reviewed.

Figure 12 shows the number of publications per year in each topic category. As expected from the results in Fig. 11 the number of publications in topic category 5 (goals, policy, curriculum, evaluation, and assessment) was the largest each year. The numbers of publications in topic category 3 (K-12 learner, learning, and learning environment), 1 (K-12 teaching, teacher, and teacher education), 6 (culture, social, and gender issues in STEM), and 4 (post-secondary STEM learner and learning) were also increasing. Although Fig. 11 shows the number of publications in topic category 1 was slightly more than the number of publications in topic category 3 (see Fig. 11 ), the number of publications in topic category 3 was increasing more rapidly in recent years than its counterpart in topic category 1. This may suggest a more rapidly growing interest in K-12 STEM learner, learning, and learning environment. The numbers of publications in topic categories 2 and 7 were not increasing, but the number of publications in IJ-STEM in topic category 2 was notable (Li, Froyd, & Wang, 2019 ). It will be interesting to follow trends in the seven topic categories in the future.

Publication distributions in terms of research topics over the years

Published articles by research methods

Figure 13 shows the number of publications per year by research methods in empirical studies. Publications with non-empirical studies are shown in a separate category. Although the number of publications in each of the four categories increased during the study period, there were many more publications presenting empirical studies than those without. For those with empirical studies, the number of publications using quantitative methods increased most rapidly in recent years, followed by qualitative and then mixed methods. Although there were quite many publications with non-empirical studies (e.g., theoretical or conceptual papers, literature reviews) during the study period, the increase of the number of publications in this category was noticeably less than empirical studies.

Publication distributions in terms of research methods over the years. (Note: 1=qualitative, 2=quantitative, 3=mixed, 4=Non-empirical)

Concluding remarks

The systematic analysis of publications that were considered to be in STEM education in 36 selected journals shows tremendous growth in scholarship in this field from 2000 to 2018, especially over the past 10 years. Our analysis indicates that STEM education research has been increasingly recognized as an important topic area and studies were being published across many different journals. Scholars still hold diverse perspectives about how research is designated as STEM education; however, authors have been increasingly distinguishing their articles with STEM, STEAM, or related words in the titles, abstracts, and lists of keywords during the past 10 years. Moreover, our systematic analysis shows a dramatic increase in the number of publications in STEM education journals in recent years, which indicates that these journals have been collectively developing their own professional identity. In addition, the International Journal of STEM Education has become the first STEM education journal to be accepted in SSCI in 2019 (Li, 2019a ). The achievement may mark an important milestone as STEM education journals develop their own identity for publishing and sharing STEM education research.

Consistent with our previous reviews (Li, Froyd, & Wang, 2019 ; Li, Wang, & Xiao, 2019 ), the vast majority of publications in STEM education research were contributed by authors from the USA, where STEM and STEAM education originated, followed by Australia, Canada, and Taiwan. At the same time, authors in some countries/regions in Asia were becoming very active in the field over the past several years. This trend is consistent with findings from the IJ-STEM review (Li, Froyd, & Wang, 2019 ). We certainly hope that STEM education scholarship continues its development across all five continents to support educational initiatives and programs in STEM worldwide.

Our analysis has shown that collaboration, as indicated by publications with multiple authors, has been very common among STEM education scholars, as that is often how STEM education distinguishes itself from the traditional individual disciplinary based education. Currently, most collaborations occurred among authors from the same country/region, although collaborations across cross-countries/regions were slowly increasing.

With the rapid changes in STEM education internationally (Li, 2019b ), it is often difficult for researchers to get an overall sense about possible hot topics in STEM education especially when STEM education publications appeared in a vast array of journals across different fields. Our systematic analysis of publications has shown that studies in the topic category of goals, policy, curriculum, evaluation, and assessment have been the most prevalent, by far. Our analysis also suggests that the research community had a broad interest in both teaching and learning in K-12 STEM education. These top three topic categories are the same as in the IJ-STEM review (Li, Froyd, & Wang, 2019 ). Work in STEM education will continue to evolve and it will be interesting to review the trends in another 5 years.

Encouraged by our recent IJ-STEM review, we began this review with an ambitious goal to provide an overview of the status and trends of STEM education research. In a way, this systematic review allowed us to achieve our initial goal with a larger scope of journal selection over a much longer period of publication time. At the same time, there are still limitations, such as the decision to limit the number of journals from which we would identify publications for analysis. We understand that there are many publications on STEM education research that were not included in our review. Also, we only identified publications in journals. Although this is one of the most important outlets for scholars to share their research work, future reviews could examine publications on STEM education research in other venues such as books, conference proceedings, and grant proposals.

Availability of data and materials

The data and materials used and analyzed for the report are publicly available at the various journal websites.

Journals containing the word "computers" or "ICT" appeared automatically when searching with the word "technology". Thus, the word of "computers" or "ICT" was taken as equivalent to "technology" if appeared in a journal's name.

Abbreviations

Information and Communications Technology

International Journal of STEM Education

Kindergarten–Grade 12

Science, Mathematics, Engineering, and Technology

Science, Technology, Engineering, Arts, and Mathematics

Science, Technology, Engineering, and Mathematics

Borrego, M., Foster, M. J., & Froyd, J. E. (2015). What is the state of the art of systematic review in engineering education? Journal of Engineering Education, 104 (2), 212–242. https://doi.org/10.1002/jee.20069 .

Article Google Scholar

Bray, A., & Tangney, B. (2017). Technology usage in mathematics education research – a systematic review of recent trends. Computers & Education, 114 , 255–273.

Brown, J. (2012). The current status of STEM education research. Journal of STEM Education: Innovations & Research, 13 (5), 7–11.

Google Scholar

Christenson, J. (2011). Ramaley coined STEM term now used nationwide . Winona Daily News Retrieved from http://www.winonadailynews.com/news/local/article_457afe3e-0db3-11e1-abe0-001cc4c03286.html Accessed on 16 Jan 2018.

Chute, E. (2009). STEM education is branching out . Pittsburgh Post-Gazette Feb 9, 2009. https://www.post-gazette.com/news/education/2009/02/10/STEM-education-is-branching-out/stories/200902100165 Accessed on 2 Jan 2020.

DeCoito, I. (2016). STEM education in Canada: A knowledge synthesis. Canadian Journal of Science, Mathematics and Technology Education, 16 (2), 114–128.

Dika, S. L., & D'Amico, M. M. (2016). Early experiences and integration in the persistence of first-generation college students in STEM and non-STEM majors. Journal of Research in Science Teaching, 53 (3), 368–383.

English, L. D. (2016). STEM education K-12: Perspectives on integration. International Journal of STEM Education, 3 , 3. https://doi.org/10.1186/s4059%204-016-0036-1 .

Erduran, S., Ozdem, Y., & Park, J.-Y. (2015). Research trends on argumentation in science education: A journal content analysis from 1998-2014. International Journal of STEM Education, 2 , 5. https://doi.org/10.1186/s40594-015-0020-1 .

Gonzalez, H. B. & Kuenzi, J. J. (2012). Science, technology, engineering, and mathematics (STEM) education: A primer. CRS report for congress, R42642, https://fas.org/sgp/crs/misc/R42642.pdf Accessed on 2 Jan 2020.

Henderson, C., Beach, A., & Finkelstein, N. (2011). Facilitating change in undergraduate STEM instructional practices: An analytic review of the literature. Journal of Research in Science Teaching, 48 (8), 952–984.

Honey, M., Pearson, G., & Schweingruber, A. (2014). STEM integration in K-12 education: Status, prospects, and an agenda for research . Washington: National Academies Press.

Howard, G. S., Cole, D. A., & Maxwell, S. E. (1987). Research productivity in psychology based on publication in the journals of the American Psychological Association. American Psychologist, 42 (11), 975–986.

Johnson, C. C., Peters-Burton, E. E., & Moore, T. J. (2015). STEM roadmap: A framework for integration . London: Taylor & Francis.

Book Google Scholar

Kelley, T. R., & Knowles, J. G. (2016). A conceptual framework for integrated STEM education. International Journal of STEM Education, 3 , 11. https://doi.org/10.1186/s40594-016-0046-z .

Kilpatrick, J. (1992). A history of research in mathematics education. In D. A. Grouws (Ed.), Handbook of research on mathematics teaching and learning (pp. 3–38). New York: Macmillan.

Kim, A. Y., Sinatra, G. M., & Seyranian, V. (2018). Developing a STEM identity among young women: A social identity perspective. Review of Educational Research, 88 (4), 589–625.

Li, Y. (2014). International journal of STEM education – a platform to promote STEM education and research worldwide. International Journal of STEM Education, 1 , 1. https://doi.org/10.1186/2196-7822-1-1 .

Li, Y. (2018a). Journal for STEM education research – promoting the development of interdisciplinary research in STEM education. Journal for STEM Education Research, 1 (1–2), 1–6. https://doi.org/10.1007/s41979-018-0009-z .

Li, Y. (2018b). Four years of development as a gathering place for international researchers and readers in STEM education. International Journal of STEM Education, 5 , 54. https://doi.org/10.1186/s40594-018-0153-0 .

Li, Y. (2019a). Five years of development in pursuing excellence in quality and global impact to become the first journal in STEM education covered in SSCI. International Journal of STEM Education, 6 , 42. https://doi.org/10.1186/s40594-019-0198-8 .

Li, Y. (2019b). STEM education research and development as a rapidly evolving and international field. 数学教育学报(Journal of Mathematics Education), 28 (3), 42–44.

Li, Y., Froyd, J. E., & Wang, K. (2019). Learning about research and readership development in STEM education: A systematic analysis of the journal’s publications from 2014 to 2018. International Journal of STEM Education, 6 , 19. https://doi.org/10.1186/s40594-019-0176-1 .

Li, Y., & Schoenfeld, A. H. (2019). Problematizing teaching and learning mathematics as ‘given’ in STEM education. International Journal of STEM Education, 6 , 44. https://doi.org/10.1186/s40594-019-0197-9 .

Li, Y., Wang, K., & Xiao, Y. (2019). Exploring the status and development trends of STEM education research: A review of research articles in selected journals published between 2000 and 2018. 数学教育学报(Journal of Mathematics Education), 28 (3), 45–52.

Lin, T.-J., Lin, T.-C., Potvin, P., & Tsai, C.-C. (2019). Research trends in science education from 2013 to 2017: A systematic content analysis of publications in selected journals. International Journal of Science Education, 41 (3), 367–387.

Margot, K. C., & Kettler, T. (2019). Teachers’ perception of STEM integration and education: A systematic literature review. International Journal of STEM Education, 6 , 2. https://doi.org/10.1186/s40594-018-0151-2 .

Minichiello, A., Hood, J. R., & Harkness, D. S. (2018). Bring user experience design to bear on STEM education: A narrative literature review. Journal for STEM Education Research, 1 (1–2), 7–33.

Minner, D. D., Levy, A. J., & Century, J. (2010). Inquiry-based science instruction – what is it and does it matter? Results from a research synthesis years 1984 to 2002. Journal of Research in Science Teaching, 47 (4), 474–496.

Mizell, S., & Brown, S. (2016). The current status of STEM education research 2013-2015. Journal of STEM Education: Innovations & Research, 17 (4), 52–56.

National Research Council. (2012). Discipline-based education research: Understanding and improving learning in undergraduate science and engineering . Washington DC: National Academies Press.

National Science Foundation (1998). Information technology: Its impact on undergraduate education in science, mathematics, engineering, and technology. (NSF 98–82), April 18–20, 1996. http://www.nsf.gov/cgi-bin/getpub?nsf9882 Accessed 16 Jan 2018.

Raju, P. K., & Sankar, C. S. (2003). Editorial. Journal of STEM Education: Innovations & Research, 4 (3&4), 2.

Ring-Whalen, E., Dare, E., Roehrig, G., Titu, P., & Crotty, E. (2018). From conception to curricula: The role of science, technology, engineering, and mathematics in integrated STEM units. International Journal of Education in Mathematics, Science and Technology, 6 (4), 343–362.

Schreffler, J., Vasquez III, E., Chini, J., & James, W. (2019). Universal design for learning in postsecondary STEM education for students with disabilities: A systematic literature review. International Journal of STEM Education, 6 , 8. https://doi.org/10.1186/s40594-019-0161-8 .

Schwab, D. B., Cole, L. W., Desai, K. M., Hemann, J., Hummels, K. R., & Maltese, A. V. (2018). A summer STEM outreach program run by graduate students: Successes, challenges, and recommendations for implementation. Journal of Research in STEM Education, 4 (2), 117–129.

Sochacka, N. W., Guyotte, K. W., & Walther, J. (2016). Learning together: A collaborative autoethnographic exploration of STEAM (STEM+ the Arts) education. Journal of Engineering Education, 105 (1), 15–42.

Sokolowski, A., Li, Y., & Willson, V. (2015). The effects of using exploratory computerized environments in grades 1 to 8 mathematics: A meta-analysis of research. International Journal of STEM Education, 2 , 8. https://doi.org/10.1186/s40594-015-0022-z .

Thibaut, L., Ceuppens, S., De Loof, H., De Meester, J., Goovaerts, L., Struyf, A., Pauw, J. B., Dehaene, W., Deprez, J., De Cock, M., Hellinckx, L., Knipprath, H., Langie, G., Struyven, K., Van de Velde, D., Van Petegem, P., & Depaepe, F. (2018). Integrated STEM education: A systematic review of instructional practices in secondary education. European Journal of STEM Education, 3 (1), 2.

Tsai, C. C., & Wen, L. M. C. (2005). Research and trends in science education from 1998 to 2002: A content analysis of publication in selected journals. International Journal of Science Education, 27 (1), 3–14.

United States Congress House Committee on Science. (1998). The state of science, math, engineering, and technology (SMET) education in America, parts I-IV, including the results of the Third International Mathematics and Science Study (TIMSS): hearings before the Committee on Science, U.S. House of Representatives, One Hundred Fifth Congress, first session, July 23, September 24, October 8 and 29, 1997. Washington: U.S. G.P.O.

Vasquez, J., Sneider, C., & Comer, M. (2013). STEM lesson essentials, grades 3–8: Integrating science, technology, engineering, and mathematics . Portsmouth, NH: Heinemann.

Wu, S. P. W., & Rau, M. A. (2019). How students learn content in science, technology, engineering, and mathematics (STEM) through drawing activities. Educational Psychology Review . https://doi.org/10.1007/s10648-019-09467-3 .

Xu, M., Williams, P. J., Gu, J., & Zhang, H. (2019). Hotspots and trends of technology education in the International Journal of Technology and Design Education: 2000-2018. International Journal of Technology and Design Education . https://doi.org/10.1007/s10798-019-09508-6 .

Download references

Not applicable

Author information

Authors and affiliations.

Texas A&M University, College Station, TX, 77843-4232, USA

Yeping Li & Yu Xiao

Nicholls State University, Thibodaux, LA, 70310, USA

Ohio State University, Columbus, OH, 43210, USA

Jeffrey E. Froyd

You can also search for this author in PubMed Google Scholar

Contributions

YL conceptualized the study and drafted the manuscript. KW and YX contributed with data collection, coding, and analyses. JEF reviewed drafts and contributed to manuscript revisions. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Yeping Li .

Ethics declarations

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/ ), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and permissions

About this article

Cite this article.

Li, Y., Wang, K., Xiao, Y. et al. Research and trends in STEM education: a systematic review of journal publications. IJ STEM Ed 7 , 11 (2020). https://doi.org/10.1186/s40594-020-00207-6

Download citation

Received : 10 February 2020

Accepted : 12 February 2020

Published : 10 March 2020

DOI : https://doi.org/10.1186/s40594-020-00207-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Journal publication
Literature review
STEM education research

Investigative Research Projects for Students in Science: The State of the Field and a Research Agenda

Open access
Published: 16 March 2023
Volume 23 , pages 80–95, ( 2023 )

Cite this article

You have full access to this open access article

Michael J. Reiss ORCID: orcid.org/0000-0003-1207-4229 1 ,
Richard Sheldrake ORCID: orcid.org/0000-0002-2909-6478 1 &
Wilton Lodge ORCID: orcid.org/0000-0002-9219-8880 1

3152 Accesses

2 Citations

6 Altmetric

Explore all metrics

One of the ways in which students can be taught science is by doing science, the intention being to help students understand the nature, processes, and methods of science. Investigative research projects may be used in an attempt to reflect some aspects of science more authentically than other teaching and learning approaches, such as confirmatory practical activities and teacher demonstrations. In this article, we are interested in the affordances of investigative research projects where students, either individually or collaboratively, undertake original research. We provide a critical rather than a systematic review of the field. We begin by examining the literature on the aims of science education, and how science is taught in schools, before specifically turning to investigative research projects. We examine how such projects are typically undertaken before reviewing their aims and, in more detail, the consequences for students of undertaking such projects. We conclude that we need social science research studies that make explicit the possible benefits of investigative research projects in science. Such studies should have adequate control groups that look at the long-term consequences of such projects not only by collecting delayed data from participants, but by following them longitudinally to see whether such projects make any difference to participants’ subsequent education and career destinations. We also conclude that there is too often a tendency for investigative research projects for students in science to ignore the reasons why scientists work in particular areas and to assume that once a written report of the research has been authored, the work is done. We therefore, while being positive about the potential for investigative research projects, make specific recommendations as to how greater authenticity might result from students undertaking such projects.

L’une des façons d’enseigner les sciences aux étudiants est de leur faire faire des activités scientifiques, l’objectif étant de les aider à comprendre la nature, les processus et les méthodes de la science. On peut avoir recours à des projets de recherche et d’enquête afin de refléter plus fidèlement certains éléments relevant de la science qu’en utilisant d’autres approches d’enseignement et d’apprentissage, telles que les activités pratiques de confirmation et les démonstrations faites par l’enseignant. Dans cet article, nous nous intéressons aux possibilités offertes par les projets de recherche dans lesquels les étudiants, individuellement ou en collaboration, entreprennent des recherches novatrices. Nous proposons un examen critique du domaine plutôt que d’y porter un regard systématique. Nous commençons par examiner la documentation portant sur les objectifs de l’enseignement des sciences et la manière dont les sciences sont enseignées dans les écoles, avant de nous intéresser plus particulièrement aux projets de recherche et d’enquête. Nous analysons la manière dont ces projets sont généralement menés avant d’examiner leurs buts et d’évaluer de façon plus approfondie quelles sont les conséquences pour les élèves de réaliser de tels projets. Nous constatons que nous avons besoin d’études de recherche en sciences sociales qui rendent explicites les avantages potentiels des projets de recherche et d’enquête scientifiques. Ces études devraient comporter des groupes de contrôle adéquats qui examinent les conséquences à long terme de ces projets, non seulement en recueillant des données différées auprès des participants, mais aussi en suivant ceux-ci de manière longitudinale de façon à voir si ces projets font une quelconque différence dans l’éducation subséquente et les destinations professionnelles ultérieures des participants. Nous concluons également que les projets de recherche et d’enquête des étudiants en sciences ont trop souvent tendance à ignorer les raisons pour lesquelles les scientifiques travaillent dans des domaines particuliers et à supposer qu’une fois que le rapport de recherche a été rédigé, le travail est terminé. Par conséquent, tout en demeurant optimistes quant au potentiel que représentent les projets de recherche et d’enquête, nous formulons des recommandations particulières en ce qui a trait à la manière dont une plus grande authenticité pourrait résulter de la réalisation de tels projets par les étudiants.

Investigative School Research Projects in Biology: Effects on Students

Moving Research into the Classroom: Synergy in Collaboration

Reintroducing “the” Scientific Method to Introduce Scientific Inquiry in Schools?

Markus Emden

Avoid common mistakes on your manuscript.

Introduction

Many young people are interested in science but do not necessarily see themselves as able to become scientists (Archer & DeWitt, 2017 ; Archer et al., 2015 ). Others may not want to become scientists even though they may see themselves as succeeding in science (Gokpinar & Reiss, 2016 ). At the same time, in many countries, governments and industry want more young people to continue with science, primarily in the hope that they will go into science or science-related careers (including engineering and technology), but also because of the benefits to society that are presumed to flow from having a scientifically literate population. Making science more inclusive and accessible to everyone may need endeavours and support from across education, employers, and society (Royal Society, 2014 ; Institute of Physics, 2020 ).

However, getting more people to continue with science, once it is no longer compulsory, is only one purpose of school science (Mansfield & Reiss, 2020 ). Much of school science is focused on getting students to understand core content of science—things like the particulate theory of matter, and the causes of disease in humans and other organisms. Another strand in school science is on getting students to understand something of the practices of science, particularly through undertaking practical work. A further, recently emerging, position is that science education should help students to use their knowledge and critical understanding of the content and practices of science to strive for social and environmental justice (Sjöström & Eilks, 2018 ).

In this article, we are interested in the affordances of investigative research projects—discussed in more detail below but essentially pieces of work undertaken by students either individually or collaboratively in which they undertake original research. We provide a critical rather than a systematic review of the field and suggest how future research might be undertaken to explore in more detail the possible contribution of such projects. We begin by examining the literature on the aims of science education, and how science is taught in schools, before specifically turning to investigative research projects. We examine how such projects are typically undertaken before reviewing their aims and, in more detail, the consequences for students of undertaking such projects. We make recommendations as to how investigative research projects might more fruitfully be undertaken and conclude by proposing a research agenda.

Aims of Science Education

School science education typically aims to prepare some students to become scientists, while concurrently educating all students in science and about science (Claussen & Osborne, 2013 ; Hofstein & Lunetta, 2004 ; Osborne & Dillon, 2008 ). For example, in England, especially for older students, the current science National Curriculum for 5–16-year-olds is framed as providing a platform for future studies and careers in science for some students, and providing knowledge and skills so that all students can understand and engage with the natural world within their everyday lives (Department for Education, 2014 ). Accordingly, science education within the National Curriculum in England broadly aims to develop students’ scientific knowledge and conceptual understanding; develop students’ understanding of the nature, processes, and methods of science (aspects of ‘working scientifically’, including experimental, analytical, and other related skills); and ensure that students understand the relevance, uses, and implications of science within everyday life (Department for Education, 2014 ). Comparable aims are typically found in other countries (Coll & Taylor, 2012 ; Hollins & Reiss, 2016 ).

Science education often involves practical work, which is generally intended to help students gain conceptual understanding, practical and wider skills, and understanding of how science and scientists work (Abrahams & Reiss, 2017 ; Cukurova et al., 2015 ; Hodson, 1993 ; Millar, 1998 ). Essentially, the thinking behind much practical work is that students would learn about science by doing science. Practical work has often been orientated towards confirming and illustrating scientific knowledge, although it is increasingly orientated around reflecting the processes of investigation and inquiry used within the field of science, and providing understanding of the nature of science (Abrahams & Reiss, 2017 ; Hofstein & Lunetta, 2004 ).

In many countries, especially those with the resources to have school laboratories, practical work in science is undertaken at secondary level relatively frequently, although this is less the case with older students (Hamlyn et al., 2020 , 2017 ). Practical work is more frequent in schools within more advantaged regions (Hamlyn et al., 2020 ) and many students report that they would have preferred to do more practical work (Cerini et al., 2003 ; Hamlyn et al., 2020 ).

The impact of practical work remains less clear (Cukurova et al., 2015 ; Gatsby Charitable Foundation, 2017 ). Society broadly expects that students in any one country will experience practical work to similar extents, so it is unfeasible, for more than a handful of lessons (e.g. Shana & Abulibdeh, 2020 ), to apply experimental designs where some students undertake practical work while others do not. One study, where students were assigned to one of four different groups, concluded that while conventional practical work led to more student learning than did either watching videos or reading textbooks, it was no more effective than when students watched a teacher demonstration (Moore et al., 2020 ).

The study by Moore et al. ( 2020 ) illustrates an important point, namely, that students can acquire conceptual knowledge and theoretical understanding by ways other than engagement in practical work. Indeed, there are some countries where less practical work is undertaken than in others, yet students score well, on average, on international measures of attainment. Some, but relatively few, studies have focused on whether the extent of practical work, and/or whether practical work undertaken in particular ways, associates with any educational or other outcomes. There are some indications that more frequent practical work associates with benefits (Cukurova et al., 2015 ). For example, students in higher-performing secondary schools have reported that they undertake more frequent practical work than pupils in lower-performing schools, although this does not reflect the impact of practical work alone (Hamlyn et al., 2017 ). In a more recent study, Oliver et al. ( 2021a , b ), in their analysis of the science scores in the six Anglophone countries (Australia, Canada, Ireland, New Zealand, the UK, and the USA) that participated in PISA (Program for International Student Assessment) 2015, found that “Of particular note is that the highest level of student achievement is associated with doing practical work in some lessons (rather than all or most) and this patterning is consistent across all six countries” (p. 35).

Students often appreciate and enjoy practical work in science (Hamlyn et al., 2020 ; National Foundation for Educational Research, 2011 ). Nevertheless, students do not necessarily understand the purposes of practical work, some feel that practical work may not necessarily be the best way to understand some aspects of science, and some highlight that practical work does not necessarily give them what they need for examinations (Abrahams & Reiss, 2012 ; Sharpe & Abrahams, 2020 ). Teachers have also spoken about the challenges of devising and delivering practical work, and often value practical work for being motivational for students rather than for helping them to understand science concepts (Gatsby Charitable Foundation, 2017 ; National Foundation for Educational Research, 2011 ).

Teaching Approaches

Educational research has examined how teaching and learning could best be undertaken. Many teaching and learning approaches have been found to associate with students’ learning outcomes, such as their achievement (Bennett et al., 2007 ; Furtak et al., 2012 ; Hattie et al., 2020 ; Savelsbergh et al., 2016 ; Schroeder et al., 2007 ) and interest (e.g. Chachashvili-Bolotin et al., 2016 ; Swarat et al., 2012 ), both in science and more generally. However, considering different teaching and learning approaches is complicated by terminology (where the definitions of terms can vary and/or terms can be applied in various ways) and wider aspects of generalisation (where it can be difficult to determine trends across studies undertaken in diverse ways across diverse contexts).

Inquiry-based approaches to teaching and learning generally involve students having more initiative to direct and undertake activities to develop their understanding (although not necessarily without guidance and support from teachers), such as working scientifically to devise and undertake investigations. However, it is important to emphasise that inquiry-based approaches do not necessitate practical work. Indeed, there are many subjects where no practical work takes place and yet students can undertake inquiries. In science, examples of non-practical-based inquiries that could fruitfully be undertaken collaboratively or individually and using the internet and/or libraries include the sort of research that students might undertake to investigate a socio-scientific issue. An example of such research includes what the effects of reintroducing an extinct or endangered species might be on an ecosystem, such as the reintroduction of the Eurasian beaver ( Castor fiber ) into the UK, or the barn owl ( Tyto alba ) into Canada. Inquiry-based learning in school science has often been found to associate with greater achievement (Furtak et al., 2012 ; Savelsbergh et al., 2016 ; Schroeder et al., 2007 ), though too much time spent on inquiry can result in reduced achievement (Oliver et al., 2021a ).

Allied to inquiry-based approaches is project-based learning. Here, students take initiative, manifest autonomy, and exercise responsibility for addressing an issue (often attempting to solve a problem) that usually results in an end product (such as a report or model), with teachers as facilitators and guides. The project occurs over a relatively long duration of time (Helle et al., 2006 ), to allow time for planning, revising, undertaking, and writing up the study. Project-based learning tends to associate positively with achievement (Chen & Yang, 2019 ).

Context-based approaches to teaching and learning use specific contexts and applications as starting points for the development of scientific ideas, rather than more traditional approaches that typically cover scientific ideas before moving on to consider their applications and contexts (Bennett et al., 2007 ). Context-based approaches have been found to be broadly equivalent to other teaching and learning approaches in developing students’ understanding, with some evidence for helping foster positive attitudes to science to a greater extent than traditional approaches (Bennett et al., 2007 ). Specifically relating learning to students’ experiences or context (referred to as ‘enhanced context strategies’) often associates positively with achievement (Schroeder et al., 2007 ). The literature on context-based approaches overlaps with that on the use of socio-scientific issues in science education, where students develop their scientific knowledge and understanding by considering complicated issues where science plays a role but on its own is not sufficient to produce solutions (e.g. Dawson, 2015 ; Zeidler & Sadler, 2008 ). To date, the literature on context-based approaches and/or socio-scientific issues has remained distinct from that on investigative research projects but, as we will argue below, there might be benefit in considering their intersection.

Various other teaching and learning approaches have been found to be beneficial in science, including collaborative work, computer-based work, and the provision of extra-curricular activities (Savelsbergh et al., 2016 ). Similarly, but specifically focusing on chemistry, various teaching and learning practices have been found to associate positively with academic outcomes, including (most strongly) collaborative learning and problem-based learning (Rahman & Lewis, 2019 ).

Most attention has focused on achievement-related outcomes. Nevertheless, inquiry-based learning, context-based learning, computer-based learning, collaborative learning, and extra-curricular activities have often also been found to associate positively with students’ interests and aspirations towards science (Savelsbergh et al., 2016 ). While many teaching and learning approaches associate with benefits, it remains difficult definitively to establish whether any particular approach is optimal and/or whether particular approaches are better than others. Teaching and learning time are limited, so applying a particular approach may mean not applying another approach.

Investigative Research Projects

Science education has often (implicitly or explicitly) been orientated around students learning science by doing science, intending to help students understand the nature, processes, and methods of science. An early critique of pedagogical approaches that saw students as scientists was provided by Driver ( 1983 ) who, while not dismissing the value of the approach, cautioned against over-enthusiastic adoption on the grounds that, unsurprisingly, school students, compared to actual scientists, manifest a range of misconceptions about how scientific research is undertaken. Contemporary recommendations for practical work include schools delivering frequent and varied practical activities (in at least half of all science lessons), and students also having the opportunity to undertake open-ended and extended investigative projects (Gatsby Charitable Foundation, 2017 ).

Investigative research projects may be intended to reflect some aspects of science more accurately or authentically than other teaching and learning approaches, such as confirmatory practical activities and teacher demonstrations. Nevertheless, authenticity in science and science education can be approached and/or defined in various ways (Braund & Reiss, 2006 ), and the issue raises wider questions such as whether only (adult) scientists can authentically experience science, and who determines what science is and what authentic experiences of science are (Kapon et al., 2018 ; Martin et al., 1990 ).

Although too tight a definition can be unhelpful, investigative research projects in science typically involve students determining a research question (where the outcome is unknown) and approaches to answer it, undertaking the investigation, analysing the data, and reporting the findings. The project may be undertaken alone or in groups, with support from teachers and/or others such as scientists and researchers (Bennett et al., 2018 ; Gatsby Charitable Foundation, 2017 ). Students may have varying degrees of autonomy—but then that is true of scientists too.

Independent research projects in science for students have often been framed around providing students with authentic experiences of scientific research and with the potential for wider benefits around scientific knowledge and skills, attitudes, and motivations around science, and ultimately helping science to become more inclusive and accessible to everyone (Bennett et al., 2018 ; Milner-Bolotin, 2012 ). Considered in review across numerous studies, independent research projects for secondary school students (aged 11–19) have often (but not necessarily always) resulted in benefits, including the following:

Acquisition of science-related knowledge (Burgin et al., 2012 ; Charney et al., 2007 ; Dijkstra & Goedhart, 2011 ; Houseal et al., 2014 ; Sousa-Silva et al., 2018 ; Ward et al., 2016 );

Enhancement of knowledge and/or skills around aspects of research and working scientifically (Bulte et al., 2006 ; Charney et al., 2007 ; Ebenezer et al., 2011 ; Etkina et al., 2003 ; Hsu & Espinoza, 2018 ; Ward et al., 2016 );

Greater confidence in undertaking various aspects of science, including applying knowledge and skills (Abraham, 2002 ; Carsten Conner et al., 2021 ; Hsu & Espinoza, 2018 ; Stake & Mares, 2001 , 2005 );

Aspirations towards science-related studies and/or careers (Abraham, 2002 ; Stake & Mares, 2001 ), although students in other studies have reported unchanged and already high aspirations towards science-related studies and/or careers (Burgin et al., 2015 , 2012 );

Subsequently entering science-related careers (Roberts & Wassersug, 2009 );

Development of science and/or research identities and/or identification as a scientist or researcher (Carsten Conner et al., 2021 ; Deemer et al., 2021 );

Feelings and experiences of real science and doing science (Barab & Hay, 2001 ; Burgin et al., 2015 ; Chapman & Feldman, 2017 );

Wider awareness and/or understanding of science, scientists, and/or positive attitudes towards science (Abraham, 2002 ; Houseal et al., 2014 ; Stake & Mares, 2005 );

Benefits akin to induction into scientific or research communities of practice (Carsten Conner et al., 2018 );

Development of wider personal, studying, and/or social skills, including working with others and independent work (Abraham, 2002 ; Moote, 2019 ; Moote et al., 2013 ; Sousa-Silva et al., 2018 ).

Positive experiences of projects and programmes are often conveyed by students (Dijkstra & Goedhart, 2011 ; Rushton et al., 2019 ; Williams et al., 2018 ). For example, students have reported appreciating the greater freedom and independence to discover things, and that they felt they were undertaking real experiments with a purpose, and a greater sense of meaning (Bulte et al., 2006 ).

Nevertheless, it remains difficult to determine the extent of generalisation from diverse research studies undertaken in various ways and across various contexts: benefits have been observed across studies involving different foci (determining what was measured and/or reported), projects for students, and contexts and countries. Essentially, each individual research study did not cover and/or evidence the whole range of benefits. Many benefits have been self-reported, and only some studies have considered changes over time (Moote, 2019 ; Moote et al., 2013 ).

Investigative science research projects for students are delivered in various ways. For example, some projects are undertaken through formal programmes that provide introductions and induction, learning modules, equipment, and the opportunity to present findings (Ward et al., 2016 ). Some programmes put a particular emphasis on the presentation and dissemination of findings (Bell et al., 2003 ; Ebenezer et al., 2011 ; Stake & Mares, 2005 ). Some projects are undertaken through schools (Ebenezer et al., 2011 ; Ward et al., 2016 ); others entail students working at universities, sometimes undertaking and/or assisting with existing projects (Bell et al., 2003 ; Burgin et al., 2015 , 2012 ; Charney et al., 2007 ; Stake & Mares, 2001 , 2005 ) or in competitions (e.g. Liao et al., 2017 ). While many projects are undertaken in laboratory settings, some are undertaken outdoors, in the field (Carsten Conner et al., 2018 ; Houseal et al., 2014 ; Young et al., 2020 ).

Primary School

While much of the school literature on investigative research projects in science concentrates on secondary or university students, some such projects are undertaken with students in primary school. These projects are often perceived as enjoyable and considered to benefit scientific skills and knowledge and/or confidence in doing science (Forbes & Skamp, 2019 ; Liljeström et al., 2013 ; Maiorca et al., 2021 ; Tyler-Wood et al., 2012 ). Such projects often help students feel that they are scientists and doing science (Forbes & Skamp, 2019 ; Reveles et al., 2004 ).

For example, one programme for primary school students in Australia intended students to develop and apply skills in thinking and working scientifically with support by scientist mentors over 10 weeks. It involved the students identifying areas of interest and testable questions within a wider scientific theme, collaboratively investigating their area of interest through collecting and analysing data, and then presenting their findings. Data on the programme’s outcomes were obtained through interviews with students and by studying the reports that they wrote (Forbes & Skamp, 2016 , 2019 ). Participating students said that they appreciated the autonomy and practical aspects, and enjoyed the experiences. The students showed developments in thinking scientifically and around the nature of science, where science often became seen as something that could be interesting, enjoyable, student-led, collaborative, creative, challenging, and a way to understand how things work within the world (Forbes & Skamp, 2019 ). The experiences of thinking and working scientifically, and aspects such as collaborative working and learning from each other, were broadly considered to help develop students’ scientific identities and include them within a scientific community of practice. Some students felt that they were doing authentic (‘real’) science, in contrast to some of their earlier or other experiences of science at school, which had not involved an emphasis on working scientifically and/or specific activities within working scientifically, such as collecting and analysing data (Forbes & Skamp, 2019 ).

CREST Awards

CREST Awards are intended to give young people (aged 5–19) in the UK the opportunity to explore real STEM (science, technology, engineering, and mathematics) projects, providing the experience of ‘being a scientist’ (British Science Association, 2018 ). The scheme has been running since the 1980s and some 30,000 Awards are given each year. They exist at three levels (Bronze, Silver, and Gold), reflecting the necessary time commitment and level of independence and originality expected. The Awards are presented as offering the potential for participants to experience the process of engaging in a project, and developing investigation, problem-solving, and communication skills. They are also presented as something that can contribute to further awards (such as Duke of Edinburgh Awards) and/or competition entries (such as The Big Bang Competition). CREST Gold Awards can be used to enhance applications to university and employment. At Gold level, arranging for a STEM professional in a field related to the student’s work to act as a mentor is recommended, though not formally required. CREST Awards are assessed by teachers and/or assessors from industry or academia, depending on the Award level.

Classes of secondary school students in Scotland undertaking CREST Awards projects appeared to show some benefits around motivational and studying strategies, but less clearly than would be ideal (Moote, 2019 ; Moote et al, 2013 ). Students undertaking CREST Silver Awards between 2010 and 2013 gained better qualifications at age 16 and were more likely to study science subjects for 16–19-year-olds than other comparable students (matched on prior attainment and certain personal characteristics), although the students may have differed on unmeasured aspects, such as attitudes and motivations towards science and studying (Stock Jones et al., 2016 ). A subsequent randomised controlled trial found that year 9 students (aged 13–14) undertaking CREST Silver Awards and other comparable students ultimately showed similar science test scores, attitudes towards school work, confidence in undertaking various aspects of life (not covering school work), attitudes towards science careers (inaccurately referred to as self-efficacy), and aspirations towards science careers (Husain et al., 2019 ). Nevertheless, teachers and students perceived benefits, including students acquiring transferable skills such as time management, problem-solving, and team working, and that science topics were made more interesting and relevant for students (Husain et al., 2019 ). Overall, it remains difficult to form any definitive conclusions about impacts, given the diverse scope of CREST Awards but limited research. For example, whether and/or how CREST Awards projects are independent of or integrated with curricula areas may determine the extent of (curricula-based) knowledge gains.

Nuffield Research Placements

Nuffield Research Placements involve students in the UK undertaking STEM research placements during the summer between years 12 and 13, and presenting their findings at a celebration event (Nuffield Foundation, 2020 ). The scheme has been running since 1996 and a little over 1000 students participate each year. The programme is variously framed as an opportunity for students to undertake real research and develop scientific and other skills, and an initiative to enhance access/inclusion and assist the progression of students into STEM studies at university (Cilauro & Paull, 2019 ; Nuffield Foundation, 2020 ).

The application process is competitive, and requires a personal statement where students explain their interest in completing the placement. Students need to be studying at least one STEM subject in year 12, be in full-time education at a state school (i.e. not a private school that requires fees), and have reached a certain academic level at year 11. The scheme historically aimed to support and prioritise students from disadvantaged backgrounds, and is now only available for students from disadvantaged backgrounds based on family income, living or having lived in care, and/or being the first person in their immediate family who will study in higher education (Nuffield Foundation, 2020 ).

There have been indications that students who undertake Nuffield Research Placements are, on average, more likely to enrol on STEM subjects at top (Russell Group) UK universities and complete a higher number of STEM qualifications for 16–19-year-olds than other students (Cilauro & Paull, 2019 ). Nevertheless, it remains difficult to isolate independent impacts of the placements, given that (for example) students commence their 16–19 education prior to the placements.

Following their Nuffield Research Placements, students have reported increased understanding of what STEM researchers do in their daily work and unchanging (already high) enjoyment of STEM and interest in STEM job opportunities (Bowes et al., 2017 ; Cilauro & Paull, 2019 ). Wider benefits have been attributed to the placement, including skills in writing reports, working independently, confidence in their own abilities in general, and team working (Bowes et al., 2017 ). Students also often report that they feel they have contributed to an authentic research study in an area of STEM in which they are interested (Bowes et al., 2021 ).

Institute for Research in Schools Projects

The Institute for Research in Schools (IRIS) started in 2016 and has about 1000 or more participating students in the UK annually. It facilitates students to undertake a range of investigative research projects from a varied portfolio of options. For example, these projects have included CERN@School (Whyntie, 2016 ; Whyntie et al., 2015 , 2016 ), where students have been found to have positive experiences, developing research and data analysis skills, and developing wider skills such as collaboration and communication (Hatfield et al., 2019 ; Parker et al., 2019 ). Teachers who have facilitated projects for their students (Rushton & Reiss, 2019 ) report that the experiences produced personal and wider benefits around:

Appreciating the freedom to teach and engage in the research projects;

Connecting or reconnecting with science and research, including interest and enthusiasm (in science as well as teaching it) and with a role as a scientist, including being able to share past experiences or work as a scientist with students;

Collaborating with students and scientists, researchers, and others in different and/or new ways via doing research (including facilitating students and providing support);

Professional and skills development (refreshing/revitalising teaching and interest), including recognition by colleagues/others (strengthening recognition as a teacher/scientist, as having skills, as someone who provides opportunities/support for students).

The teachers felt that their students developed a range of specific and transferable benefits, including around research, communication, teamwork, planning, leadership, interest and enthusiasm, confidence, and awareness of the realities of science and science careers. Some benefits could follow and/or be enhanced by the topics that the students were studying, such as interest and enthusiasm linking with personal and wider/real-life relevance, for example, for topics like biodiversity (Rushton & Reiss, 2019 ).

Students in England who completed IRIS projects and presented their findings at conferences reported that the experiences were beneficial through developing skills (including communication, confidence, and managing anxiety); gaining awareness, knowledge, and understanding of the processes of research and careers in research; collaboration and sharing with students and teachers; developing networks and contacts; and doing something that may benefit their university applications (Rushton et al., 2019 ). Presenting and disseminating findings at conferences were considered to be inspirational and validating (including experiencing the impressive scientific and historical context of the conference venue), although also challenging, given limited time, competing demands, anxiety and nervousness, and uncertainty about how to engage with others and undertake networking (Rushton et al., 2019 ).

Although our principal interest is in investigative research projects in science at school, it is worth briefly surveying the literature on such projects at university level. This is because while such projects are rare at school level, normally resulting from special initiatives, there is a long tradition in a number of countries of investigative research projects in science being undertaken at university level, alongside other types of practical work.

Unsurprisingly, university science students typically report having little to no prior experience with authentic research, although they may have had laboratory or fieldwork experience on their pre-university courses (Cartrette & Melroe-Lehrman, 2012 ; John & Creighton, 2011 ). University students still perceive non-investigative-based laboratory work as meaningful experiences of scientific laboratory work, even if these might be less authentic experiences of (some aspects of) scientific research (Goodwin et al., 2021 ; Rowland et al., 2016 ).

Research experiences for university science students are often framed around providing students with authentic experiences of scientific research, with more explicit foci towards developing research skills and practices, developing conceptual understanding, conveying the nature of science, and fostering science identities (Linn et al., 2015 ). Considered in review across numerous studies, research experiences for university science students have often (but not necessarily always) resulted in benefits, including to research skills and practices and confidence in applying them, enhanced understanding of the reality of scientific research and careers, and higher likelihood of persisting or progressing within science education and/or careers (Linn et al., 2015 ).

For example, in one study, university students of science in England reported having no experience of ‘real’ research before undertaking a summer research placement programme (John & Creighton, 2011 ). After the programme, the majority of students agreed that they had discovered that they liked research and that they had gained an understanding of the everyday realities of research. Most of the students reported that their placement confirmed or increased their intentions towards postgraduate study and research careers (John & Creighton, 2011 ).

Implications and Future Directions

Investigative research projects in science have the potential for various benefits, given the findings from wider research into inquiry-based learning (Furtak et al., 2012 ; Savelsbergh et al., 2016 ; Schroeder et al., 2007 ), context-based learning (Bennett et al., 2007 ; Schroeder et al., 2007 ), and project-based learning (Chen & Yang, 2019 ). However, the potential for benefits involves broad generalisations, where inquiry-based learning (for example) covers a diverse range of approaches that may or may not be similar to those encountered within investigative research projects. Furthermore, we do not see investigative research projects as a universal panacea. It is, for example, unrealistic to expect that students can simultaneously learn scientific knowledge, learn about scientific practice, and engage skillfully and appropriately in aspects of scientific practice. Indeed, careful scaffolding from teachers is likely to be required for any, let alone all, of these benefits to result.

We are conscious that enabling students to undertake investigative research projects in science places particular burdens on teachers. Anecdotal evidence suggests that if teachers themselves have had a university education in which they undertook one or more such projects themselves (e.g. because they undertook a research masters or doctorate in science), they are more likely both to be enthused about the benefits of this way of working and to be able to help their students undertake research. It would be good to have this hypothesis investigated rigorously and, more importantly, to have data on effective professional development for teachers to help their students undertake investigative research projects in science. It is known that school teachers of science can benefit from undertaking small-scale research projects as professional development (e.g. Bevins et al., 2011 ; Koomen et al., 2014 ), but such studies do not seem rigorously to have followed individual teachers through into their subsequent day-to-day work with their students to determine the long-term consequences for the students.

Benefits accruing from investigative research projects are likely to be enhanced if there is an alignment between the form of the assessment and the intended outcomes of the investigative research project (cf. Molefe, 2011 ). The first author recalls how advanced level biology projects (for 16–18-year-olds) were assessed in England by one of the Examination Boards back in the 1980s. At the end of the course, each student who had submitted such a project had a 15-min viva with an external examiner. The mark scheme rewarded not only the sorts of things that any advanced level biology mark scheme would credit (use of literature, appropriate research design, care in data collection, thorough analysis, etc.) but originality too. There was therefore an emphasis on novel research. Indeed, occasionally students published sole- or co-authored accounts of their work in biology or biology education journals.

We mentioned above Driver’s ( 1983 ) caution about the extent to which it is realistic to envisage high school students undertaking investigative research projects that have more than superficial resemblance to those undertaken by actual scientists. Nevertheless, as the above review indicates, there is a strong strand within school science education of advocating the benefits of students designing and undertaking open-ended research projects (cf. Albone et al., 1995 ). Roth ( 1995 ) argued that for school science to be authentic, students need to:

(1) learn in contexts constituted in part by ill-defined problems; (2) experience uncertainties and ambiguities and the social nature of scientific work and knowledge; (3) learning is predicated on, and driven by, their current knowledge state; (4) experience themselves as parts of communities of inquiry in which knowledge, practices, resources and discourse are shared; (5) in these communities, members can draw on the expertise of more knowledgeable others whether they are peers, advisors or teachers. (p. 1)

Investigative research projects in science allow learners to learn about science by doing science, and therefore might help foster science identities. Science identities can involve someone recognising themselves and also being recognised by others as being a science person, and also with having various experiences, knowledge, and skills that are valued and recognised within the wider fields of science.

However, the evidence base, as indicated above and in the systematic review of practical independent research projects in high school science undertaken by Bennett et al. ( 2018 ), is still not robust. We need research studies that make explicit the putative benefits of investigative research projects in science, that have adequate control groups, and that look at the long-term consequences of such projects not only by collecting delayed data from participants (whether by surveys or interviews) but by following them longitudinally to see whether such projects make any difference to their subsequent education and career destinations. We also know very little about the significance of students’ home circumstances for their enthusiasm and capacity to undertake investigative research projects in science, though it seems likely that students with high science capital (DeWitt et al., 2016 ) are more likely to receive familial support in undertaking such projects (cf. Lissitsa & Chachashvili‐Bolotin, 2019 ).

We also need studies that consider more carefully what it is to engage in scientific practices. It is notable that the existing literature on investigative research projects for students in science makes no use of the literature on ethnographic studies of scientists at work—neither the foundational texts (e.g. Latour & Woolgar, 1979 ; Knorr-Cetina, 1983 ) nor more recent studies (e.g. Silvast et al., 2020 ). Too often there is a tendency for investigative research projects for students in science to ignore the reasons why scientists work in particular areas and to assume that once a written report of the research has been authored, the work is done. There can also be a somewhat simplistic belief that the sine qua non of an investigative research project is experimental science. Keen as we are on experimental science, there is more to being a scientist than undertaking experiments. For example, computer simulations (Winsberg, 2019 ) and other approaches that take advantage of advances in digital technologies are of increasing importance to the work of many scientists. It would be good to see such approaches reflected in more school student investigative projects (cf. Staacks et al., 2018 ).

More generally, greater authenticity would be likely to result if the following three issues were explicitly considered with students:

How should the particular focus of the research be identified? Students should be helped to realise that virtually all scientific research requires substantial funding. It may not be enough, therefore, for students to identify the focus for their work on the grounds of personal interest alone if they wish to understand how science is undertaken in reality. Here, such activities as participating in well-designed citizen science projects that still enable student autonomy (e.g. Curtis, 2018 ) can help.

Students should be encouraged, once their written report has been completed, to present it at a conference (as happens, for instance, with many IRIS projects) and to write it up for publication. Writing for publication is more feasible now that publication can be via blogs or on the internet, compared to the days when the only possible outlets were hard-copy journals or monographs.

What change in the world does the research wish to effect? Much student research in science seems implicitly to presume that science is neutral. The reality—back to funding again—is that most scientific research is undertaken with specific ends in mind (for instance, the development of medical treatments, the location of valuable mineral ores, the manufacture of new products for which desire can also be manufactured). It is not, of course, that we are calling for students unquestioningly to adopt the same values as those of professional scientists. Rather, we would encourage students to be enabled to reflect on such ends and values.

Abraham, L. (2002). What do high school science students gain from field-based research apprenticeship programs? The Clearing House, 75 (5), 229–232.

Article Google Scholar

Abrahams, I., & Reiss, M. (2012). Practical work: its effectiveness in primary and secondary schools in England. Journal of Research in Science Teaching, 49 (8), 1035–1055.

Abrahams, I., & Reiss, M. J. (Eds) (2017). Enhancing learning with effective practical science 11-16 . London: Bloomsbury.

Google Scholar

Albone, E., Collins, N., & Hill, T. (Eds) (1995). Scientific research in schools: a compendium of practical experience. Bristol: Clifton Scientific Trust.

Archer, L., Dawson, E., DeWitt, J., Seakins, A., & Wong, B. (2015). “Science capital”: a conceptual, methodological, and empirical argument for extending Bourdieusian notions of capital beyond the arts. Journal of Research in Science Teaching, 52 (7), 922–948.

Archer, L., & DeWitt, J. (2017). Understanding young people’s science aspirations: How students form ideas about ‘becoming a scientist’. Abingdon: Routledge.

Barab, S., & Hay, K. (2001). Doing science at the elbows of experts: issues related to the science apprenticeship camp. Journal of Research in Science Teaching, 38 (1), 70–102.

Bell, R., Blair, L., Crawford, B., & Lederman, N. (2003). Just do it? Impact of a science apprenticeship program on high school students’ understandings of the nature of science and scientific inquiry. Journal of Research in Science Teaching, 40 (5), 487–509.

Bennett, J., Dunlop, L., Knox, K., Reiss, M. J., & Torrance Jenkins, R. (2018). Practical independent research projects in science: a synthesis and evaluation of the evidence of impact on high school students. International Journal of Science Education, 40 (14), 1755–1773.

Bennett, J., Lubben, F., & Hogarth, S. (2007). Bringing science to life: a synthesis of the research evidence on the effects of context-based and STS approaches to science teaching. Science Education, 91 (3), 347–370.

Bevins, S., Jordan, J., & Perry, E. (2011). Reflecting on professional development. Educational Action Research, 19 (3), 399–411.

Bowes, L., Birkin, G., & Tazzyman, S. (2017). Nuffield research placements evaluation: final report on waves 1 to 3 of the longitudinal survey of 2016 applicants. Leicester: CFE Research.

Bowes, L., Tazzyman, S., Stutz, A., & Birkin, G. (2021). Evaluation of Nuffield future researchers. London: Nuffield Foundation.

Braund, M., & Reiss, M. (2006). Towards a more authentic science curriculum: the contribution of out-of-school learning. International Journal of Science Education , 28 , 1373–1388.

British Science Association. (2018). CREST Awards: getting started guide, primary. London: British Science Association.

Bulte, A., Westbroek, H., de Jong, O., & Pilot, A. (2006). A research approach to designing chemistry education using authentic practices as contexts. International Journal of Science Education, 28 (9), 1063–1086.

Burgin, S., McConnell, W., & Flowers, A. (2015). ‘I actually contributed to their research’: the influence of an abbreviated summer apprenticeship program in science and engineering for diverse high-school learners. International Journal of Science Education, 37 (3), 411–445.

Burgin, S., Sadler, T., & Koroly, M. J. (2012). High school student participation in scientific research apprenticeships: variation in and relationships among student experiences and outcomes. Research in Science Education, 42 , 439–467.

Carsten Conner, L., Oxtoby, L., & Perin, S. (2021). Power and positionality shape identity work during a science research apprenticeship for girls. International Journal of Science Education , 1–14.

Carsten Conner, L., Perin, S., & Pettit, E. (2018). Tacit knowledge and girls’ notions about a field science community of practice. International Journal of Science Education, Part B, 8 (2), 164–177.

Cartrette, D., & Melroe-Lehrman, B. (2012). Describing changes in undergraduate students’ preconceptions of research activities. Research in Science Education, 42 , 1073–1100.

Cerini, B., Murray, I., & Reiss, M. (2003). Student review of the science curriculum: major findings . London: Planet Science.

Chachashvili-Bolotin, S., Milner-Bolotin, M., & Lissitsa, S. (2016). Examination of factors predicting secondary students’ interest in tertiary STEM education. International Journal of Science Education , 38 (3), 366–390.

Chapman, A., & Feldman, A. (2017). Cultivation of science identity through authentic science in an urban high school classroom. Cultural Studies of Science Education, 12 , 469–491.

Charney, J., Hmelo-Silver, C., Sofer, W., Neigeborn, L., Coletta, S., & Nemeroff, M. (2007). Cognitive apprenticeship in science through immersion in laboratory practices. International Journal of Science Education, 29 (2), 195–213.

Chen, C.-H., & Yang, Y.-C. (2019). Revisiting the effects of project-based learning on students’ academic achievement: a meta-analysis investigating moderators. Educational Research Review, 26 , 71–81.

Cilauro, F., & Paull, G. (2019). Evaluation of Nuffield research placements: interim report. London: Nuffield Foundation.

Claussen, S., & Osborne, J. (2013). Bourdieu’s notion of cultural capital and its implications for the science curriculum. Science Education, 97 (1), 58–79.

Coll, R. K., & Taylor, N. (2012). An international perspective on science curriculum development and implementation. In B. J. Fraser, K. Tobin, & C. J. McRobbie (Eds), Second international handbook of science education (pp. 771–782). Springer, Dordrecht.

Chapter Google Scholar

Cukurova, M., Hanley, P., & Lewis, A. (2015). Rapid evidence review of good practical science. London: Gatsby Charitable Foundation.

Curtis, V. (2018). Online citizen science and the widening of academia: distributed engagement with research and knowledge production . Cham: Palgrave.

Dawson, V. (2015). Western Australian high school students’ understandings about the socioscientific issue of climate change. International Journal of Science Education , 37 (7), 1024–1043.

Deemer, E., Ogas, J., Barr, A., Bowdon, R., Hall, M., Paula, S., … Lim, S. (2021). Scientific research identity development need not wait until college: examining the motivational impact of a pre-college authentic research experience. Research in Science Education , 1–16. https://doi.org/10.1007/s11165-021-09994-6

Department for Education. (2014). The national curriculum in England: framework document. London: Department for Education. https://www.gov.uk/government/publications/national-curriculum-in-england-framework-for-key-stages-1-to-4 . Accessed 1 July 1 2017.

DeWitt, J., Archer, L., & Mau, A. (2016). Dimensions of science capital: exploring its potential for understanding students’ science participation. International Journal of Science Education, 38 , 2431–2449.

Dijkstra, E., & Goedhart, M. (2011). Evaluation of authentic science projects on climate change in secondary schools: a focus on gender differences. Research in Science & Technological Education, 29 (2), 131–146.

Driver, R. (1983). The pupil as scientist? Milton Keynes: Open University Press.

Ebenezer, J., Kaya, O. N., & Ebenezer, D. L. (2011). Engaging students in environmental research projects: perceptions of fluency with innovative technologies and levels of scientific inquiry abilities. Journal of Research in Science Teaching, 48 (1), 94–116.

Etkina, E., Matilsky, T., & Lawrence, M. (2003). Pushing to the edge: Rutgers Astrophysics Institute motivates talented high school students. Journal of Research in Science Teaching, 40 (10), 958–985.

Forbes, A., & Skamp, K. (2016). Secondary science teachers’ and students’ involvement in a primary school community of science practice: how it changed their practices and interest in science. Research in Science Education, 46 , 91–112.

Forbes, A., & Skamp, K. (2019). ‘You actually feel like you’re actually doing some science’: primary students’ perspectives of their involvement in the MyScience initiative. Research in Science Education, 49 , 465–498.

Furtak, E. M., Seidel, T., Iverson, H., & Briggs, D. (2012). Experimental and quasi-experimental studies of inquiry-based science teaching: a meta-analysis. Review of Educational Research, 82 (3), 300–329.

Gatsby Charitable Foundation. (2017). Good practical science. London: Gatsby Charitable Foundation.

Gokpinar, T., & Reiss, M. (2016). The role of outside-school factors in science education: a two-stage theoretical model linking Bourdieu and Sen, with a case study. International Journal of Science Education , 38 , 1278–1303.

Goodwin, E., Anokhin, V., Gray, M., Zajic, D., Podrabsky, J., & Shortlidge, E. (2021). Is this science? Students’ experiences of failure make a research-based course feel authentic. CBE-Life Sciences Education, 20 (1), 1–15.

Hamlyn, B., Hanson, T., Malam, S., Man, C., Smith, K., & Williams, L. (2020). Young people’s views on science education: science education tracker 2019: wave 2. London: Wellcome Trust.

Hamlyn, R., Matthews, P., & Shanahan, M. (2017). Young people’s views on science education: science education tracker research report February 2017. London: Wellcome Trust.

Hatfield, P., Furnell, W., Shenoy, A., Fox, E., Parker, B., Thomas, L., & Rushton, E. (2019). IRIS opens pupils’ eyes to real space research. Astronomy & Geophysics, 60 (1), 1.22–1.24.

Hattie, J., Bustamante, V., Almarode, J. T., Fisher, D., & Frey, N. (2020). Great teaching by design: from intention to implementation in the visible learning classroom. Thousand Oaks, CA: Corwin.

Helle, L., Tynjälä, P., & Olkinuora, E. (2006). Project-based learning in post-secondary education – theory, practice and rubber sling shots. Higher Education, 51 , 287–314.

Hodson, D. (1993). Re-thinking old ways: towards a more critical approach to practical work in school science. Studies in Science Education, 22 (1), 85–142.

Hofstein, A., & Lunetta, V. (2004). The laboratory in science education: foundations for the twenty-first century. Science Education, 88 (1), 28–54.

Hollins, M. & Reiss, M. J. (2016) A review of the school science curricula in eleven high achieving jurisdictions. The Curriculum Journal , 27 , 80-94.

Houseal, A., Abd-El-Khalick, F., & Destefano, L. (2014). Impact of a student-teacher-scientist partnership on students’ and teachers’ content knowledge, attitudes toward science, and pedagogical practices. Journal of Research in Science Teaching, 51 (1), 84–115.

Hsu, P.-L., & Espinoza, P. (2018). Cultivating constructivist science internships for high school students through a community of practice with cogenerative dialogues. Learning Environments Research, 21 , 267–283.

Husain, F., Wishart, R., Attygalle, K., Averill, P., Ilic, N., & Mayer, M. (2019). CREST Silver evaluation report. London: Education Endowment Foundation.

Institute of Physics. (2020). Limit Less: Support young people to change the world. London: Institute of Physics.

John, J., & Creighton, J. (2011). Researcher development: the impact of undergraduate research opportunity programmes on students in the UK. Studies in Higher Education, 36 (7), 781–797.

Kapon, S., Laherto, A., & Levrini, O. (2018). Disciplinary authenticity and personal relevance in school science. Science Education, 102 (5), 1077–1106.

Knorr-Cetina, K. D. (1983). New developments in science studies: the ethnographic challenge. The Canadian Journal of Sociology 8 (2), 153–177.

Koomen, M. H., Blair, R., Young-Isebrand, E., & Oberhauser, K. S. (2014). Science professional development with teachers: nurturing the scientist within. The Electronic Journal for Research in Science & Mathematics Education , 18 (6).

Latour, B. & Woolgar, S. (1979). Laboratory life: the social construction of scientific facts . Beverly Hills: Sage.

Liao, T., McKenna, J., & Milner-Bolotin, M. (2017). Four decades of High School Physics Olympics Competitions at the University of British Columbia. Physics in Canada , 73 (3), 127–129.

Liljeström, A., Enkenberg, J., & Pöllänen, S. (2013). Making learning whole: an instructional approach for mediating the practices of authentic science inquiries. Cultural Studies of Science Education, 8 , 51–86.

Linn, M., Palmer, E., Baranger, A., Gerard, E., & Stone, E. (2015). Undergraduate research experiences: impacts and opportunities. Science, 347 (6222), 1261757.

Lissitsa, S., & Chachashvili‐Bolotin, S. (2019). Enrolment in mathematics and physics at the advanced level in secondary school among two generations of highly skilled immigrants. International Migration , 57 (5), 216–234.

Maiorca, C., Roberts, T., Jackson, C., Bush, S., Delaney, A., Mohr-Schroeder, M., & Soledad, S. Y. (2021). Informal learning environments and impact on interest in STEM careers. International Journal of Science and Mathematics Education, 19 , 45–64.

Mansfield J., & Reiss M. J. (2020). The place of values in the aims of school science education. In D. Corrigan, C. Buntting, A. Fitzgerald, & A. Jones (Eds), Values in science education (pp. 191–209), Cham: Springer.

Martin, B., Kass, H., & Brouwer, W. (1990). Authentic science: a diversity of meanings. Science Education, 74 (5), 541–554.

Millar, R. (1998). Rhetoric and reality: what practical work in science is really for. In J. Wellington (Ed.), Practical work in school science. Which way now? (pp. 16–31). London: Routledge.

Milner-Bolotin, M. (2012). Increasing interactivity and authenticity of chemistry instruction through data acquisition systems and other technologies. Journal of Chemical Education , 89 (4), 477–481.

Molefe, M. L. (2011). A study of life sciences projects in science talent quest competitions in the Western Cape, South Africa, with special reference to scientific skills and knowledge . Unpublished PhD thesis.

Moore, A. M., Fairhurst, P., Correia, C. F., Harrison, C., & Bennett, J. M. (2020). Science practical work in a COVID-19 world: are teacher demonstrations, videos and textbooks effective replacements for hands-on practical activities? School Science Review , 102 (378), 7–12.

Moote, J. (2019). Investigating the longer-term impact of the CREST inquiry-based learning programme on student self-regulated processes and related motivations: views of students and teachers. Research in Science Education, 49 (1), 265–294.

Moote, J., Williams, J., & Sproule, J. (2013). When students take control: investigating the impact of the CREST inquiry-based learning program on self-regulated processes and related motivations in young science students. Journal of Cognitive Education and Psychology, 12 (2), 178–196.

National Foundation for Educational Research. (2011). Exploring young people’s views on science education. London: Wellcome Trust.

Nuffield Foundation. (2020). Nuffield research placements: guide for student applicants. London: Nuffield Foundation.

Oliver, M. C., Jerrim, J., & Adkins, M. J. (2021a). PISA: Engagement Attainment and interest in Science (PEAS) – Final Report. Available at https://www.nottingham.ac.uk/research/groups/lsri/documents/peas-report.pdf .

Oliver, M., McConney, A., & Woods-McConney, A. (2021b). The efficacy of inquiry-based instruction in science: a comparative analysis of six countries using PISA 2015. Research in Science Education , 51 , 595–616.

Osborne, J., & Dillon, J. (2008). Science education in Europe: critical reflections. London: The Nuffield Foundation.

Parker, B., Thomas, L., Rushton, E., & Hatfield, P. (2019). Transforming education with the Timepix detector – Ten years of CERN@school. Radiation Measurements, 127 (106090), 1–7.

Rahman, M. T., & Lewis, S. (2019). Evaluating the evidence base for evidence‐based instructional practices in chemistry through meta‐analysis. Journal of Research in Science Teaching , 1–29. https://doi.org/10.1002/tea.21610

Reveles, J., Cordova, R., & Kelly, G. (2004). Science literacy and academic identity formulation. Journal of Research in Science Teaching, 41 (10), 1111–1144.

Roberts, L., & Wassersug, R. (2009). Does doing scientific research in high school correlate with students staying in science? A half-century retrospective study. Research in Science Education, 39 , 251–256.

Roth, W.-M. (1995). Authentic school science knowing and learning in open-inquiry science laboratories. The Netherlands: Kluwer.

Rowland, S., Pedwell, R., Lawrie, G., Lovie-Toon, J., & Hung, Y. (2016). Do we need to design course-based undergraduate research experiences for authenticity? CBE-Life Sciences Education, 15 (4), 1–16.

Royal Society. (2014). Vision for science and mathematics education. London: The Royal Society.

Rushton, E., & Reiss, M. J. (2019). From science teacher to ‘teacher scientist’: exploring the experiences of research-active science teachers in the UK. International Journal of Science Education, 41 (11), 1541–1561.

Rushton, E., Charters, L., & Reiss, M. J. (2019). The experiences of active participation in academic conferences for high school science students. Research in Science & Technological Education , 1–19. https://doi.org/10.1080/02635143.2019.1657395

Savelsbergh, E., Prins, G., Rietbergen, C., Fechner, S., Vaessen, B., Draijer, J., & Bakker, A. (2016). Effects of innovative science and mathematics teaching on student attitudes and achievement: a meta-analytic study. Educational Research Review, 19 , 158–172.

Schroeder, C., Scott, T., Tolson, H., Huang, T.-Y., & Lee, Y.-H. (2007). A meta-analysis of national research: effects of teaching strategies on student achievement in science in the United States. Journal of Research in Science Teaching, 44 (10), 1436–1460.

Shana, Z., & Abulibdeh, E. S. (2020). Science practical work and its impact on high students’ academic achievement. Journal of Technology and Science Education , 10 (2), 199–215.

Sharpe, R., & Abrahams, I. (2020). Secondary school students’ attitudes to practical work in biology, chemistry and physics in England. Research in Science & Technological Education, 38 (1), 84–104.

Silvast, A., Laes, E., Abram, S., & Bombaerts, G. (2020). What do energy modellers know? An ethnography of epistemic values and knowledge models. Energy Research & Social Science , 66 , 101495.

Sjöström, J. & Eilks, I. (2018). Reconsidering different visions of scientific literacy and science education based on the concept of Bildung . In Y. J. Dori, Z. R. Mevarech, & D. R. Baker (Eds), Cognition, metacognition, and culture in STEM education (pp. 65–88). Cham: Springer.

Sousa-Silva, C., McKemmish, L., Chubb, K., Gorman, M., Baker, J., Barton, E., … Tennyson, J. (2018). Original Research by Young Twinkle Students (ORBYTS): when can students start performing original research? Physics Education, 53 (1), 1–12.

Staacks, S., Hütz, S., Heinke, H., & Stampfer, C. (2018). Advanced tools for smartphone-based experiments: phyphox. Physics Education , 53 (4), 045009.

Stake, J., & Mares, K. (2001). Science enrichment programs for gifted high school girls and boys: predictors of program impact on science confidence and motivation. Journal of Research in Science Teaching, 38 (10), 1065–1088.

Stake, J., & Mares, K. (2005). Evaluating the impact of science-enrichment programs on adolescents’ science motivation and confidence: the splashdown effect. Journal of Research in Science Teaching, 42 (4), 359–375.

Stock Jones, R., Annable, T., Billingham, Z., & MacDonald, C. (2016). Quantifying CREST: what impact does the Silver CREST Award have on science scores and STEM subject selection? London: British Science Association.

Swarat, S., Ortony, A., & Revelle, W. (2012). Activity matters: understanding student interest in school science. Journal of Research in Science Teaching , 49 (4), 515–537.

Tyler-Wood, T., Ellison, A., Lim, O., & Periathiruvadi, S. (2012). Bringing up girls in science (BUGS): the effectiveness of an afterschool environmental science program for increasing female students’ interest in science careers. Journal of Science Education and Technology, 21 , 46–55.

Ward, T., Delaloye, N., Adams, E. R., Ware, D., Vanek, D., Knuth, R., … Holian, A. (2016). Air toxics under the big sky: examining the effectiveness of authentic scientific research on high school students’ science skills and interest. International Journal of Science Education, 38 (6), 905–921.

Whyntie, T. (2016). CERN@School: forming nationwide collaborations for physics research in schools. Nuclear Physics News, 26 (1), 16–19.

Whyntie, T., Bithray, H., Cook, J., Coupe, A., Eddy, D., Fickling, R., … Shearer, N. (2015). CERN@school: demonstrating physics with the Timepix detector. Contemporary Physics, 56 (4), 451–467.

Whyntie, T., Cook, J., Coupe, A., Fickling, R., Parker, B., & Shearer, N. (2016). CERN@school: bringing CERN into the classroom. Nuclear and Particle Physics Proceedings, 273-275 , 1265–1270.

Williams, D., Brule, H., Kelley, S., & Skinner, E. (2018). Science in the learning gardens (SciLG): a study of students’ motivation, achievement, and science identity in low-income middle schools. International Journal of STEM Education, 5 (8), 1–14.

Winsberg, E. (2019). Computer simulations in science. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy , https://plato.stanford.edu/archives/win2019/entries/simulations-science/ .

Young, J., Carsten Conner, L., & Pettit, E. (2020). ‘You really see it’: environmental identity shifts through interacting with a climate change-impacted glacier landscape. International Journal of Science Education, 42 (18), 3049–3070.

Zeidler, D. L., & Sadler, T. D. (2008). Social and ethical issues in science education: a prelude to action. Science & Education , 17 , 799–803.

Download references

Acknowledgements

We are very grateful to The Institute of Research in Schools for funding.

Author information

Authors and affiliations.

UCL Institute of Education, 20 Bedford Way, London, WC1H 0AL, UK

Michael J. Reiss, Richard Sheldrake & Wilton Lodge

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Michael J. Reiss .

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Reiss, M.J., Sheldrake, R. & Lodge, W. Investigative Research Projects for Students in Science: The State of the Field and a Research Agenda. Can. J. Sci. Math. Techn. Educ. 23 , 80–95 (2023). https://doi.org/10.1007/s42330-023-00263-4

Download citation

Accepted : 01 February 2023

Published : 16 March 2023

Issue Date : March 2023

DOI : https://doi.org/10.1007/s42330-023-00263-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Science investigative research projects
Student autonomy
Student engagement
Authenticity
Find a journal
Publish with us
Track your research

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

View all journals
Explore content
About the journal
Publish with us
Sign up for alerts

Research articles

Development of risk-score model in patients with negative surgical margin after robot-assisted radical prostatectomy

Yuta Yamada
Yoichi Fujii
Haruki Kume

Relationships of SIGLEC family-related lncRNAs with clinical prognosis and tumor immune microenvironment in ovarian cancer

Prevalence of bifidity of the seventh cervical vertebral spinous process in southwestern Nigeria: a computed tomography based study

Babatunde Oluwaseun Ibitoye
Olatunde Wasiu Oladipupo
Olajumoke Fatima Bello

Comparison of results obtained using clot-fibrinolysis waveform analysis and global fibrinolysis capacity assay with rotational thromboelastography

Takumi Tsuchida
Mineji Hayakawa
Osamu Kumano

Utilizing ultra-early continuous physiologic data to develop automated measures of clinical severity in a traumatic brain injury population

Shiming Yang
Neeraj Badjatia

Design, synthesis and bioactivity study on oxygen-heterocyclic-based pyran analogues as effective P -glycoprotein-mediated multidrug resistance in MCF-7/ADR cell

Ashraf H. F. Abd El-Wahab
Rita M. A. Borik
Ahmed M. El-Agrody

Dynamic performance of functionally graded composite structures with viscoelastic polymers

Shaoqing Wang
Weigang Wang

Murmur identification and outcome prediction in phonocardiograms using deep features based on Stockwell transform

Omid Dehghan Manshadi
Sara mihandoost

An efficient and accurate 2D human pose estimation method using VTTransPose network

Intravenous metoclopramide for increasing endoscopic mucosal visualization in patients with acute upper gastrointestinal bleeding: a multicenter, randomized, double-blind, controlled trial

Paveeyada Manupeeraphant
Dhanusorn Wanichagool
Supatsri Sethasine

Bioengineering of vascularized porcine flaps using perfusion-recellularization

Michael S. Xu
Andrew D’Elia
Siba Haykal

Organizational commitments to equality change how people view women’s and men’s professional success

Kristin Kelley
Paula Protsch

Genome-wide identification and evolutionary analysis of the AP2/EREBP , COX and LTP genes in Zea mays L. under drought stress

Amaal Maghraby
Mohamed Alzalaty

Transcranial random noise stimulation (tRNS) improves hot and cold executive functions in children with attention deficit-hyperactivity disorder (ADHD)

Vahid Nejati
Mahshid Dehghan
Michael A. Nitsche

Translation and validation of the German version of the FACE-Q paralysis module in adult patients with unilateral peripheral facial palsy

Wieta Elin Moritz
Gerd Fabian Volk
Orlando Guntinas-Lichius

The bidirectional associations between sarcopenia-related traits and cognitive performance

Chun-feng Lu
Wang-shu Liu

European soybean to benefit people and the environment

Jose L. Rotundo
Rachel Marshall
Mariana C. Rufino

Developments of a centimeter-level precise muometric wireless navigation system (MuWNS-V) and its first demonstration using directional information from tracking detectors

Dezso Varga
Hiroyuki K. M. Tanaka

Lesion volume and spike frequency on EEG impact perfusion values in focal cortical dysplasia: a pediatric arterial spin labeling study

Antonio Giulio Gennari
Giulio Bicciato
Georgia Ramantani

Applying a semi-quantitative risk assessment on petroleum production unit

Fatma M. Eltahan
Monica Toderas

Quick links

Explore articles by subject
Guide to authors
Editorial policies

Research article
Open access
Published: 09 November 2005

A qualitative study of nursing student experiences of clinical practice

Farkhondeh Sharif 1 &
Sara Masoumi 2

BMC Nursing volume 4 , Article number: 6 ( 2005 ) Cite this article

355k Accesses

166 Citations

9 Altmetric

Metrics details

Nursing student's experiences of their clinical practice provide greater insight to develop an effective clinical teaching strategy in nursing education. The main objective of this study was to investigate student nurses' experience about their clinical practice.

Focus groups were used to obtain students' opinion and experiences about their clinical practice. 90 baccalaureate nursing students at Shiraz University of Medical Sciences (Faculty of Nursing and Midwifery) were selected randomly from two hundred students and were arranged in 9 groups of ten students. To analyze the data the method used to code and categories focus group data were adapted from approaches to qualitative data analysis.

Four themes emerged from the focus group data. From the students' point of view," initial clinical anxiety", "theory-practice gap"," clinical supervision", professional role", were considered as important factors in clinical experience.

The result of this study showed that nursing students were not satisfied with the clinical component of their education. They experienced anxiety as a result of feeling incompetent and lack of professional nursing skills and knowledge to take care of various patients in the clinical setting.

Peer Review reports

Clinical experience has been always an integral part of nursing education. It prepares student nurses to be able of "doing" as well as "knowing" the clinical principles in practice. The clinical practice stimulates students to use their critical thinking skills for problem solving [ 1 ]

Awareness of the existence of stress in nursing students by nurse educators and responding to it will help to diminish student nurses experience of stress. [ 2 ]

Clinical experience is one of the most anxiety producing components of the nursing program which has been identified by nursing students. In a descriptive correlational study by Beck and Srivastava 94 second, third and fourth year nursing students reported that clinical experience was the most stressful part of the nursing program[ 3 ]. Lack of clinical experience, unfamiliar areas, difficult patients, fear of making mistakes and being evaluated by faculty members were expressed by the students as anxiety-producing situations in their initial clinical experience. In study done by Hart and Rotem stressful events for nursing students during clinical practice have been studied. They found that the initial clinical experience was the most anxiety producing part of their clinical experience [ 4 ]. The sources of stress during clinical practice have been studied by many researchers [ 5 – 10 ] and [ 11 ].

The researcher came to realize that nursing students have a great deal of anxiety when they begin their clinical practice in the second year. It is hoped that an investigation of the student's view on their clinical experience can help to develop an effective clinical teaching strategy in nursing education.

A focus group design was used to investigate the nursing student's view about the clinical practice. Focus group involves organized discussion with a selected group of individuals to gain information about their views and experiences of a topic and is particularly suited for obtaining several perspectives about the same topic. Focus groups are widely used as a data collection technique. The purpose of using focus group is to obtain information of a qualitative nature from a predetermined and limited number of people [ 12 , 13 ].

Using focus group in qualitative research concentrates on words and observations to express reality and attempts to describe people in natural situations [ 14 ].

The group interview is essentially a qualitative data gathering technique [ 13 ]. It can be used at any point in a research program and one of the common uses of it is to obtain general background information about a topic of interest [ 14 ].

Focus groups interviews are essential in the evaluation process as part of a need assessment, during a program, at the end of the program or months after the completion of a program to gather perceptions on the outcome of that program [ 15 , 16 ]. Kruegger (1988) stated focus group data can be used before, during and after programs in order to provide valuable data for decision making [ 12 ].

The participants from which the sample was drawn consisted of 90 baccalaureate nursing students from two hundred nursing students (30 students from the second year and 30 from the third and 30 from the fourth year) at Shiraz University of Medical Sciences (Faculty of Nursing and Midwifery). The second year nursing students already started their clinical experience. They were arranged in nine groups of ten students. Initially, the topics developed included 9 open-ended questions that were related to their nursing clinical experience. The topics were used to stimulate discussion.

The following topics were used to stimulate discussion regarding clinical experience in the focus groups.

How do you feel about being a student in nursing education?

How do you feel about nursing in general?

Is there any thing about the clinical field that might cause you to feel anxious about it?

Would you like to talk about those clinical experiences which you found most anxiety producing?

Which clinical experiences did you find enjoyable?

What are the best and worst things do you think can happen during the clinical experience?

What do nursing students worry about regarding clinical experiences?

How do you think clinical experiences can be improved?

What is your expectation of clinical experiences?

The first two questions were general questions which were used as ice breakers to stimulate discussion and put participants at ease encouraging them to interact in a normal manner with the facilitator.

Data analysis

The following steps were undertaken in the focus group data analysis.

Immediate debriefing after each focus group with the observer and debriefing notes were made. Debriefing notes included comments about the focus group process and the significance of data

Listening to the tape and transcribing the content of the tape

Checking the content of the tape with the observer noting and considering any non-verbal behavior. The benefit of transcription and checking the contents with the observer was in picking up the following:

Parts of words

Non-verbal communication, gestures and behavior...

The researcher facilitated the groups. The observer was a public health graduate who attended all focus groups and helped the researcher by taking notes and observing students' on non-verbal behavior during the focus group sessions. Observer was not known to students and researcher

The methods used to code and categorise focus group data were adapted from approaches to qualitative content analysis discussed by Graneheim and Lundman [ 17 ] and focus group data analysis by Stewart and Shamdasani [ 14 ] For coding the transcript it was necessary to go through the transcripts line by line and paragraph by paragraph, looking for significant statements and codes according to the topics addressed. The researcher compared the various codes based on differences and similarities and sorted into categories and finally the categories was formulated into a 4 themes.

The researcher was guided to use and three levels of coding [ 17 , 18 ]. Three levels of coding selected as appropriate for coding the data.

Level 1 coding examined the data line by line and making codes which were taken from the language of the subjects who attended the focus groups.

Level 2 coding which is a comparing of coded data with other data and the creation of categories. Categories are simply coded data that seem to cluster together and may result from condensing of level 1 code [ 17 , 19 ].

Level 3 coding which describes the Basic Social Psychological Process which is the title given to the central themes that emerge from the categories.

Table 1 shows the three level codes for one of the theme

The documents were submitted to two assessors for validation. This action provides an opportunity to determine the reliability of the coding [ 14 , 15 ]. Following a review of the codes and categories there was agreement on the classification.

Ethical considerations

The study was conducted after approval has been obtained from Shiraz university vice-chancellor for research and in addition permission to conduct the study was obtained from Dean of the Faculty of Nursing and Midwifery. All participants were informed of the objective and design of the study and a written consent received from the participants for interviews and they were free to leave focus group if they wish.

Most of the students were females (%94) and single (% 86) with age between 18–25.

The qualitative analysis led to the emergence of the four themes from the focus group data. From the students' point of view," initial clinical anxiety", "theory-practice gap", clinical supervision"," professional role", was considered as important factors in clinical experience.

Initial clinical anxiety

This theme emerged from all focus group discussion where students described the difficulties experienced at the beginning of placement. Almost all of the students had identified feeling anxious in their initial clinical placement. Worrying about giving the wrong information to the patient was one of the issues brought up by students.

One of the students said:

On the first day I was so anxious about giving the wrong information to the patient. I remember one of the patients asked me what my diagnosis is. ' I said 'I do not know', she said 'you do not know? How can you look after me if you do not know what my diagnosis is?'

From all the focus group sessions, the students stated that the first month of their training in clinical placement was anxiety producing for them.

One of the students expressed:

The most stressful situation is when we make the next step. I mean ... clinical placement and we don't have enough clinical experience to accomplish the task, and do our nursing duties .

Almost all of the fourth year students in the focus group sessions felt that their stress reduced as their training and experience progressed.

Another cause of student's anxiety in initial clinical experience was the students' concern about the possibility of harming a patient through their lack of knowledge in the second year.

One of the students reported:

In the first day of clinical placement two patients were assigned to me. One of them had IV fluid. When I introduced myself to her, I noticed her IV was running out. I was really scared and I did not know what to do and I called my instructor .

Fear of failure and making mistakes concerning nursing procedures was expressed by another student. She said:

I was so anxious when I had to change the colostomy dressing of my 24 years old patient. It took me 45 minutes to change the dressing. I went ten times to the clinic to bring the stuff. My heart rate was increasing and my hand was shaking. I was very embarrassed in front of my patient and instructor. I will never forget that day .

Sellek researched anxiety-creating incidents for nursing students. He suggested that the ward is the best place to learn but very few of the learner's needs are met in this setting. Incidents such as evaluation by others on initial clinical experience and total patient care, as well as interpersonal relations with staff, quality of care and procedures are anxiety producing [ 11 ].

Theory-practice gap

The category theory-practice gap emerged from all focus discussion where almost every student in the focus group sessions described in some way the lack of integration of theory into clinical practice.

I have learnt so many things in the class, but there is not much more chance to do them in actual settings .

Another student mentioned:

When I just learned theory for example about a disease such as diabetic mellitus and then I go on the ward and see the real patient with diabetic mellitus, I relate it back to what I learned in class and that way it will remain in my mind. It is not happen sometimes .

The literature suggests that there is a gap between theory and practice. It has been identified by Allmark and Tolly [ 20 , 21 ]. The development of practice theory, theory which is developed from practice, for practice, is one way of reducing the theory-practice gap [ 21 ]. Rolfe suggests that by reconsidering the relationship between theory and practise the gap can be closed. He suggests facilitating reflection on the realities of clinical life by nursing theorists will reduce the theory-practice gap. The theory- practice gap is felt most acutely by student nurses. They find themselves torn between the demands of their tutor and practising nurses in real clinical situations. They were faced with different real clinical situations and are unable to generalise from what they learnt in theory [ 22 ].

Clinical supervision

Clinical supervision is recognised as a developmental opportunity to develop clinical leadership. Working with the practitioners through the milieu of clinical supervision is a powerful way of enabling them to realize desirable practice [ 23 ]. Clinical nursing supervision is an ongoing systematic process that encourages and supports improved professional practice. According to Berggren and Severinsson the clinical nurse supervisors' ethical value system is involved in her/his process of decision making. [ 24 , 25 ]

Clinical Supervision by Head Nurse (Nursing Unit Manager) and Staff Nurses was another issue discussed by the students in the focus group sessions. One of the students said:

Sometimes we are taught mostly by the Head Nurse or other Nursing staff. The ward staff are not concerned about what students learn, they are busy with their duties and they are unable to have both an educational and a service role

Another student added:

Some of the nursing staff have good interaction with nursing students and they are interested in helping students in the clinical placement but they are not aware of the skills and strategies which are necessary in clinical education and are not prepared for their role to act as an instructor in the clinical placement

The students mostly mentioned their instructor's role as an evaluative person. The majority of students had the perception that their instructors have a more evaluative role than a teaching role.

The literature suggests that the clinical nurse supervisors should expressed their existence as a role model for the supervisees [ 24 ]

Professional role

One view that was frequently expressed by student nurses in the focus group sessions was that students often thought that their work was 'not really professional nursing' they were confused by what they had learned in the faculty and what in reality was expected of them in practice.

We just do basic nursing care, very basic . ... You know ... giving bed baths, keeping patients clean and making their beds. Anyone can do it. We spend four years studying nursing but we do not feel we are doing a professional job .

The role of the professional nurse and nursing auxiliaries was another issue discussed by one of the students:

The role of auxiliaries such as registered practical nurse and Nurses Aids are the same as the role of the professional nurse. We spend four years and we have learned that nursing is a professional job and it requires training and skills and knowledge, but when we see that Nurses Aids are doing the same things, it can not be considered a professional job .

The result of student's views toward clinical experience showed that they were not satisfied with the clinical component of their education. Four themes of concern for students were 'initial clinical anxiety', 'theory-practice gap', 'clinical supervision', and 'professional role'.

The nursing students clearly identified that the initial clinical experience is very stressful for them. Students in the second year experienced more anxiety compared with third and fourth year students. This was similar to the finding of Bell and Ruth who found that nursing students have a higher level of anxiety in second year [ 26 , 27 ]. Neary identified three main categories of concern for students which are the fear of doing harm to patients, the sense of not belonging to the nursing team and of not being fully competent on registration [ 28 ] which are similar to what our students mentioned in the focus group discussions. Jinks and Patmon also found that students felt they had an insufficiency in clinical skills upon completion of pre-registration program [ 29 ].

Initial clinical experience was the most anxiety producing part of student clinical experience. In this study fear of making mistake (fear of failure) and being evaluated by faculty members were expressed by the students as anxiety-producing situations in their initial clinical experience. This finding is supported by Hart and Rotem [ 4 ] and Stephens [ 30 ]. Developing confidence is an important component of clinical nursing practice [ 31 ]. Development of confidence should be facilitated by the process of nursing education; as a result students become competent and confident. Differences between actual and expected behaviour in the clinical placement creates conflicts in nursing students. Nursing students receive instructions which are different to what they have been taught in the classroom. Students feel anxious and this anxiety has effect on their performance [ 32 ]. The existence of theory-practice gap in nursing has been an issue of concern for many years as it has been shown to delay student learning. All the students in this study clearly demonstrated that there is a gap between theory and practice. This finding is supported by other studies such as Ferguson and Jinks [ 33 ] and Hewison and Wildman [ 34 ] and Bjork [ 35 ]. Discrepancy between theory and practice has long been a source of concern to teachers, practitioners and learners. It deeply rooted in the history of nurse education. Theory-practice gap has been recognised for over 50 years in nursing. This issue is said to have caused the movement of nurse education into higher education sector [ 34 ].

Clinical supervision was one of the main themes in this study. According to participant, instructor role in assisting student nurses to reach professional excellence is very important. In this study, the majority of students had the perception that their instructors have a more evaluative role than a teaching role. About half of the students mentioned that some of the head Nurse (Nursing Unit Manager) and Staff Nurses are very good in supervising us in the clinical area. The clinical instructor or mentors can play an important role in student nurses' self-confidence, promote role socialization, and encourage independence which leads to clinical competency [ 36 ]. A supportive and socialising role was identified by the students as the mentor's function. This finding is similar to the finding of Earnshaw [ 37 ]. According to Begat and Severinsson supporting nurses by clinical nurse specialist reported that they may have a positive effect on their perceptions of well-being and less anxiety and physical symptoms [ 25 ].

The students identified factors that influence their professional socialisation. Professional role and hierarchy of occupation were factors which were frequently expressed by the students. Self-evaluation of professional knowledge, values and skills contribute to the professional's self-concept [ 38 ]. The professional role encompasses skills, knowledge and behaviour learned through professional socialisation [ 39 ]. The acquisition of career attitudes, values and motives which are held by society are important stages in the socialisation process [ 40 ]. According to Corwin autonomy, independence, decision-making and innovation are achieved through professional self-concept 41 . Lengacher (1994) discussed the importance of faculty staff in the socialisation process of students and in preparing them for reality in practice. Maintenance and/or nurturance of the student's self-esteem play an important role for facilitation of socialisation process 42 .

One view that was expressed by second and third year student nurses in the focus group sessions was that students often thought that their work was 'not really professional nursing' they were confused by what they had learned in the faculty and what in reality was expected of them in practice.

The finding of this study and the literature support the need to rethink about the clinical skills training in nursing education. It is clear that all themes mentioned by the students play an important role in student learning and nursing education in general. There were some similarities between the results of this study with other reported studies and confirmed that some of the factors are universal in nursing education. Nursing students expressed their views and mentioned their worry about the initial clinical anxiety, theory-practice gap, professional role and clinical supervision. They mentioned that integration of both theory and practice with good clinical supervision enabling them to feel that they are enough competent to take care of the patients. The result of this study would help us as educators to design strategies for more effective clinical teaching. The results of this study should be considered by nursing education and nursing practice professionals. Faculties of nursing need to be concerned about solving student problems in education and clinical practice. The findings support the need for Faculty of Nursing to plan nursing curriculum in a way that nursing students be involved actively in their education.

Dunn SV, Burnett P: The development of a clinical learning environment scale. Journal of Advanced Nursing. 1995, 22: 1166-1173.

Article CAS PubMed Google Scholar

Lindop E: Factors associated with student and pupil nurse wastage. Journal of Advanced Nursing. 1987, 12 (6): 751-756.

Beck D, Srivastava R: Perceived level and source of stress in baccalaureate nursing students. Journal of Nursing Education. 1991, 30 (3): 127-132.

CAS PubMed Google Scholar

Hart G, Rotem A: The best and the worst: Students' experience of clinical education. The Australian Journal of Advanced Nursing. 1994, 11 (3): 26-33.

Sheila Sh, Huey-Shyon L, Shiowli H: Perceived stress and physio-psycho-social status of nursing students during their initial period of clinical practice. International Journal of Nursing Studies. 2002, 39: 165-175. 10.1016/S0020-7489(01)00016-5.

Article Google Scholar

Johnson J: Reducing distress in first level and student nurses. Journal of Advanced Nursing. 2000, 32 (1): 66-74. 10.1046/j.1365-2648.2000.01421.x.

Admi H: Nursing students' stress during the initial clinical experience. Journal of Nursing Education. 1997, 36: 323-327.

Blainey GC: Anxiety in the undergraduate medical-surgical clinical student. Journal of Nursing Education. 1980, 19 (8): 33-36.

Wong J, Wong S: Towards effective clinical teaching in nursing. Journal of Advanced Nursing. 1987, 12 (4): 505-513.

Windsor A: Nursing students' perceptions of clinical experience. Journal of Nursing Education. 1987, 26 (4): 150-154.

Sellek T: Satisfying and anxiety creating incidents for nursing students. Nursing Times. 1982, 78 (35): 137-140.

PubMed Google Scholar

Krueger RA: Focus Groups: A Practical Guide for Applied Research. Sage Publications: California. 1988

Google Scholar

Denzin NK: The Research Act. 1989, Prentice Hall: Englewood Cliffs, New Jersey, 3

Stewart DW, Shamdasani PN: Analysing focus group data. Focus Groups: Theory and Practice. Edited by: Shamdasani PN. 1990, Sage Publications: Newbury Park

Barbour RS, Kitzinger J: Developing focus group research : politics, theory and practice. Sage. 1999

Patton MQ: Qualitative Evaluation and Research Methods. 1990, Sage publications, 2

Graneheim UH, Lundman B: Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Education Today. 2004, 24: 105-112. 10.1016/j.nedt.2003.10.001.

Streubert HJ, Carpenter DR: Qualitative Research in Nursing. Advancing the Humanistic Imperative. 1995, J.B. Lippincott Company: Philadelphia

Polit DF, Hungler BP: Nursing research: Principles and Methods. Philadelphia newyork. 1999

Allmark PA: classical view of the theory-practice gap in nursing. Journal of Advanced Nursing. 1995, 22 (1): 18-23. 10.1046/j.1365-2648.1995.22010018.x.

Tolley KA: Theory from practice for practice: Is this a reality?. Journal of Advanced Nursing. 1995, 21 (1): 184-190. 10.1046/j.1365-2648.1995.21010184.x.

Rolfe G: Listening to students: Course evaluation as action research. Nurse Education Today. 1994, 14 (3): 223-227. 10.1016/0260-6917(94)90085-X.

Johns Ch: clinical supervision as a model for clinical leadership. Journal of Nursing Management. 2003, 11: 25-34. 10.1046/j.1365-2834.2002.00288.x.

Article PubMed Google Scholar

Berggren I, Severinsson E: Nurses supervisors'action in relation to their decision-making style and ethical approach to clinical supervision. Journal of Advanced Nursing. 2003, 41 (6): 615-622. 10.1046/j.1365-2648.2003.02573.x.

Begat I, Severinsson E: Nurses' satisfaction with their work environment and the outcomes of clinical nursing supervision on nurses' experiences of well-being. Journal of Nursing Management. 2005, 13: 221-230. 10.1111/j.1365-2834.2004.00527.x.

Bell P: Anxiety in mature age and higher school certificate entry student nurses – A comparison of effects on performance. Journal of Australian Congress of Mental Health Nurses. 1984, 4/5: 13-21.

Ruth L: Experiencing before and throughout the nursing career. Journal of Advanced Nursing. 2002, 39: 119-10.1046/j.1365-2648.2000.02251.x.

Neary M: Project 2000 students' survival kit: a return to the practical room. Nurse Education Today. 1997, 17 (1): 46-52. 10.1016/S0260-6917(97)80078-0.

Jinks A, Pateman B: Nither this nor that: The stigma of being an undergraduate nurse. Nursing Times. 1998, 2 (2): 12-13.

CAS Google Scholar

Stephen RL: Imagery: A treatment for nursing student anxiety. Journal of Nursing Education. 1992, 31 (7): 314-319.

Grundy SE: The confidence scale. Nurse Educator. 1993, 18 (1): 6-9.

Copeland L: Developing student confidence. Nurse Educator. 1990, 15 (1): 7-

Ferguson K, Jinks A: Integrating what is taught with what is practised in the nursing curriculum: A multi-dimensional model. Journal of Advanced Nursing. 1994, 20 (4): 687-695. 10.1046/j.1365-2648.1994.20040687.x.

Hewison A, Wildman S: The theory-practice gap in nursing: A new dimension. Journal of Advanced Nursing. 1996, 24 (4): 754-761. 10.1046/j.1365-2648.1996.25214.x.

Bjork T: Neglected conflicts in the discipline of nursing: Perceptions of the importance and value of practical skill. Journal of Advanced Nursing. 1995, 22 (1): 6-12. 10.1046/j.1365-2648.1995.22010006.x.

Busen N: Mentoring in advanced practice nursing. Journal of Advanced Nursing Practice. 1999, 2: 2-

Earnshaw GP: Mentorship: The students' view. Nurse Education Today. 1995, 15 (4): 274-279. 10.1016/S0260-6917(95)80130-8.

Kelly B: The professional self-concepts of nursing undergraduates and their perceptions of influential forces. Journal of Nursing Education. 1992, 31 (3): 121-125.

Lynn MR, McCain NL, Boss BJ: Socialization of R.N. to B.S.N Image:. Journal of Nursing Scholarship. 1989, 21 (4): 232-237.

Article CAS Google Scholar

Klein SM, Ritti RR: Understanding Organisational Behaviour. 1980, Kent: Boston

Corwin RG: The professional employee: A study of conflict in nursing roles. The American Journal of Sociology. 1961, 66: 604-615. 10.1086/223010.

Lengacher CA: Effects of professional development seminars on role conception, role deprivation, and self-esteem of generic baccalaureate students. Nursing Connections. 1994, 7 (1): 21-34.

Pre-publication history

The pre-publication history for this paper can be accessed here: http://www.biomedcentral.com/1472-6955/4/6/prepub

Download references

Acknowledgements

The author would like to thank the student nurses who participated in this study for their valuable contribution

Author information

Authors and affiliations.

Psychiatric Nursing Department, Fatemeh (P.B.U.H) College of Nursing and Midwifery Shiraz University of Medical Sciences, Zand BlvD, Shiraz, Iran

Farkhondeh Sharif

English Department, Shiraz University, Shiraz, Iran

Sara Masoumi

You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Farkhondeh Sharif .

Additional information

Competing interests.

The author(s) declare that they no competing interests.

Authors' contributions

FSH: Initiation and design of the research, focus groups conduction, data collection, analysis and writing the paper, SM: Editorial revision of paper

Rights and permissions

Open Access This article is published under license to BioMed Central Ltd. This is an Open Access article is distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and permissions

About this article

Cite this article.

Sharif, F., Masoumi, S. A qualitative study of nursing student experiences of clinical practice. BMC Nurs 4 , 6 (2005). https://doi.org/10.1186/1472-6955-4-6

Download citation

Received : 10 June 2005

Accepted : 09 November 2005

Published : 09 November 2005

DOI : https://doi.org/10.1186/1472-6955-4-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Focus Group
Nursing Student
Professional Role
Nursing Education
Focus Group Session

BMC Nursing

ISSN: 1472-6955

General enquiries: [email protected]

DEGREES & PROGRAMS
Programs & Pathways
Courses & Catalogs
Online Learning
Academic Calendar
Short-Term Training
ADMISSIONS & AID
Financial Aid
Get Started
Paying for College
Michigan Reconnect
SERVICES & SUPPORT
Mentoring & Advising
Career Center
Registration & Records
Library & Learning Services
Student Wellness
Technology Services
Mid Foundation
Facilities & Features
Lifelong Learning
Safety & Security
Current Students
Area Businesses
Future Students
K-12 Counselors
Faculty & Staff

Academic vs Non-Academic Articles

Find Articles
Research Assistance

Academic vs. Non-Academic: What's the Difference?

The majority of your research will require academic and scholarly articles. Many students struggle with trying to determine what an academic source, or article, is.

Academic articles are written by professionals in a given field. They are edited by the author's peers and often take years to publish. Their language is formal and will contain words and terms typical to the field. The author's name will be present, as will their credentials. There will be a list of references that indicate where the author obtained the information they are using in the article.

Academic articles can be found in periodicals similar to the Journal of Psychology, Childhood Education, or The American Journal of Public Health.

The following link is an example of an academic article. Experimental educational networking on open research issues; Studying PSS applicability and development in emerging contexts .

This article is considered academic because the language is very formal and genre-specific, there are two authors and their credentials are listed (these are found at the end of the article), and most importantly there is a list of references.

Non-academic articles are written for the mass public. They are published quickly and can be written by anyone. Their language is informal, and casual and may contain slang. The author may not be provided and will not have any credentials listed. There will be no reference list. Non-academic articles can be found in periodicals similar to Time, Newsweek, or Rolling Stone.

As a general rule religious texts and newspapers are not considered academic sources. Do not use Wikipedia as an academic source. This website can be altered by anyone so any information found within its pages cannot be considered credible or academic.

The following link is an example of a non-academic article. Marketing News's Writers Rules

This article is non-academic because the language is very casual and includes some examples of slang, there is an author, but they chose to write anonymously so there are no credentials provided for the author, and no references were included to show where the author obtained their information.

YouTube Icon
Facebook Icon
Twitter Icon
LinkedIn Icon
Instagram Icon

Open supplemental data
Reference Manager
Simple TEXT file

People also looked at

Original research article, learning scientific observation with worked examples in a digital learning environment.

1 Department Educational Sciences, Chair for Formal and Informal Learning, Technical University Munich School of Social Sciences and Technology, Munich, Germany
2 Aquatic Systems Biology Unit, TUM School of Life Sciences, Technical University of Munich, Freising, Germany

Science education often aims to increase learners’ acquisition of fundamental principles, such as learning the basic steps of scientific methods. Worked examples (WE) have proven particularly useful for supporting the development of such cognitive schemas and successive actions in order to avoid using up more cognitive resources than are necessary. Therefore, we investigated the extent to which heuristic WE are beneficial for supporting the acquisition of a basic scientific methodological skill—conducting scientific observation. The current study has a one-factorial, quasi-experimental, comparative research design and was conducted as a field experiment. Sixty two students of a German University learned about scientific observation steps during a course on applying a fluvial audit, in which several sections of a river were classified based on specific morphological characteristics. In the two experimental groups scientific observation was supported either via faded WE or via non-faded WE both presented as short videos. The control group did not receive support via WE. We assessed factual and applied knowledge acquisition regarding scientific observation, motivational aspects and cognitive load. The results suggest that WE promoted knowledge application: Learners from both experimental groups were able to perform the individual steps of scientific observation more accurately. Fading of WE did not show any additional advantage compared to the non-faded version in this regard. Furthermore, the descriptive results reveal higher motivation and reduced extraneous cognitive load within the experimental groups, but none of these differences were statistically significant. Our findings add to existing evidence that WE may be useful to establish scientific competences.

1 Introduction

Learning in science education frequently involves the acquisition of basic principles or generalities, whether of domain-specific topics (e.g., applying a mathematical multiplication rule) or of rather universal scientific methodologies (e.g., performing the steps of scientific observation) ( Lunetta et al., 2007 ). Previous research has shown that worked examples (WE) can be considered particularly useful for developing such cognitive schemata during learning to avoid using more cognitive resources than necessary for learning successive actions ( Renkl et al., 2004 ; Renkl, 2017 ). WE consist of the presentation of a problem, consecutive solution steps and the solution itself. This is especially advantageous in initial cognitive skill acquisition, i.e., for novice learners with low prior knowledge ( Kalyuga et al., 2001 ). With growing knowledge, fading WE can lead from example-based learning to independent problem-solving ( Renkl et al., 2002 ). Preliminary work has shown the advantage of WE in specific STEM domains like mathematics ( Booth et al., 2015 ; Barbieri et al., 2021 ), but less studies have investigated their impact on the acquisition of basic scientific competencies that involve heuristic problem-solving processes (scientific argumentation, Schworm and Renkl, 2007 ; Hefter et al., 2014 ; Koenen et al., 2017 ). In the realm of natural sciences, various basic scientific methodologies are employed to acquire knowledge, such as experimentation or scientific observation ( Wellnitz and Mayer, 2013 ). During the pursuit of knowledge through scientific inquiry activities, learners may encounter several challenges and difficulties. Similar to the hurdles faced in experimentation, where understanding the criteria for appropriate experimental design, including the development, measurement, and evaluation of results, is crucial ( Sirum and Humburg, 2011 ; Brownell et al., 2014 ; Dasgupta et al., 2014 ; Deane et al., 2014 ), scientific observation additionally presents its own set of issues. In scientific observation, e.g., the acquisition of new insights may be somewhat incidental due to spontaneous and uncoordinated observations ( Jensen, 2014 ). To address these challenges, it is crucial to provide instructional support, including the use of WE, particularly when observations are carried out in a more self-directed manner.

For this reason, the aim of the present study was to determine the usefulness of digitally presented WE to support the acquisition of a basic scientific methodological skill—conducting scientific observations—using a digital learning environment. In this regard, this study examined the effects of different forms of digitally presented WE (non-faded vs. faded) on students’ cognitive and motivational outcomes and compared them to a control group without WE. Furthermore, the combined perspective of factual and applied knowledge, as well as motivational and cognitive aspects, represent further value added to the study.

2 Theoretical background

2.1 worked examples.

WE have been commonly used in the fields of STEM education (science, technology, engineering, and mathematics) ( Booth et al., 2015 ). They consist of a problem statement, the steps to solve the problem, and the solution itself ( Atkinson et al., 2000 ; Renkl et al., 2002 ; Renkl, 2014 ). The success of WE can be explained by their impact on cognitive load (CL) during learning, based on assumptions from Cognitive Load Theory ( Sweller, 2006 ).

Learning with WE is considered time-efficient, effective, and superior to problem-based learning (presentation of the problem without demonstration of solution steps) when it comes to knowledge acquisition and transfer (WE-effect, Atkinson et al., 2000 ; Van Gog et al., 2011 ). Especially WE can help by reducing the extraneous load (presentation and design of the learning material) and, in turn, can lead to an increase in germane load (effort of the learner to understand the learning material) ( Paas et al., 2003 ; Renkl, 2014 ). With regard to intrinsic load (difficulty and complexity of the learning material), it is still controversially discussed if it can be altered by instructional design, e.g., WE ( Gerjets et al., 2004 ). WE have a positive effect on learning and knowledge transfer, especially for novices, as the step-by-step presentation of the solution requires less extraneous mental effort compared to problem-based learning ( Sweller et al., 1998 ; Atkinson et al., 2000 ; Bokosmaty et al., 2015 ). With growing knowledge, WE can lose their advantages (due to the expertise-reversal effect), and scaffolding learning via faded WE might be more successful for knowledge gain and transfer ( Renkl, 2014 ). Faded WE are similar to complete WE, but fade out solution steps as knowledge and competencies grow. Faded WE enhance near-knowledge transfer and reduce errors compared to non-faded WE ( Renkl et al., 2000 ).

In addition, the reduction of intrinsic and extraneous CL by WE also has an impact on learner motivation, such as interest ( Van Gog and Paas, 2006 ). Um et al. (2012) showed that there is a strong positive correlation between germane CL and the motivational aspects of learning, like satisfaction and emotion. Gupta (2019) mentions a positive correlation between CL and interest. Van Harsel et al. (2019) found that WE positively affect learning motivation, while no such effect was found for problem-solving. Furthermore, learning with WE increases the learners’ belief in their competence in completing a task. In addition, fading WE can lead to higher motivation for more experienced learners, while non-faded WE can be particularly motivating for learners without prior knowledge ( Paas et al., 2005 ). In general, fundamental motivational aspects during the learning process, such as situational interest ( Lewalter and Knogler, 2014 ) or motivation-relevant experiences, like basic needs, are influenced by learning environments. At the same time, their use also depends on motivational characteristics of the learning process, such as self-determined motivation ( Deci and Ryan, 2012 ). Therefore, we assume that learning with WE as a relevant component of a learning environment might also influence situational interest and basic needs.

2.1.1 Presentation of worked examples

WE are frequently used in digital learning scenarios ( Renkl, 2014 ). When designing WE, the application via digital learning media can be helpful, as their content can be presented in different ways (video, audio, text, and images), tailored to the needs of the learners, so that individual use is possible according to their own prior knowledge or learning pace ( Mayer, 2001 ). Also, digital media can present relevant information in a timely, motivating, appealing and individualized way and support learning in an effective and needs-oriented way ( Mayer, 2001 ). The advantages of using digital media in designing WE have already been shown in previous studies. Dart et al. (2020) presented WE as short videos (WEV). They report that the use of WEV leads to increased student satisfaction and more positive attitudes. Approximately 90% of the students indicated an active learning approach when learning with the WEV. Furthermore, the results show that students improved their content knowledge through WEV and that they found WEV useful for other courses as well.

Another study ( Kay and Edwards, 2012 ) presented WE as video podcasts. Here, the advantages of WE regarding self-determined learning in terms of learning location, learning time, and learning speed were shown. Learning performance improved significantly after use. The step-by-step, easy-to-understand explanations, the diagrams, and the ability to determine the learning pace by oneself were seen as beneficial.

Multimedia WE can also be enhanced with self-explanation prompts ( Berthold et al., 2009 ). Learning from WE with self-explanation prompts was shown to be superior to other learning methods, such as hypertext learning and observational learning.

In addition to presenting WE in different medial ways, WE can also comprise different content domains.

2.1.2 Content and context of worked examples

Regarding the content of WE, algorithmic and heuristic WE, as well as single-content and double-content WE, can be distinguished ( Reiss et al., 2008 ; Koenen et al., 2017 ; Renkl, 2017 ). Algorithmic WE are traditionally used in the very structured mathematical–physical field. Here, an algorithm with very specific solution steps is to learn, for example, in probability calculation ( Koenen et al., 2017 ). In this study, however, we focus on heuristic double-content WE. Heuristic WE in science education comprise fundamental scientific working methods, e.g., conducting experiments ( Koenen et al., 2017 ). Furthermore, double-content WE contain two learning domains that are relevant for the learning process: (1) the learning domain describes the primarily to be learned abstract process or concept, e.g., scientific methodologies like observation (see section 2.2), while (2) the exemplifying domain consists of the content that is necessary to teach this process or concept, e.g., mapping of river structure ( Renkl et al., 2009 ).

Depending on the WE content to be learned, it may be necessary for learning to take place in different settings. This can be in a formal or informal learning setting or a non-formal field setting. In this study, the focus is on learning scientific observation (learning domain) through river structure mapping (exemplary domain), which takes place with the support of digital media in a formal (university) setting, but in an informal context (nature).

2.2 Scientific observation

Scientific observation is fundamental to all scientific activities and disciplines ( Kohlhauf et al., 2011 ). Scientific observation must be clearly distinguished from everyday observation, where observation is purely a matter of noticing and describing specific characteristics ( Chinn and Malhotra, 2001 ). In contrast to this everyday observation, scientific observation as a method of knowledge acquisition can be described as a rather complex activity, defined as the theory-based, systematic and selective perception of concrete systems and processes without any fundamental manipulation ( Wellnitz and Mayer, 2013 ). Wellnitz and Mayer (2013) described the scientific observation process via six steps: (1) formulation of the research question (s), (2) deduction of the null hypothesis and the alternative hypothesis, (3) planning of the research design, (4) conducting the observation, (5) analyzing the data, and (6) answering the research question(s) on this basis. Only through reliable and qualified observation, valid data can be obtained that provide solid scientific evidence ( Wellnitz and Mayer, 2013 ).

Since observation activities are not trivial and learners often observe without generating new knowledge or connecting their observations to scientific explanations and thoughts, it is important to provide support at the related cognitive level, so that observation activities can be conducted in a structured way according to pre-defined criteria ( Ford, 2005 ; Eberbach and Crowley, 2009 ). Especially during field-learning experiences, scientific observation is often spontaneous and uncoordinated, whereby random discoveries result in knowledge gain ( Jensen, 2014 ).

To promote successful observing in rather unstructured settings like field trips, instructional support for the observation process seems useful. To guide observation activities, digitally presented WE seem to be an appropriate way to introduce learners to the individual steps of scientific observation using concrete examples.

2.3 Research questions and hypothesis

The present study investigates the effect of digitally presented double-content WE that supports the mapping of a small Bavarian river by demonstrating the steps of scientific observation. In this analysis, we focus on the learning domain of the WE and do not investigate the exemplifying domain in detail. Distinct ways of integrating WE in the digital learning environment (faded WE vs. non-faded WE) are compared with each other and with a control group (no WE). The aim is to examine to what extent differences between those conditions exist with regard to (RQ1) learners’ competence acquisition [acquisition of factual knowledge about the scientific observation method (quantitative data) and practical application of the scientific observation method (quantified qualitative data)], (RQ2) learners’ motivation (situational interest and basic needs), and (RQ3) CL. It is assumed that (Hypothesis 1), the integration of WE (faded and non-faded) leads to significantly higher competence acquisition (factual and applied knowledge), significantly higher motivation and significantly lower extraneous CL as well as higher germane CL during the learning process compared to a learning environment without WE. No differences between the conditions are expected regarding intrinsic CL. Furthermore, it is assumed (Hypothesis 2) that the integration of faded WE leads to significantly higher competence acquisition, significantly higher motivation, and lower extraneous CL as well as higher germane CL during the learning processes compared to non-faded WE. No differences between the conditions are expected with regard to intrinsic CL.

The study took place during the field trips of a university course on the application of a fluvial audit (FA) using the German working aid for mapping the morphology of rivers and their floodplains ( Bayerisches Landesamt für Umwelt, 2019 ). FA is the leading fluvial geomorphological tool for application to data collection contiguously along all watercourses of interest ( Walker et al., 2007 ). It is widely used because it is a key example of environmental conservation and monitoring that needs to be taught to students of selected study programs; thus, knowing about the most effective ways of learning is of high practical relevance.

3.1 Sample and design

3.1.1 sample.

The study was conducted with 62 science students and doctoral students of a German University (age M = 24.03 years; SD = 4.20; 36 females; 26 males). A total of 37 participants had already conducted a scientific observation and would rate their knowledge in this regard at a medium level ( M = 3.32 out of 5; SD = 0.88). Seven participants had already conducted an FA and would rate their knowledge in this regard at a medium level ( M = 3.14 out of 5; SD = 0.90). A total of 25 participants had no experience at all. Two participants had to be excluded from the sample afterward because no posttest results were available.

3.1.2 Design

The study has a 1-factorial quasi-experimental comparative research design and is conducted as a field experiment using a pre/posttest design. Participants were randomly assigned to one of three conditions: no WE ( n = 20), faded WE ( n = 20), and non-faded WE ( n = 20).

3.2 Implementation and material

3.2.1 implementation.

The study started with an online kick-off meeting where two lecturers informed all students within an hour about the basics regarding the assessment of the structural integrity of the study river and the course of the field trip days to conduct an FA. Afterward, within 2 weeks, students self-studied via Moodle the FA following the German standard method according to the scoresheets of Bayerisches Landesamt für Umwelt (2019) . This independent preparation using the online presented documents was a necessary prerequisite for participation in the field days and was checked in the pre-testing. The preparatory online documents included six short videos and four PDF files on the content, guidance on the German protocol of the FA, general information on river landscapes, information about anthropogenic changes in stream morphology and the scoresheets for applying the FA. In these sheets, the river and its floodplain are subdivided into sections of 100 m in length. Each of these sections is evaluated by assessing 21 habitat factors related to flow characteristics and structural variability. The findings are then transferred into a scoring system for the description of structural integrity from 1 (natural) to 7 (highly modified). Habitat factors have a decisive influence on the living conditions of animals and plants in and around rivers. They included, e.g., variability in water depth, stream width, substratum diversity, or diversity of flow velocities.

3.2.2 Materials

On the field trip days, participants were handed a tablet and a paper-based FA worksheet (last accessed 21st September 2022). 1 This four-page assessment sheet was accompanied by a digital learning environment presented on Moodle that instructed the participants on mapping the water body structure and guided the scientific observation method. All three Moodle courses were identical in structure and design; the only difference was the implementation of the WE. Below, the course without WE are described first. The other two courses have an identical structure, but contain additional WE in the form of learning videos.

3.2.3 No worked example

After a short welcome and introduction to the course navigation, the FA started with the description of a short hypothetical scenario: Participants should take the role of an employee of an urban planning office that assesses the ecomorphological status of a small river near a Bavarian city. The river was divided into five sections that had to be mapped separately. The course was structured accordingly. At the beginning of each section, participants had to formulate and write down a research question, and according to hypotheses regarding the ecomorphological status of the river’s section, they had to collect data in this regard via the mapping sheet and then evaluate their data and draw a conclusion. Since this course serves as a control group, no WE videos supporting the scientific observation method were integrated. The layout of the course is structured like a book, where it is not possible to scroll back. This is important insofar as the participants do not have the possibility to revisit information in order to keep the conditions comparable as well as distinguishable.

3.2.4 Non-faded worked example

In the course with no-faded WE, three instructional videos are shown for each of the five sections. In each of the three videos, two steps of the scientific observation method are presented so that, finally, all six steps of scientific observation are demonstrated. The mapping of the first section starts after the general introduction (as described above) with the instruction to work on the first two steps of scientific observation: the formulation of a research question and hypotheses. To support this, a video of about 4 min explains the features of scientific sound research questions and hypotheses. To this aim, a practical example, including explanations and tips, is given regarding the formulation of research questions and hypotheses for this section (e.g., “To what extent does the building development and the closeness of the path to the water body have an influence on the structure of the water body?” Alternative hypothesis: It is assumed that the housing development and the closeness of the path to the water body have a negative influence on the water body structure. Null hypothesis: It is assumed that the housing development and the closeness of the path to the watercourse have no negative influence on the watercourse structure.). Participants should now formulate their own research questions and hypotheses, write them down in a text field at the end of the page, and then skip to the next page. The next two steps of scientific observation, planning and conducting, are explained in a short 4-min video. To this aim, a practical example including explanations and tips is given regarding planning and conducting scientific for this section (e.g., “It’s best to go through each evaluation category carefully one by one that way you are sure not to forget anything!”). Now, participants were asked to collect data for the first section using their paper-based FA worksheet. Participants individually surveyed the river and reported their results in the mapping sheet by ticking the respective boxes in it. After collecting this data, they returned to the digital learning environment to learn how to use these data by studying the last two steps of scientific observation, evaluation, and conclusion. The third 4-min video explained how to evaluate and interpret collected data. For this purpose, a practical example with explanations and tips is given regarding evaluating and interpreting data for this section (e.g., “What were the individual points that led to the assessment? Have there been points that were weighted more than others? Remember the introduction video!”). At the end of the page, participants could answer their before-stated research questions and hypotheses by evaluating their collected data and drawing a conclusion. This brings participants to the end of the first mapping section. Afterward, the cycle begins again with the second section of the river that has to be mapped. Again, participants had to conduct the steps of scientific observation, guided by WE videos, explaining the steps in slightly different wording or with different examples. A total of five sections are mapped, in which the structure of the learning environment and the videos follow the same procedure.

3.2.5 Faded worked example

The digital learning environment with the faded WE follow the same structure as the version with the non-faded WE. However, in this version, the information in the WE videos is successively reduced. In the first section, all three videos are identical to the version with the non-faded WE. In the second section, faded content was presented as follows: the tip at the end was omitted in all three videos. In the third section, the tip and the practical example were omitted. In the fourth and fifth sections, no more videos were presented, only the work instructions.

3.3 Procedure

The data collection took place on four continuous days on the university campus, with a maximum group size of 15 participants on each day. The students were randomly assigned to one of the three conditions (no WE vs. faded WE vs. non-faded WE). After a short introduction to the procedure, the participants were handed the paper-based FA worksheet and one tablet per person. Students scanned the QR code on the first page of the worksheet that opened the pretest questionnaire, which took about 20 min to complete. After completing the questionnaire, the group walked for about 15 min to the nearby small river that was to be mapped. Upon arrival, there was first a short introduction to the digital learning environment and a check that the login (via university account on Moodle) worked. During the next 4 h, the participants individually mapped five segments of the river using the cartography worksheet. They were guided through the steps of scientific observation using the digital learning environment on the tablet. The results of their scientific observation were logged within the digital learning environment. At the end of the digital learning environment, participants were directed to the posttest via a link. After completing the test, the tablets and mapping sheets were returned. Overall, the study took about 5 h per group each day.

3.4 Instruments

In the pretest, sociodemographic data (age and gender), the study domain and the number of study semesters were collected. Additionally, the previous scientific observation experience and the estimation of one’s own ability in this regard were assessed. For example, it was asked whether scientific observation had already been conducted and, if so, how the abilities were rated on a 5-point scale from very low to very high. Preparation for the FA on the basis of the learning material was assessed: Participants were asked whether they had studied all six videos and all four PDF documents, with the response options not at all, partially, and completely. Furthermore, a factual knowledge test about scientific observation and questions about self-determination theory was administered. The posttest used the same knowledge test, and additional questions on basic needs, situational interest, measures of CL and questions about the usefulness of the WE. All scales were presented online, and participants reached the questionnaire via QR code.

3.4.1 Scientific observation competence acquisition

For the factual knowledge (quantitative assessment of the scientific observation competence), a single-choice knowledge test with 12 questions was developed and used as pre- and posttest with a maximum score of 12 points. It assesses the learners’ knowledge of the scientific observation method regarding the steps of scientific observation, e.g., formulating research questions and hypotheses or developing a research design. The questions are based on Wahser (2008 , adapted by Koenen, 2014 ) and adapted to scientific observation: “Although you are sure that you have conducted the scientific observation correctly, an unexpected result turns up. What conclusion can you draw?” Each question has four answer options (one of which is correct) and, in addition, one “I do not know” option.

For the applied knowledge (quantified qualitative assessment of the scientific observation competence), students’ scientific observations written in the digital learning environment were analyzed. A coding scheme was used with the following codes: 0 = insufficient (text field is empty or includes only insufficient key points), 1 = sufficient (a research question and no hypotheses or research question and inappropriate hypotheses are stated), 2 = comprehensive (research question and appropriate hypothesis or research question and hypotheses are stated, but, e.g., incorrect null hypothesis), 3 = very comprehensive (correct research question, hypothesis and null hypothesis are stated). One example of a very comprehensive answer regarding the research question and hypothesis is: To what extent does the lack of riparian vegetation have an impact on water body structure? Hypothesis: The lack of shore vegetation has a negative influence on the water body structure. Null hypothesis: The lack of shore vegetation has no influence on the water body structure. Afterward, a sum score was calculated for each participant. Five times, a research question and hypotheses (steps 1 and 2 in the observation process) had to be formulated (5 × max. 3 points = 15 points), and five times, the research questions and hypotheses had to be answered (steps 5 and 6 in the observation process: evaluation and conclusion) (5 × max. 3 points = 15 points). Overall, participants could reach up to 30 points. Since the observation and evaluation criteria in data collection and analysis were strongly predetermined by the scoresheet, steps 3 and 4 of the observation process (planning and conducting) were not included in the analysis.

All 600 cases (60 participants, each 10 responses to code) were coded by the first author. For verification, 240 cases (24 randomly selected participants, eight from each course) were cross-coded by an external coder. In 206 of the coded cases, the raters agreed. The cases in which the raters did not agree were discussed together, and a solution was found. This results in Cohen’s κ = 0.858, indicating a high to very high level of agreement. This indicates that the category system is clearly formulated and that the individual units of analysis could be correctly assigned.

3.4.2 Self-determination index

For the calculation of the self-determination index (SDI-index), Thomas and Müller (2011) scale for self-determination was used in the pretest. The scale consists of four subscales: intrinsic motivation (five items; e.g., I engage with the workshop content because I enjoy it; reliability of alpha = 0.87), identified motivation (four items; e.g., I engage with the workshop content because it gives me more options when choosing a career; alpha = 0.84), introjected motivation (five items; e.g., I engage with the workshop content because otherwise I would have a guilty feeling; alpha = 0.79), and external motivation (three items, e.g., I engage with the workshop content because I simply have to learn it; alpha = 0.74). Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree. To calculate the SDI-index, the sum of the self-determined regulation styles (intrinsic and identified) is subtracted from the sum of the external regulation styles (introjected and external), where intrinsic and external regulation are scored two times ( Thomas and Müller, 2011 ).

3.4.3 Motivation

Basic needs were measured in the posttest with the scale by Willems and Lewalter (2011) . The scale consists of three subscales: perceived competence (four items; e.g., during the workshop, I felt that I could meet the requirements; alpha = 0.90), perceived autonomy (five items; e.g., during the workshop, I felt that I had a lot of freedom; alpha = 0.75), and perceived autonomy regarding personal wishes and goals (APWG) (four items; e.g., during the workshop, I felt that the workshop was how I wish it would be; alpha = 0.93). We added all three subscales to one overall basic needs scale (alpha = 0.90). Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

Situational interest was measured in the posttest with the 12-item scale by Lewalter and Knogler (2014 ; Knogler et al., 2015 ; Lewalter, 2020 ; alpha = 0.84). The scale consists of two subscales: catch (six items; e.g., I found the workshop exciting; alpha = 0.81) and hold (six items; e.g., I would like to learn more about parts of the workshop; alpha = 0.80). Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

3.4.4 Cognitive load

In the posttest, CL was used to examine the mental load during the learning process. The intrinsic CL (three items; e.g., this task was very complex; alpha = 0.70) and extraneous CL (three items; e.g., in this task, it is difficult to identify the most important information; alpha = 0.61) are measured with the scales from Klepsch et al. (2017) . The germane CL (two items; e.g., the learning session contained elements that supported me to better understand the learning material; alpha = 0.72) is measured with the scale from Leppink et al. (2013) . Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

3.4.5 Attitudes toward worked examples

To measure how effective participants rated the WE, we used two scales related to the WE videos as instructional support. The first scale from Renkl (2001) relates to the usefulness of WE. The scale consists of four items (e.g., the explanations were helpful; alpha = 0.71). Two items were recoded because they were formulated negatively. The second scale is from Wachsmuth (2020) and relates to the participant’s evaluation of the WE. The scale consists of nine items (e.g., I always did what was explained in the learning videos; alpha = 0.76). Four items were recoded because they were formulated negatively. Participants could indicate their answers on a 5-point Likert scale ranging from 1 = completely disagree to 5 = completely agree.

3.5 Data analysis

An ANOVA was used to calculate if the variable’s prior knowledge and SDI index differed between the three groups. However, as no significant differences between the conditions were found [prior factual knowledge: F (2, 59) = 0.15, p = 0.865, η 2 = 0.00 self-determination index: F (2, 59) = 0.19, p = 0.829, η 2 = 0.00], they were not included as covariates in subsequent analyses.

Furthermore, a repeated measure, one-way analysis of variance (ANOVA), was conducted to compare the three treatment groups (no WE vs. faded WE vs. non-faded WE) regarding the increase in factual knowledge about the scientific observation method from pretest to posttest.

A MANOVA (multivariate analysis) was calculated with the three groups (no WE vs. non-faded WE vs. faded WE) as a fixed factor and the dependent variables being the practical application of the scientific observation method (first research question), situational interest, basic needs (second research question), and CL (third research question).

Additionally, to determine differences in applied knowledge even among the three groups, Bonferroni-adjusted post-hoc analyses were conducted.

The descriptive statistics between the three groups in terms of prior factual knowledge about the scientific observation method and the self-determination index are shown in Table 1 . The descriptive statistics revealed only small, non-significant differences between the three groups in terms of factual knowledge.

Table 1 . Means (standard deviations) of factual knowledge tests (pre- and posttest) and self-determination index for the three different groups.

The results of the ANOVA revealed that the overall increase in factual knowledge from pre- to posttest just misses significance [ F (1, 57) = 3.68, p = 0.060, η 2 = 0 0.06]. Furthermore, no significant differences between the groups were found regarding the acquisition of factual knowledge from pre- to posttest [ F (2, 57) = 2.93, p = 0.062, η 2 = 0.09].

An analysis of the descriptive statistics showed that the largest differences between the groups were found in applied knowledge (qualitative evaluation) and extraneous load (see Table 2 ).

Table 2 . Means (standard deviations) of dependent variables with the three different groups.

Results of the MANOVA revealed significant overall differences between the three groups [ F (12, 106) = 2.59, p = 0.005, η 2 = 0.23]. Significant effects were found for the application of knowledge [ F (2, 57) = 13.26, p = <0.001, η 2 = 0.32]. Extraneous CL just missed significance [ F (2, 57) = 2.68, p = 0.065, η 2 = 0.09]. There were no significant effects for situational interest [ F (2, 57) = 0.44, p = 0.644, η 2 = 0.02], basic needs [ F (2, 57) = 1.22, p = 0.302, η 2 = 0.04], germane CL [ F (2, 57) = 2.68, p = 0.077, η 2 = 0.09], and intrinsic CL [ F (2, 57) = 0.28, p = 0.757, η 2 = 0.01].

Bonferroni-adjusted post hoc analysis revealed that the group without WE had significantly lower scores in the evaluation of the applied knowledge than the group with non-faded WE ( p = <0.001, M diff = −8.90, 95% CI [−13.47, −4.33]) and then the group with faded WE ( p = <0.001, M diff = −7.40, 95% CI [−11.97, −2.83]). No difference was found between the groups with faded and non-faded WE ( p = 1.00, M diff = −1.50, 95% CI [−6.07, 3.07]).

The descriptive statistics regarding the perceived usefulness of WE and participants’ evaluation of the WE revealed that the group with the faded WE rated usefulness slightly higher than the participants with non-faded WE and also reported a more positive evaluation. However, the results of a MANOVA revealed no significant overall differences [ F (2, 37) = 0.32, p = 0.732, η 2 = 0 0.02] (see Table 3 ).

Table 3 . Means (standard deviations) of dependent variables with the three different groups.

5 Discussion

This study investigated the use of WE to support students’ acquisition of science observation. Below, the research questions are answered, and the implications and limitations of the study are discussed.

5.1 Results on factual and applied knowledge

In terms of knowledge gain (RQ1), our findings revealed no significant differences in participants’ results of the factual knowledge test both across all three groups and specifically between the two experimental groups. These results are in contradiction with related literature where WE had a positive impact on knowledge acquisition ( Renkl, 2014 ) and faded WE are considered to be more effective in knowledge acquisition and transfer, in contrast to non-faded WE ( Renkl et al., 2000 ; Renkl, 2014 ). A limitation of the study is the fact that the participants already scored very high on the pretest, so participation in the intervention would likely not yield significant knowledge gains due to ceiling effects ( Staus et al., 2021 ). Yet, nearly half of the students reported being novices in the field prior to the study, suggesting that the difficulty of some test items might have been too low. Here, it would be important to revise the factual knowledge test, e.g., the difficulty of the distractors in further study.

Nevertheless, with regard to application knowledge, the results revealed large significant differences: Participants of the two experimental groups performed better in conducting scientific observation steps than participants of the control group. In the experimental groups, the non-faded WE group performed better than the faded WE group. However, the absence of significant differences between the two experimental groups suggests that faded and non-faded WE used as double-content WE are suitable to teach applied knowledge about scientific observation in the learning domain ( Koenen, 2014 ). Furthermore, our results differ from the findings of Renkl et al. (2000) , in which the faded version led to the highest knowledge transfer. Despite the fact that the non-faded WE performed best in our study, the faded version of the WE was also appropriate to improve learning, confirming the findings of Renkl (2014) and Hesser and Gregory (2015) .

5.2 Results on learners’ motivation

Regarding participants’ motivation (RQ2; situational interest and basic needs), no significant differences were found across all three groups or between the two experimental groups. However, descriptive results reveal slightly higher motivation in the two experimental groups than in the control group. In this regard, our results confirm existing literature on a descriptive level showing that WE lead to higher learning-relevant motivation ( Paas et al., 2005 ; Van Harsel et al., 2019 ). Additionally, both experimental groups rated the usefulness of the WE as high and reported a positive evaluation of the WE. Therefore, we assume that even non-faded WE do not lead to over-instruction. Regarding the descriptive tendency, a larger sample might yield significant results and detect even small effects in future investigations. However, because this study also focused on comprehensive qualitative data analysis, it was not possible to evaluate a larger sample in this study.

5.3 Results on cognitive load

Finally, CL did not vary significantly across all three groups (RQ3). However, differences in extraneous CL just slightly missed significance. In descriptive values, the control group reported the highest extrinsic and lowest germane CL. The faded WE group showed the lowest extrinsic CL and a similar germane CL as the non-faded WE group. These results are consistent with Paas et al. (2003) and Renkl (2014) , reporting that WE can help to reduce the extraneous CL and, in return, lead to an increase in germane CL. Again, these differences were just above the significance level, and it would be advantageous to retest with a larger sample to detect even small effects.

Taken together, our results only partially confirm H1: the integration of WE (both faded and non-faded WE) led to a higher acquisition of application knowledge than the control group without WE, but higher factual knowledge was not found. Furthermore, higher motivation or different CL was found on a descriptive level only. The control group provided the basis for comparison with the treatment in order to investigate if there is an effect at all and, if so, how large the effect is. This is an important point to assess whether the effort of implementing WE is justified. Additionally, regarding H2, our results reveal no significant differences between the two WE conditions. We assume that the high complexity of the FA could play a role in this regard, which might be hard to handle, especially for beginners, so learners could benefit from support throughout (i.e., non-faded WE).

In addition to the limitations already mentioned, it must be noted that only one exemplary topic was investigated, and the sample only consisted of students. Since only the learning domain of the double-content WE was investigated, the exemplifying domain could also be analyzed, or further variables like motivation could be included in further studies. Furthermore, the influence of learners’ prior knowledge on learning with WE could be investigated, as studies have found that WE are particularly beneficial in the initial acquisition of cognitive skills ( Kalyuga et al., 2001 ).

6 Conclusion

Overall, the results of the current study suggest a beneficial role for WE in supporting the application of scientific observation steps. A major implication of these findings is that both faded and non-faded WE should be considered, as no general advantage of faded WE over non-faded WE was found. This information can be used to develop targeted interventions aimed at the support of scientific observation skills.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics statement

Ethical approval was not required for the study involving human participants in accordance with the local legislation and institutional requirements. Written informed consent to participate in this study was not required from the participants in accordance with the national legislation and the institutional requirements.

Author contributions

ML: Writing – original draft. SM: Writing – review & editing. JP: Writing – review & editing. JG: Writing – review & editing. DL: Writing – review & editing.

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/feduc.2024.1293516/full#supplementary-material

1. ^ https://www.lfu.bayern.de/wasser/gewaesserstrukturkartierung/index.htm

Atkinson, R. K., Derry, S. J., Renkl, A., and Wortham, D. (2000). Learning from examples: instructional principles from the worked examples research. Rev. Educ. Res. 70, 181–214. doi: 10.3102/00346543070002181

Crossref Full Text | Google Scholar

Barbieri, C. A., Booth, J. L., Begolli, K. N., and McCann, N. (2021). The effect of worked examples on student learning and error anticipation in algebra. Instr. Sci. 49, 419–439. doi: 10.1007/s11251-021-09545-6

Bayerisches Landesamt für Umwelt. (2019). Gewässerstrukturkartierung von Fließgewässern in Bayern – Erläuterungen zur Erfassung und Bewertung. (Water structure mapping of flowing waters in Bavaria - Explanations for recording and assessment) . Available at: https://www.bestellen.bayern.de/application/eshop_app000005?SID=1020555825&ACTIONxSESSxSHOWPIC(BILDxKEY:%27lfu_was_00152%27,BILDxCLASS:%27Artikel%27,BILDxTYPE:%27PDF%27)

Google Scholar

Berthold, K., Eysink, T. H., and Renkl, A. (2009). Assisting self-explanation prompts are more effective than open prompts when learning with multiple representations. Instr. Sci. 37, 345–363. doi: 10.1007/s11251-008-9051-z

Bokosmaty, S., Sweller, J., and Kalyuga, S. (2015). Learning geometry problem solving by studying worked examples: effects of learner guidance and expertise. Am. Educ. Res. J. 52, 307–333. doi: 10.3102/0002831214549450

Booth, J. L., McGinn, K., Young, L. K., and Barbieri, C. A. (2015). Simple practice doesn’t always make perfect. Policy Insights Behav. Brain Sci. 2, 24–32. doi: 10.1177/2372732215601691

Brownell, S. E., Wenderoth, M. P., Theobald, R., Okoroafor, N., Koval, M., Freeman, S., et al. (2014). How students think about experimental design: novel conceptions revealed by in-class activities. Bioscience 64, 125–137. doi: 10.1093/biosci/bit016

Chinn, C. A., and Malhotra, B. A. (2001). “Epistemologically authentic scientific reasoning” in Designing for science: implications from everyday, classroom, and professional settings . eds. K. Crowley, C. D. Schunn, and T. Okada (Mahwah, NJ: Lawrence Erlbaum), 351–392.

Dart, S., Pickering, E., and Dawes, L. (2020). Worked example videos for blended learning in undergraduate engineering. AEE J. 8, 1–22. doi: 10.18260/3-1-1153-36021

Dasgupta, A., Anderson, T. R., and Pelaez, N. J. (2014). Development and validation of a rubric for diagnosing students’ experimental design knowledge and difficulties. CBE Life Sci. Educ. 13, 265–284. doi: 10.1187/cbe.13-09-0192

PubMed Abstract | Crossref Full Text | Google Scholar

Deane, T., Nomme, K. M., Jeffery, E., Pollock, C. A., and Birol, G. (2014). Development of the biological experimental design concept inventory (BEDCI). CBE Life Sci. Educ. 13, 540–551. doi: 10.1187/cbe.13-11-0218

Deci, E. L., and Ryan, R. M. (2012). Self-determination theory. In P. A. M. LangeVan, A. W. Kruglanski, and E. T. Higgins (Eds.), Handbook of theories of social psychology , 416–436.

Eberbach, C., and Crowley, K. (2009). From everyday to scientific observation: how children learn to observe the Biologist’s world. Rev. Educ. Res. 79, 39–68. doi: 10.3102/0034654308325899

Ford, D. (2005). The challenges of observing geologically: third graders’ descriptions of rock and mineral properties. Sci. Educ. 89, 276–295. doi: 10.1002/sce.20049

Gerjets, P., Scheiter, K., and Catrambone, R. (2004). Designing instructional examples to reduce intrinsic cognitive load: molar versus modular presentation of solution procedures. Instr. Sci. 32, 33–58. doi: 10.1023/B:TRUC.0000021809.10236.71

Gupta, U. (2019). Interplay of germane load and motivation during math problem solving using worked examples. Educ. Res. Theory Pract. 30, 67–71.

Hefter, M. H., Berthold, K., Renkl, A., Riess, W., Schmid, S., and Fries, S. (2014). Effects of a training intervention to foster argumentation skills while processing conflicting scientific positions. Instr. Sci. 42, 929–947. doi: 10.1007/s11251-014-9320-y

Hesser, T. L., and Gregory, J. L. (2015). Exploring the Use of Faded Worked Examples as a Problem Solving Approach for Underprepared Students. High. Educ. Stud. 5, 36–46.

Jensen, E. (2014). Evaluating children’s conservation biology learning at the zoo. Conserv. Biol. 28, 1004–1011. doi: 10.1111/cobi.12263

Kalyuga, S., Chandler, P., Tuovinen, J., and Sweller, J. (2001). When problem solving is superior to studying worked examples. J. Educ. Psychol. 93, 579–588. doi: 10.1037/0022-0663.93.3.579

Kay, R. H., and Edwards, J. (2012). Examining the use of worked example video podcasts in middle school mathematics classrooms: a formative analysis. Can. J. Learn. Technol. 38, 1–20. doi: 10.21432/T2PK5Z

Klepsch, M., Schmitz, F., and Seufert, T. (2017). Development and validation of two instruments measuring intrinsic, extraneous, and germane cognitive load. Front. Psychol. 8:1997. doi: 10.3389/fpsyg.2017.01997

Knogler, M., Harackiewicz, J. M., Gegenfurtner, A., and Lewalter, D. (2015). How situational is situational interest? Investigating the longitudinal structure of situational interest. Contemp. Educ. Psychol. 43, 39–50. doi: 10.1016/j.cedpsych.2015.08.004

Koenen, J. (2014). Entwicklung und Evaluation von experimentunterstützten Lösungsbeispielen zur Förderung naturwissenschaftlich experimenteller Arbeitsweisen . Dissertation.

Koenen, J., Emden, M., and Sumfleth, E. (2017). Naturwissenschaftlich-experimentelles Arbeiten. Potenziale des Lernens mit Lösungsbeispielen und Experimentierboxen. (scientific-experimental work. Potentials of learning with solution examples and experimentation boxes). Zeitschrift für Didaktik der Naturwissenschaften 23, 81–98. doi: 10.1007/s40573-017-0056-5

Kohlhauf, L., Rutke, U., and Neuhaus, B. J. (2011). Influence of previous knowledge, language skills and domain-specific interest on observation competency. J. Sci. Educ. Technol. 20, 667–678. doi: 10.1007/s10956-011-9322-3

Leppink, J., Paas, F., Van der Vleuten, C. P., Van Gog, T., and Van Merriënboer, J. J. (2013). Development of an instrument for measuring different types of cognitive load. Behav. Res. Methods 45, 1058–1072. doi: 10.3758/s13428-013-0334-1

Lewalter, D. (2020). “Schülerlaborbesuche aus motivationaler Sicht unter besonderer Berücksichtigung des Interesses. (Student laboratory visits from a motivational perspective with special attention to interest)” in Handbuch Forschen im Schülerlabor – theoretische Grundlagen, empirische Forschungsmethoden und aktuelle Anwendungsgebiete . eds. K. Sommer, J. Wirth, and M. Vanderbeke (Münster: Waxmann-Verlag), 62–70.

Lewalter, D., and Knogler, M. (2014). “A questionnaire to assess situational interest – theoretical considerations and findings” in Poster Presented at the 50th Annual Meeting of the American Educational Research Association (AERA) (Philadelphia, PA)

Lunetta, V., Hofstein, A., and Clough, M. P. (2007). Learning and teaching in the school science laboratory: an analysis of research, theory, and practice. In N. Lederman and S. Abel (Eds.). Handbook of research on science education , Mahwah, NJ: Lawrence Erlbaum, 393–441.

Mayer, R. E. (2001). Multimedia learning. Cambridge University Press.

Paas, F., Renkl, A., and Sweller, J. (2003). Cognitive load theory and instructional design: recent developments. Educ. Psychol. 38, 1–4. doi: 10.1207/S15326985EP3801_1

Paas, F., Tuovinen, J., van Merriënboer, J. J. G., and Darabi, A. (2005). A motivational perspective on the relation between mental effort and performance: optimizing learner involvement in instruction. Educ. Technol. Res. Dev. 53, 25–34. doi: 10.1007/BF02504795

Reiss, K., Heinze, A., Renkl, A., and Groß, C. (2008). Reasoning and proof in geometry: effects of a learning environment based on heuristic worked-out examples. ZDM Int. J. Math. Educ. 40, 455–467. doi: 10.1007/s11858-008-0105-0

Renkl, A. (2001). Explorative Analysen zur effektiven Nutzung von instruktionalen Erklärungen beim Lernen aus Lösungsbeispielen. (Exploratory analyses of the effective use of instructional explanations in learning from worked examples). Unterrichtswissenschaft 29, 41–63. doi: 10.25656/01:7677

Renkl, A. (2014). “The worked examples principle in multimedia learning” in Cambridge handbook of multimedia learning . ed. R. E. Mayer (Cambridge University Press), 391–412.

Renkl, A. (2017). Learning from worked-examples in mathematics: students relate procedures to principles. ZDM 49, 571–584. doi: 10.1007/s11858-017-0859-3

Renkl, A., Atkinson, R. K., and Große, C. S. (2004). How fading worked solution steps works. A cognitive load perspective. Instr. Sci. 32, 59–82. doi: 10.1023/B:TRUC.0000021815.74806.f6

Renkl, A., Atkinson, R. K., and Maier, U. H. (2000). “From studying examples to solving problems: fading worked-out solution steps helps learning” in Proceeding of the 22nd Annual Conference of the Cognitive Science Society . eds. L. Gleitman and A. K. Joshi (Mahwah, NJ: Erlbaum), 393–398.

Renkl, A., Atkinson, R. K., Maier, U. H., and Staley, R. (2002). From example study to problem solving: smooth transitions help learning. J. Exp. Educ. 70, 293–315. doi: 10.1080/00220970209599510

Renkl, A., Hilbert, T., and Schworm, S. (2009). Example-based learning in heuristic domains: a cognitive load theory account. Educ. Psychol. Rev. 21, 67–78. doi: 10.1007/s10648-008-9093-4

Schworm, S., and Renkl, A. (2007). Learning argumentation skills through the use of prompts for self-explaining examples. J. Educ. Psychol. 99, 285–296. doi: 10.1037/0022-0663.99.2.285

Sirum, K., and Humburg, J. (2011). The experimental design ability test (EDAT). Bioscene 37, 8–16.

Staus, N. L., O’Connell, K., and Storksdieck, M. (2021). Addressing the ceiling effect when assessing STEM out-of-school time experiences. Front. Educ. 6:690431. doi: 10.3389/feduc.2021.690431

Sweller, J. (2006). The worked example effect and human cognition. Learn. Instr. 16, 165–169. doi: 10.1016/j.learninstruc.2006.02.005

Sweller, J., Van Merriënboer, J. J. G., and Paas, F. (1998). Cognitive architecture and instructional design. Educ. Psychol. Rev. 10, 251–295. doi: 10.1023/A:1022193728205

Thomas, A. E., and Müller, F. H. (2011). “Skalen zur motivationalen Regulation beim Lernen von Schülerinnen und Schülern. Skalen zur akademischen Selbstregulation von Schüler/innen SRQ-A [G] (überarbeitete Fassung)” in Scales of motivational regulation in student learning. Student academic self-regulation scales SRQ-A [G] (revised version). Wissenschaftliche Beiträge aus dem Institut für Unterrichts- und Schulentwicklung Nr. 5 (Klagenfurt: Alpen-Adria-Universität)

Um, E., Plass, J. L., Hayward, E. O., and Homer, B. D. (2012). Emotional design in multimedia learning. J. Educ. Psychol. 104, 485–498. doi: 10.1037/a0026609

Van Gog, T., Kester, L., and Paas, F. (2011). Effects of worked examples, example-problem, and problem- example pairs on novices’ learning. Contemp. Educ. Psychol. 36, 212–218. doi: 10.1016/j.cedpsych.2010.10.004

Van Gog, T., and Paas, G. W. C. (2006). Optimising worked example instruction: different ways to increase germane cognitive load. Learn. Instr. 16, 87–91. doi: 10.1016/j.learninstruc.2006.02.004

Van Harsel, M., Hoogerheide, V., Verkoeijen, P., and van Gog, T. (2019). Effects of different sequences of examples and problems on motivation and learning. Contemp. Educ. Psychol. 58, 260–275. doi: 10.1002/acp.3649

Wachsmuth, C. (2020). Computerbasiertes Lernen mit Aufmerksamkeitsdefizit: Unterstützung des selbstregulierten Lernens durch metakognitive prompts. (Computer-based learning with attention deficit: supporting self-regulated learning through metacognitive prompts) . Chemnitz: Dissertation Technische Universität Chemnitz.

Wahser, I. (2008). Training von naturwissenschaftlichen Arbeitsweisen zur Unterstützung experimenteller Kleingruppenarbeit im Fach Chemie (Training of scientific working methods to support experimental small group work in chemistry) . Dissertation

Walker, J., Gibson, J., and Brown, D. (2007). Selecting fluvial geomorphological methods for river management including catchment scale restoration within the environment agency of England and Wales. Int. J. River Basin Manag. 5, 131–141. doi: 10.1080/15715124.2007.9635313

Wellnitz, N., and Mayer, J. (2013). Erkenntnismethoden in der Biologie – Entwicklung und evaluation eines Kompetenzmodells. (Methods of knowledge in biology - development and evaluation of a competence model). Z. Didaktik Naturwissensch. 19, 315–345.

Willems, A. S., and Lewalter, D. (2011). “Welche Rolle spielt das motivationsrelevante Erleben von Schülern für ihr situationales Interesse im Mathematikunterricht? (What role does students’ motivational experience play in their situational interest in mathematics classrooms?). Befunde aus der SIGMA-Studie” in Erziehungswissenschaftliche Forschung – nachhaltige Bildung. Beiträge zur 5. DGfE-Sektionstagung “Empirische Bildungsforschung”/AEPF-KBBB im Frühjahr 2009 . eds. B. Schwarz, P. Nenninger, and R. S. Jäger (Landau: Verlag Empirische Pädagogik), 288–294.

Keywords: digital media, worked examples, scientific observation, motivation, cognitive load

Citation: Lechner M, Moser S, Pander J, Geist J and Lewalter D (2024) Learning scientific observation with worked examples in a digital learning environment. Front. Educ . 9:1293516. doi: 10.3389/feduc.2024.1293516

Received: 13 September 2023; Accepted: 29 February 2024; Published: 18 March 2024.

Reviewed by:

Copyright © 2024 Lechner, Moser, Pander, Geist and Lewalter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Miriam Lechner, [email protected]

Study Tracks Shifts in Student Mental Health During College

Dartmouth study followed 200 students all four years, including through the pandemic.

Andrew Campbell seated by a window in a blue t-shirt and glasses

Phone App Uses AI to Detect Depression From Facial Cues

A four-year study by Dartmouth researchers captures the most in-depth data yet on how college students’ self-esteem and mental health fluctuates during their four years in academia, identifying key populations and stressors that the researchers say administrators could target to improve student well-being.

The study also provides among the first real-time accounts of how the coronavirus pandemic affected students’ behavior and mental health. The stress and uncertainty of COVID-19 resulted in long-lasting behavioral changes that persisted as a “new normal” even as the pandemic diminished, including students feeling more stressed, less socially engaged, and sleeping more.

The researchers tracked more than 200 Dartmouth undergraduates in the classes of 2021 and 2022 for all four years of college. Students volunteered to let a specially developed app called StudentLife tap into the sensors that are built into smartphones. The app cataloged their daily physical and social activity, how long they slept, their location and travel, the time they spent on their phone, and how often they listened to music or watched videos. Students also filled out weekly behavioral surveys, and selected students gave post-study interviews.

The study—which is the longest mobile-sensing study ever conducted—is published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies .

The researchers will present it at the Association of Computing Machinery’s UbiComp/ISWC 2024 conference in Melbourne, Australia, in October.

These sorts of tools will have a tremendous impact on projecting forward and developing much more data-driven ways to intervene and respond exactly when students need it most.

The team made their anonymized data set publicly available —including self-reports, surveys, and phone-sensing and brain-imaging data—to help advance research into the mental health of students during their college years.

Andrew Campbell , the paper’s senior author and Dartmouth’s Albert Bradley 1915 Third Century Professor of Computer Science, says that the study’s extensive data reinforces the importance of college and university administrators across the country being more attuned to how and when students’ mental well-being changes during the school year.

“For the first time, we’ve produced granular data about the ebb and flow of student mental health. It’s incredibly dynamic—there’s nothing that’s steady state through the term, let alone through the year,” he says. “These sorts of tools will have a tremendous impact on projecting forward and developing much more data-driven ways to intervene and respond exactly when students need it most.”

First-year and female students are especially at risk for high anxiety and low self-esteem, the study finds. Among first-year students, self-esteem dropped to its lowest point in the first weeks of their transition from high school to college but rose steadily every semester until it was about 10% higher by graduation.

“We can see that students came out of high school with a certain level of self-esteem that dropped off to the lowest point of the four years. Some said they started to experience ‘imposter syndrome’ from being around other high-performing students,” Campbell says. “As the years progress, though, we can draw a straight line from low to high as their self-esteem improves. I think we would see a similar trend class over class. To me, that’s a very positive thing.”

Female students—who made up 60% of study participants—experienced on average 5% greater stress levels and 10% lower self-esteem than male students. More significantly, the data show that female students tended to be less active, with male students walking 37% more often.

Sophomores were 40% more socially active compared to their first year, the researchers report. But these students also reported feeling 13% more stressed during their second year than during their first year as their workload increased, they felt pressure to socialize, or as first-year social groups dispersed.

One student in a sorority recalled that having pre-arranged activities “kind of adds stress as I feel like I should be having fun because everyone tells me that it is fun.” Another student noted that after the first year, “students have more access to the whole campus and that is when you start feeling excluded from things.”

In a novel finding, the researchers identify an “anticipatory stress spike” of 17% experienced in the last two weeks of summer break. While still lower than mid-academic year stress, the spike was consistent across different summers.

In post-study interviews, some students pointed to returning to campus early for team sports as a source of stress. Others specified reconnecting with family and high school friends during their first summer home, saying they felt “a sense of leaving behind the comfort and familiarity of these long-standing friendships” as the break ended, the researchers report.

“This is a foundational study,” says Subigya Nepal , first author of the study and a PhD candidate in Campbell’s research group. “It has more real-time granular data than anything we or anyone else has provided before. We don’t know yet how it will translate to campuses nationwide, but it can be a template for getting the conversation going.”

The depth and accuracy of the study data suggest that mobile-sensing software could eventually give universities the ability to create proactive mental-health policies specific to certain student populations and times of year, Campbell says.

For example, a paper Campbell’s research group published in 2022 based on StudentLife data showed that first-generation students experienced lower self-esteem and higher levels of depression than other students throughout their four years of college.

“We will be able to look at campus in much more nuanced ways than waiting for the results of an annual mental health study and then developing policy,” Campbell says. “We know that Dartmouth is a small and very tight-knit campus community. But if we applied these same methods to a college with similar attributes, I believe we would find very similar trends.”

Weathering the pandemic

When students returned home at the start of the coronavirus pandemic, the researchers found that self-esteem actually increased during the pandemic by 5% overall and by another 6% afterward when life returned closer to what it was before. One student suggested in their interview that getting older came with more confidence. Others indicated that being home led to them spending more time with friends talking on the phone, on social media, or streaming movies together.

The data show that phone usage—measured by the duration a phone was unlocked—indeed increased by nearly 33 minutes, or 19%, during the pandemic, while time spent in physical activity dropped by 52 minutes, or 27%. By 2022, phone usage fell from its pandemic peak to just above pre-pandemic levels, while engagement in physical activity had recovered to exceed the pre-pandemic period by three minutes.

Despite reporting higher self-esteem, students’ feelings of stress increased by more than 10% during the pandemic. By the end of the study in June 2022, stress had fallen by less than 2% of its pandemic peak, indicating that the experience had a lasting impact on student well-being, the researchers report.

In early 2021, as students returned to campus, their reunion with friends and community was tempered by an overwhelming concern about the still-rampant coronavirus. “There was the first outbreak in winter 2021 and that was terrifying,” one student recalls. Another student adds: “You could be put into isolation for a long time even if you did not have COVID. Everyone was afraid to contact-trace anyone else in case they got mad at each other.”

Female students were especially concerned about the coronavirus, on average 13% more than male students. “Even though the girls might have been hanging out with each other more, they are more aware of the impact,” one female student reported. “I actually had COVID and exposed some friends of mine. All the girls that I told tested as they were worried. They were continually checking up to make sure that they did not have it and take it home to their family.”

Students still learning remotely had social levels 16% higher than students on campus, who engaged in activity an average of 10% less often than when they were learning from home. However, on-campus students used their phones 47% more often. When interviewed after the study, these students reported spending extended periods of time video-calling or streaming movies with friends and family.

Social activity and engagement had not yet returned to pre-pandemic levels by the end of the study in June 2022, recovering by a little less than 3% after a nearly 10% drop during the pandemic. Similarly, the pandemic correlates with students sticking closer to home, with their distance traveled nearly cut in half during the pandemic and holding at that level since then.

Campbell and several of his fellow researchers are now developing a smartphone app known as MoodCapture that uses artificial intelligence paired with facial-image processing software to reliably detect the onset of depression before the user even knows something is wrong.

Morgan Kelly can be reached at [email protected] .

Mental Health and Wellness
Innovation and Impact
Arts and Sciences
Class of 2021
Class of 2022
Department of Computer Science
Guarini School of Graduate and Advanced Studies
Mental Health

A Q&A With Film Critic and Theorist Vinzenz Hediger

Portrait of Montgomery Fellow Vinzenz Hediger

After a Year of Turmoil, Harvard’s Applications Drop

National Security
Matthew Continetti
Men of the Year

Men Of The Year

Travel Teams and Other Perils of Parenthood

San Francisco Voters Deliver Blow to Soft-on-Crime Policies

Watch: joe biden's senior moment of the week (vol. 87), biden admin coordinates with unrwa after congress banned taxpayer dollars, state department says, biden has no israel policy, court sides with free beacon, gives gallego 15 days to make case for specific redactions to divorce file, san francisco cited this professor to end 8th grade algebra. her research had 'reckless disregard for accuracy,' complaint alleges., complaint against jo boaler alleges 52 instances of misrepresented research.

A Stanford University professor, whose research was credited with inspiring San Francisco’s failed experiment to ax 8th grade algebra, is facing allegations of "reckless disregard for accuracy" in her work, according to an official academic complaint filed Wednesday with Stanford’s provost and dean of research.

The anonymous complaint , backed by a California-based group of math-and-science focused professionals, alleges that Professor Jo Boaler—the most prominent influence on California’s K-12 math framework that nudges schools away from accelerated math pathways—has in 52 instances misrepresented supporting research she has cited in her own work in order to support her conclusions. These include the notions that taking timed tests causes math anxiety, mixing students of different academic levels boosts achievement, and students have been found to perform better when teachers don’t grade their work. This pattern of "citation misrepresentation," the complaint alleges, violates Stanford’s standards of professional conduct for faculty, showing a disregard for accuracy, and may violate the university's research integrity rules.

"[D]ue to the potential impact and influence Dr. Boaler may have upon the math education of CA K-12 public school students … it is imperative to investigate the allegations of citation misrepresentation in Dr. Boaler’s work," the complaint states.

The allegations come amid backlash against equity-focused educational policies Boaler has championed. The University of California—whose 10 campuses include some of the United States’ most prestigious universities—has reasserted its admissions policy that high school students must take Algebra II, and may no longer swap it with "math-light" data science courses such as those produced by Youcubed, a Stanford center run by Boaler. UC's move drew praise from Silicon Valley executives like Tesla founder Elon Musk and OpenAI CEO Sam Altman. And San Francisco public schools are restoring middle school algebra—which the district axed a decade ago citing Boaler as a major influence—after years of declining student performance.

Wednesday’s complaint alleges that Boaler’s pattern of misrepresenting research citations could violate Stanford’s strict standards of accuracy and academic integrity for its faculty. The university’s research handbook states that the "importance of integrity in research cannot be overemphasized," and stresses that faculty have a "responsibility to foster an environment which promotes intellectual honesty and integrity, and which does not tolerate misconduct in any aspect of research or scholarly endeavor." Stanford deems "reckless disregard for accuracy" a "misdeed."

"In the case of a serious violation of these standards, a faculty member may face disciplinary charges," the faculty handbook says .

On the question of timed tests causing "math anxiety," Boaler has asserted that "researchers now know that students experience stress on timed tests that they do not experience even when working on the same math questions in untimed conditions." As evidence, she cites a study by psychologist Randall Engle. However, Engle’s paper in question deals with "working memory" rather than student anxiety, and Engle himself called the assessment a "huge misrepresentation" of his work.

Anna Stokke, a mathematics professor at the University of Winnipeg who has studied this claim and found that it contradicts available evidence, said many math teachers nonetheless seem to believe it—and that their belief seems to stem from Boaler.

"I’ve tried to figure out where this misconception comes from among teachers, that timed tests cause math anxiety, and it often seems to lead back to Jo Boaler's faulty opinion piece," Stokke told the Washington Free Beacon .

In other instances, Boaler has said students have "achieved at significantly higher levels" if teachers offered "diagnostic comments" on their work instead of grading them—citing a 1988 study that involved giving a random sample of students a basic language task and some puzzle questions outside of their normal classrooms. The study did not involve an actual academic class taught over the course of several months—a limitation acknowledged by the study’s author but not by Boaler.

Boaler has also claimed that students reached more advanced levels of math, and enjoyed the subject more, if students of all achievement levels learned together. This assertion was reiterated in California’s math framework as a reason to avoid separating advanced students from their lower-performing peers. But the study cited in both cases was not looking solely at the virtues of classroom diversity, but rather the benefits of teaching an accelerated algebra course to all 8th graders in a "diverse suburban school district"—a fact that went unmentioned by Boaler.

Boaler's spokesman Ian McCaleb on Tuesday declined to comment on the complaint before it was filed.

"Dr. Boaler is confident in the integrity and expansiveness of the research that backs her work," he said.

Cole Sampson, a member of the committee that vetted the California framework who has defended its guidelines and the research behind them, said the complaint is an effort by its opponents to "discredit" Boaler.

"While I am not assuming the intent of those I have never met face-to-face, I could imagine why those with opposing views would choose to target and critique the work of Dr. Boaler over all the others who played a pivotal role in the new framework, given her 100K+ followers on social media and the attention (like this report) would draw to their attempt to slow progress of mathematics in the state of California," Sampson said in an email.

Boaler runs a center out of Stanford called Youcubed , which produces data science courses promoted in the California math framework and offers consulting services. Records from one California public school district showed she charged $5,000 per hour in fees. She has also cultivated a high profile in educational and progressive circles. After she drew negative press for the initial drafts of the equity-focused California math framework that she led, she sought help from Democratic megadonor Laurene Powell Jobs to advocate for the guidelines to California governor Gavin Newsom, according to emails.

In correspondence with the Free Beacon , she has downplayed her influence in San Francisco public schools’ 2014 decision to ditch middle school algebra for equity reasons—a policy that was just reversed by San Francisco’s school board and rejected by a voter referendum. Yet she frequently praised the elimination of that course—in a Stanford video , in her research, and op-eds. The district’s former superintendent also credited her research as an inspiration for the policy.

Published under: Education , K-12 , San Francisco , Stanford University

IMAGES

How to Write a Research Article
literature review article examples Sample of research literature review
Feature Article Sample
Article Writing Examples for Students
Format Example Of Scientific Paper / 2: Example of scientific article
Esse for You: Research report examples for students

VIDEO

how research article are published#article #shorts #subscribe #published
6. HOW TO FIND AN ARTICLE
definitions, concepts, and examples of ideology
How to Write a Research Article?
Connecting Research with Education: 20 research scenarios that require new computational practice
Research Article Writing; Professional Scientific Communication; NPTEL-PMRF Week 3 Live Session

COMMENTS

Research Paper Example
If you are working on your research paper for the first time, here is a collection of examples that you will need to understand the paper's format and how its different parts are drafted. Continue reading the article to get free research paper examples. On This Page. 1. Research Paper Example for Different Formats.
PDF The Impact of Covid-19 on Student Experiences and Expectations
NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts Avenue Cambridge, MA 02138 June 2020 Noah Deitrick and Adam Streff provided excellent research assistance. ... each student believes COVID-19 has impacted their current and future outcomes.2 For example, by asking students about their current GPA in a post-COVID-19 world and their expected ...
Free APA Journal Articles
Recently published articles from subdisciplines of psychology covered by more than 90 APA Journals™ publications. For additional free resources (such as article summaries, podcasts, and more), please visit the Highlights in Psychological Research page. Browse and read free articles from APA Journals across the field of psychology, selected by ...
PDF Describing Populations and Samples in Doctoral Student Research
and describing research structural elements, to include populations and the sam-ple, provides needed scaffolding to doctoral students. Methodology The systematic review of 65 empirical research articles and research texts pro-vided peer-reviewed support for presenting consistent population- and sample-related definitions and exemplars.
Journal of Educational Psychology
A Meta-Analysis (PDF, 215KB) October 2020. by Harriet R. Tenenbaum email the author, Naomi E. Winstone, Patrick J. Leman, and Rachel E. Avery. Last updated: September 2022 Date created: 2009. Read free sample articles from the Journal of Educational Psychology.
A Guide to Writing a Scientific Paper: A Focus on High School Through
This article presents a detailed guide for high school through graduate level instructors that leads students to write effective and well-organized scientific papers. Interesting research emerges from the ability to ask questions, define problems, design experiments, analyze and interpret data, and make critical connections.
How to Write a Research Paper
Develop a thesis statement. Create a research paper outline. Write a first draft of the research paper. Write the introduction. Write a compelling body of text. Write the conclusion. The second draft. The revision process. Research paper checklist.
Exploring Types of Research Articles: Examples & Tips
The following are the most common types of research articles: Original Research Articles: Original research articles report on new research findings. They follow the structure outlined above and ...
(PDF) How to Write an Original Research Article: A Guide for
This paper attempts to give a general outline, which undergraduate students can refer to, and cites a few checklists and official guidelines, which can help in structuring a manuscript. Discover ...
A Practical Guide to Writing Quantitative and Qualitative Research
INTRODUCTION. Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses.1,2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results.3,4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the ...
20+ Research Paper Example
Research Paper Example Outline. Before you plan on writing a well-researched paper, make a rough draft. An outline can be a great help when it comes to organizing vast amounts of research material for your paper. Here is an outline of a research paper example: I. Title Page. A. Title of the Research Paper.
Full article: Fostering student engagement through a real-world
One student, for example, explained that 'the project improved my learning by relating topic to a real world problem. By making the assignment relatable I was more inclined and interested in the topic'. ... Returning to the literature, we found no research on student engagement stemming from students' desire to help their community. The ...
How to Write a Research Proposal
Research proposal examples. Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We've included a few for you below. Example research proposal #1: "A Conceptual Framework for Scheduling Constraint Management" Example research proposal #2: "Medical Students as Mediators of ...
The 10 Most Significant Education Studies of 2021
3. The Surprising Power of Pretesting. Asking students to take a practice test before they've even encountered the material may seem like a waste of time—after all, they'd just be guessing. But new research concludes that the approach, called pretesting, is actually more effective than other typical study strategies.
Research and trends in STEM education: a systematic review of journal
With the rapid increase in the number of scholarly publications on STEM education in recent years, reviews of the status and trends in STEM education research internationally support the development of the field. For this review, we conducted a systematic analysis of 798 articles in STEM education published between 2000 and the end of 2018 in 36 journals to get an overview about developments ...
The top 10 journal articles of 2020
Students with high emotional intelligence get better grades and score higher on standardized tests, according to the research presented in this article in Psychological Bulletin (Vol. 146, No. 2). Researchers analyzed data from 158 studies representing more than 42,529 students—ranging in age from elementary school to college—from 27 countries.
10 Research Question Examples to Guide your Research Project
The first question asks for a ready-made solution, and is not focused or researchable. The second question is a clearer comparative question, but note that it may not be practically feasible. For a smaller research project or thesis, it could be narrowed down further to focus on the effectiveness of drunk driving laws in just one or two countries.
Article Writing for Students
1. The reader is identified. An article is basically a direct conversation with your reader. If a portion in an exam is for you to write an article, the reader may be identified or specified as part of the instructions. That way you can write your article as if you are directly discussing your topic with them.
Investigative Research Projects for Students in Science: The ...
One of the ways in which students can be taught science is by doing science, the intention being to help students understand the nature, processes, and methods of science. Investigative research projects may be used in an attempt to reflect some aspects of science more authentically than other teaching and learning approaches, such as confirmatory practical activities and teacher ...
Research articles
Modeling and development of technology for smelting a complex alloy (ligature) Fe-Si-Mn-Al from manganese-containing briquettes and high-ash coals. Assylbek Nurumgaliyev. Talgat Zhuniskaliyev ...
40 Must-read academic blogs for researchers and PhD students
1. Academics Write ( @academicswrite ): As the name suggests, Academics Write is a blog about "academic writing in all disciplines.". Blog owner, Kim Mitchell is from a nursing discipline and is an Instructor at Red River College, Winnipeg Manitoba, Canada.
(PDF) An Action Research Case Study on Students' Diversity in the
An Action Research Case Study on Students' Diversity in the Classroom: Focus on Students' Diverse Learning Progress. ... whereby a sample of 283 students completed a survey. The results indicate ...
A qualitative study of nursing student experiences of clinical practice
In study done by Hart and Rotem stressful events for nursing students during clinical practice have been studied. They found that the initial clinical experience was the most anxiety producing part of their clinical experience [ 4 ]. The sources of stress during clinical practice have been studied by many researchers [ 5 - 10] and [ 11 ].
Academic vs Non-Academic Articles
Academic articles can be found in periodicals similar to the Journal of Psychology, Childhood Education, or The American Journal of Public Health. The following link is an example of an academic article. Experimental educational networking on open research issues; Studying PSS applicability and development in emerging contexts.
Frontiers
The current study has a one-factorial, quasi-experimental, comparative research design and was conducted as a field experiment. 62 students of a German University learned about scientific observation steps during a course on applying a fluvial audit, in which several sections of a river were classified based on specific morphological ...
Study Tracks Shifts in Student Mental Health During College
The team made their anonymized data set publicly available—including self-reports, surveys, and phone-sensing and brain-imaging data—to help advance research into the mental health of students during their college years.. Andrew Campbell, the paper's senior author and Dartmouth's Albert Bradley 1915 Third Century Professor of Computer Science, says that the study's extensive data ...
Full article: Awarding digital badges: research from a first-year
Research articles. Awarding digital badges: research from a first-year university course. J. Goulding School of Education, University of Newcastle, ... An important caveat to phase 3 data is the sample size, which consisted of two student interviews and one tutor interview, making it difficult to fully delineate the effects of badges and ...
San Francisco Cited This Professor To End 8th Grade Algebra. Her
A Stanford University professor, whose research was credited with inspiring San Francisco's failed experiment to ax 8th grade algebra, is facing allegations of "reckless disregard for accuracy ...