a research objective stems directly from

• Defining Research Objectives: How To  Write Them

Almost all industries use research for growth and development. Research objectives are how researchers ensure that their study has direction and makes a significant contribution to growing an industry or niche.

Research objectives provide a clear and concise statement of what the researcher wants to find out. As a researcher, you need to clearly outline and define research objectives to guide the research process and ensure that the study is relevant and generates the impact you want.

In this article, we will explore research objectives and how to leverage them to achieve successful research studies.

What Are Research Objectives?

Research objectives are what you want to achieve through your research study. They guide your research process and help you focus on the most important aspects of your topic.

You can also define the scope of your study and set realistic and attainable study goals with research objectives. For example, with clear research objectives, your study focuses on the specific goals you want to achieve and prevents you from spending time and resources collecting unnecessary data.

However, sticking to research objectives isn’t always easy, especially in broad or unconventional research. This is why most researchers follow the SMART criteria when defining their research objectives.

Understanding SMART Criteria in Research

Think of research objectives as a roadmap to achieving your research goals, with the SMART criteria as your navigator on the map.

SMART stands for Specific, Measurable, Achievable, Relevant, and Time-bound. These criteria help you ensure that your research objectives are clear, specific, realistic, meaningful, and time-bound.

Here’s a breakdown of the SMART Criteria:

Specific : Your research objectives should be clear: what do you want to achieve, why do you want to achieve it, and how do you plan to achieve it? Avoid vague or broad statements that don’t provide enough direction for your research.

Measurable : Your research objectives should have metrics that help you track your progress and measure your results. Also, ensure the metrics are measurable with data to verify them.

Achievable : Your research objectives should be within your research scope, timeframe, and budget. Also, set goals that are challenging but not impossible.

Relevant: Your research objectives should be in line with the goal and significance of your study. Also, ensure that the objectives address a specific issue or knowledge gap that is interesting and relevant to your industry or niche.

Time-bound : Your research objectives should have a specific deadline or timeframe for completion. This will help you carefully set a schedule for your research activities and milestones and monitor your study progress.

Characteristics of Effective Research Objectives

Clarity : Your objectives should be clear and unambiguous so that anyone who reads them can understand what you intend to do. Avoid vague or general terms that could be taken out of context.

Specificity : Your objectives should be specific and address the research questions that you have formulated. Do not use broad or narrow objectives as they may restrict your field of research or make your research irrelevant.

Measurability : Define your metrics with indicators or metrics that help you determine if you’ve accomplished your goals or not. This will ensure you are tracking the research progress and making interventions when needed.

Also, do use objectives that are subjective or based on personal opinions, as they may be difficult to accurately verify and measure.

Achievability : Your objectives should be realistic and attainable, given the resources and time available for your research project. You should set objectives that match your skills and capabilities, they can be difficult but not so hard that they are realistically unachievable.

For example, setting very difficult make you lose confidence, and abandon your research. Also, setting very simple objectives could demotivate you and prevent you from closing the knowledge gap or making significant contributions to your field with your research.

Relevance : Your objectives should be relevant to your research topic and contribute to the existing knowledge in your field. Avoid objectives that are unrelated or insignificant, as they may waste your time or resources.

Time-bound : Your objectives should be time-bound and specify when you will complete them. Have a realistic and flexible timeframe for achieving your objectives, and track your progress with it. 

Steps to Writing Research Objectives

Identify the research questions.

The first step in writing effective research objectives is to identify the research questions that you are trying to answer. Research questions help you narrow down your topic and identify the gaps or problems that you want to address with your research.

For example, if you are interested in the impact of technology on children’s development, your research questions could be:

• What is the relationship between technology use and academic performance among children?
• Are children who use technology more likely to do better in school than those who do not?
• What is the social and psychological impact of technology use on children?

Brainstorm Objectives

Once you have your research questions, you can brainstorm possible objectives that relate to them. Objectives are more specific than research questions, and they tell you what you want to achieve or learn in your research.

You can use verbs such as analyze, compare, evaluate, explore, investigate, etc. to express your objectives. Also, try to generate as many objectives as possible, without worrying about their quality or feasibility at this stage.

Prioritize Objectives

Once you’ve brainstormed your objectives, you’ll need to prioritize them based on their relevance and feasibility. Relevance is how relevant the objective is to your research topic and how well it fits into your overall research objective.

Feasibility is how realistic and feasible the objective is compared to the time, money, and expertise you have. You can create a matrix or ranking system to organize your objectives and pick the ones that matter the most.

Refine Objectives

The next step is to refine and revise your objectives to ensure clarity and specificity. Start by ensuring that your objectives are consistent and coherent with each other and with your research questions. 

Make Objectives SMART

A useful way to refine your objectives is to make them SMART, which stands for specific, measurable, achievable, relevant, and time-bound. 

• Specific : Objectives should clearly state what you hope to achieve.
• Measurable : They should be able to be quantified or evaluated.
• Achievable : realistic and within the scope of the research study.
• Relevant : They should be directly related to the research questions.
• Time-bound : specific timeframe for research completion.

Review and Finalize Objectives

The final step is to review your objectives for coherence and alignment with your research questions and aim. Ensure your objectives are logically connected and consistent with each other and with the purpose of your study.

You also need to check that your objectives are not too broad or too narrow, too easy or too hard, too many or too few. You can use a checklist or a rubric to evaluate your objectives and make modifications.

Examples of Well-Written Research Objectives

Example 1- Psychology

Research question: What are the effects of social media use on teenagers’ mental health?

Objective : To determine the relationship between the amount of time teenagers in the US spend on social media and their levels of anxiety and depression before and after using social media.

What Makes the Research Objective SMART?

The research objective is specific because it clearly states what the researcher hopes to achieve. It is measurable because it can be quantified by measuring the levels of anxiety and depression in teenagers. 

Also, the objective is achievable because the researcher can collect enough data to answer the research question. It is relevant because it is directly related to the research question. It is time-bound because it has a specific deadline for completion.

Example 2- Marketing

Research question : How can a company increase its brand awareness by 10%?

Objective : To develop a marketing strategy that will increase the company’s sales by 10% within the next quarter.

How Is this Research Objective SMART?

The research states what the researcher hopes to achieve ( Specific ). You can also measure the company’s reach before and after the marketing plan is implemented ( Measurable ).

The research objective is also achievable because you can develop a marketing plan that will increase awareness by 10% within the timeframe. The objective is directly related to the research question ( Relevant ). It is also time-bound because it has a specific deadline for completion.

Research objectives are a well-designed roadmap to completing and achieving your overall research goal. 

However, research goals are only effective if they are well-defined and backed up with the best practices such as the SMART criteria. Properly defining research objectives will help you plan and conduct your research project effectively and efficiently.

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• research goals
• research objectives
• research roadmap
• smart goals
• SMART research objectives
• Moradeke Owa

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• Introduction

Welcome to the journey of mastering research design! In this comprehensive guide, we delve into the art and science of formulating effective research objectives. Whether you’re a seasoned academic or a budding researcher, our step-by-step approach will equip you with the tools to define clear, achievable, and impactful goals for your study. Let’s embark on this journey to transform your research ideas into reality!

• Understanding the Research Problem

Identify the Issue

The first step in formulating research objectives is to identify the issue or problem you want to address in your study. This step is crucial because it lays the foundation for your entire research project. Here’s how to effectively identify the issue:

• Specificity: The issue should be specific and well-defined. Avoid broad topics that are too general, as they can be overwhelming and unmanageable. For example, instead of focusing on “climate change,” a more specific issue could be “the impact of climate change on coastal erosion in the Pacific Northwest.”
• Relevance: Choose an issue that is relevant to your field of study or professional interests. It should be something that piques your curiosity and has significance in the real world.
• Originality: While it’s important to focus on a relevant topic, try to find an angle or aspect that hasn’t been extensively explored. This could involve looking at the problem from a new perspective or using a different methodology.
• Feasibility: Consider the feasibility of studying the issue. Do you have access to the necessary data or resources? Is the scope manageable within the time and constraints you have?

Background Research

Once you have identified a specific issue, the next step is to conduct background research, primarily through a literature review. This involves:

• Surveying Existing Literature: Explore existing research papers, books, articles, and other scholarly material related to your topic. The goal is to gain a comprehensive understanding of what has already been studied and published.
• Identifying Knowledge Gaps: Pay attention to areas that have not been thoroughly explored in the literature. These gaps might present opportunities for your research. For instance, maybe previous studies have overlooked certain geographical areas, demographic groups, or theoretical perspectives.
• Understanding Theories and Models: Familiarize yourself with the theoretical frameworks and models that are commonly used to study your chosen issue. This will help you in conceptualizing your research and positioning it within the broader academic discourse.
• Documenting Key Findings: As you review the literature, document the key findings and major debates related to your topic. This documentation will be invaluable when you start to formulate your own research objectives.
• Critical Analysis: Don’t just summarize the existing literature; critically analyze it. Consider the strengths and weaknesses of previous studies, the methodologies used, and the conclusions drawn.
• Establishing a Rationale: Use your understanding of the current state of knowledge to establish a rationale for your study. Explain why your research is necessary and how it can contribute to filling the identified gaps.

Understanding the research problem is a foundational step in any scholarly inquiry. It involves a careful and critical assessment of the issue at hand, coupled with a thorough review of existing literature. By doing so, researchers can ensure that their work is grounded in the current state of knowledge while also contributing something new and valuable to their field.

• Aligning with Research Questions

Develop Research Questions

Once you have a clear understanding of the research problem, the next step is to develop research questions. These questions guide the direction of your study and ensure that your research is focused and purposeful. Here’s how to develop effective research questions:

• Directly Related to the Research Problem: Your questions should stem directly from the research problem you’ve identified. They serve as a bridge between the broad research problem and the specific objectives you will set to address it.
• Open-Ended and Inquiry-Based : Good research questions are open-ended, encouraging exploration and inquiry. They should not be answerable with a simple yes or no. For example, instead of asking, “Does social media use affect mental health?” a more open-ended question could be, “How does social media use impact the mental health of teenagers?”
• Focused and Manageable: While being open-ended, the questions should also be focused and manageable. They should not be so broad that they become impossible to answer comprehensively within the scope of your research.
• Relevant and Researchable : Choose questions that are relevant to the field and can be researched with the resources and methodologies available to you.

Specificity and Clarity in Objectives

After formulating your research questions, the next step is to ensure that your objectives are specifically and clearly aligned with these questions. Here’s how to achieve this alignment:

• Transforming Questions into Objectives: Convert each research question into one or more specific objectives. These objectives should provide a roadmap for what you need to do in order to answer each question. For instance, if your question is about the impact of social media on teenagers’ mental health, an objective might be to “assess the correlation between social media usage patterns and anxiety levels in teenagers aged 13-18.”
• Clarity and Precision : Objectives should be clearly stated, leaving no room for ambiguity. Use precise language that conveys exactly what you intend to do, how you plan to do it, and what you hope to achieve.
• Measurable and Observable: The objectives should be framed in a way that their achievement can be measured and observed. This could involve quantitative measures, such as statistical analysis, or qualitative ones, like thematic analysis of interview data.
• Directly Answering the Research Questions: Each objective should directly contribute to answering one or more of your research questions. There should be a clear and logical connection between your questions and the objectives you set.

Aligning research objectives with research questions is a critical process in ensuring that your study is coherent and focused. This alignment not only guides the direction of your research but also ensures that the objectives you set are directly relevant to answering the key questions posed by your research problem. By developing clear, specific, and researchable questions and translating them into measurable objectives, you create a solid framework for a successful research project.

• Setting SMART Objectives

When formulating research objectives, it’s crucial to use the SMART criteria: Specific, Measurable, Achievable, Relevant, and Time-Bound. This framework ensures that your objectives are well-defined and feasible, setting a clear path for your research.

• Clear and Defined Goals: Objectives should be explicitly stated, leaving no room for ambiguity. They should clearly define what you intend to accomplish. For example, instead of a vague objective like “understand customer behavior,” a specific objective would be “identify the primary factors influencing purchase decisions among customers aged 20-30 in the retail sector.”
• Detail-Oriented: Incorporate details such as who is involved, what you want to accomplish, and where the study will take place.
• Quantifiable Indicators: Objectives should have criteria that allow for measuring progress and success. This could involve quantitative measures (like survey response rates, statistical analysis results) or qualitative measures (like themes from interview data).
• Tracking Progress: Measurable objectives enable you to track your progress systematically and assess whether you are moving towards achieving your goals.
• Realistic Goals: Ensure that your objectives are attainable given your resources, time, and constraints. They should be challenging yet feasible.
• Resource Consideration: Consider your access to resources such as data, research materials, and funding when setting objectives. For example, an objective to conduct a nationwide survey might not be achievable for an individual researcher due to resource constraints.
• Alignment with Research Problem: Your objectives should be directly related to your research problem. They should contribute towards filling the knowledge gaps identified in your literature review.
• Appropriateness for the Field: Ensure that your objectives are suitable for your area of study and contribute to the broader field of knowledge.
• Clear Deadlines: Set realistic deadlines for each objective. This helps in creating a schedule for your research and keeps you focused.
• Consider Research Phases : Break down the research into phases and assign timeframes for each objective. This structured approach ensures steady progress.

SMART objectives are a cornerstone of effective research planning. By ensuring that each objective is Specific, Measurable, Achievable, Relevant, and Time-Bound, researchers can create a clear, focused, and feasible roadmap for their study. This not only streamlines the research process but also enhances the likelihood of producing meaningful and impactful results.

• Types of Objectives

Research objectives can be categorized into different types based on the nature and purpose of the study. Understanding these types helps in formulating objectives that align with the overall goals of your research. The four primary types are Exploratory, Descriptive, Explanatory, and Predictive.

Exploratory Objectives

• Purpose: Exploratory research objectives are set when a researcher aims to explore a phenomenon that is not yet well understood. The goal is to gain insights and familiarity with the subject matter.
• Characteristics: These objectives often involve investigating new ideas, asking open-ended questions, and exploring different aspects of a topic without a predefined direction or hypothesis.
• Application: Exploratory objectives are common in new fields of study or when studying aspects that have not been deeply researched. For example, exploring how a newly emerged technology is impacting consumer behavior.

Descriptive Objectives

• Purpose: Descriptive research objectives aim to describe the characteristics of variables or phenomena. The goal is to paint a picture of situations, events, or conditions.
• Characteristics: These objectives are focused on answering the “what,” “where,” and “when” of a subject. They do not delve into the “why” – that’s left for explanatory research.
• Application: An example could be describing the demographic characteristics of consumers who use a particular service or mapping the geographic distribution of a certain phenomenon.

Explanatory Objectives

• Purpose: Explanatory research objectives aim to explain the relationships and causal connections between variables. They delve into understanding the “why” and “how” of phenomena.
• Characteristics: These objectives often involve hypothesis testing. They seek to establish cause-and-effect relationships and are more structured compared to exploratory or descriptive research.
• Application: For instance, explaining how consumer satisfaction impacts brand loyalty or understanding the causal factors behind environmental changes in a specific region.

Predictive Objectives

• Purpose: Predictive research objectives are focused on forecasting future occurrences or trends based on current data and trends. The aim is to make predictions about future events or behaviors.
• Characteristics: These objectives involve analyzing current and historical data to identify patterns and trends that can be used to make predictions about the future.
• Application: Examples include predicting market trends based on current economic data or forecasting the impact of climate change on biodiversity.

The type of research objectives you choose should align with the overall purpose and scope of your study. Each type serves a different role in the research process, and understanding these differences is key to formulating effective and relevant objectives. Exploratory objectives are best for new or unexplored areas, descriptive for painting detailed pictures, explanatory for understanding causality, and predictive for forecasting future trends or events.

• Balancing Scope and Depth

Balancing scope and depth is crucial in research to ensure that the study is both manageable and meaningful. This involves considering the feasibility of the objectives and carefully defining the scope of the research.

Feasibility

• Realistic Assessment of Resources: Assess the resources available to you, including time, funding, equipment, and data access. Your objectives should be achievable within these constraints.
• Time Management: Consider the amount of time you have to complete the research. Set realistic deadlines for each phase of your research, taking into account potential obstacles and delays.
• Resource Allocation: Allocate your resources effectively. This includes human resources (like research assistants), financial resources, and any specific materials or tools required for your study.
• Adjusting Objectives: If you find that certain objectives are not feasible, don’t hesitate to adjust them. It’s better to have a smaller set of achievable objectives than a larger set of unattainable ones.
• Clearly Defined Boundaries: The scope of your research refers to what the study will cover and what it will not. It’s important to define these boundaries clearly to ensure that your research remains focused and manageable.
• Avoiding Over-Broad Topics: A scope that is too broad can make your research unwieldy and diffuse. For instance, a study on “climate change” is enormously broad; narrowing it down to a specific aspect like “the impact of climate change on urban coastal areas in the coastal region of Kenya” is more manageable.
• Avoiding Over-Narrow Topics: Conversely, a scope that is too narrow may not offer enough material for a comprehensive study. It’s important to find a middle ground where your research is specific enough to be in-depth but broad enough to be significant.
• Iterative Process: Defining the scope is often an iterative process. As you delve deeper into your research, you might find it necessary to either broaden or narrow your focus. Be flexible and willing to adjust the scope as needed.

Balancing scope and depth in research involves a careful consideration of what is feasible within the constraints of your resources and time, and defining clear boundaries for what your study will cover. This balance is key to creating a focused, manageable, and meaningful research project. It requires an ongoing process of assessment and adjustment to align the research objectives with the practicalities of conducting the study.

• Review and Refinement:
• Peer Feedback: Seek feedback from peers or advisors to refine your objectives.
• Flexibility: Be prepared to refine your objectives as you progress in your research.
• Writing Clear Objectives:
• Concise and Focused: Use clear, concise language.
• Avoid Ambiguity: Make sure there’s no room for misinterpretation.
• Active Voice: Use active voice for clarity and directness.
• Ethical Considerations:
• Ethical Approval: Ensure your objectives do not breach ethical guidelines.
• Respect for Participants: If your research involves participants, respect their rights and privacy.
• Record-Keeping: Keep a detailed record of how you formulated your objectives.
• Justification: Be prepared to justify how your objectives contribute to the field.
• Examples for Reference:
• Provide Context: Use examples from previous research to illustrate how objectives were formulated effectively.

Conclusion:

In conclusion, crafting well-defined research objectives is a vital step in the journey of any research project. By applying the principles of specificity, measurability, achievability, relevance, and time-bound criteria, your research is set on a path of clarity and purpose. Remember, a good research objective not only guides your study but also significantly enhances its impact and validity. Embrace this process as a foundational element of your research journey, and you’ll find yourself well-equipped to explore, describe, explain, and predict the fascinating world of your study. Happy researching!

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How to write a research question

Last updated

7 February 2023

Reviewed by

Miroslav Damyanov

In this article, we take an in-depth look at what a research question is, the different types of research questions, and how to write one (with examples). Read on to get started with your thesis, dissertation, or research paper .

Make research less tedious

Dovetail streamlines research to help you uncover and share actionable insights

• What is a research question?

A research question articulates exactly what you want to learn from your research. It stems directly from your research objectives, and you will arrive at an answer through data analysis and interpretation.

However, it is not that simple to write a research question—even when you know the question you intend to answer with your study. The main characteristics of a good research question are:

Feasible. You need to have the resources and abilities to examine the question, collect the data, and give answers.

Interesting. Create research questions that offer fascinating insights into your industry.

Novel. Research questions have to offer something new within your field of study.

Ethical. The research question topic should be approved by the relevant authorities and review boards.

Relevant. Your research question should lead to visible changes in society or your industry.

Usually, you write one single research question to guide your entire research paper. The answer becomes the thesis statement—the central position of your argument. A dissertation or thesis, on the other hand, may require multiple problem statements and research questions. However, they should be connected and focused on a specific problem.

• Importance of the research question

A research question acts as a guide for your entire study. It serves two vital purposes:

to determine the specific issue your research paper addresses

to identify clear objectives

Therefore, it helps split your research into small steps that you need to complete to provide answers.

Your research question will also provide boundaries for your study, which help set limits and ensure cohesion.

Finally, it acts as a frame of reference for assessing your work. Bear in mind that research questions can evolve, shift, and change during the early stages of your study or project.

• Types of research questions

The type of research you are conducting will dictate the type of research question to use. Primarily, research questions are grouped into three distinct categories of study:

qualitative

quantitative

mixed-method

Let’s look at each of these in turn:

Quantitative research questions

The number-one rule of quantitative research questions is that they are precise. They mainly include:

independent and dependent variables

the exact population being studied

the research design to be used

Therefore, you must frame and finalize quantitative research questions before starting the study.

Equally, a quantitative research question creates a link between itself and the research design. These questions cannot be answered with simple 'yes' or' no' responses, so they begin with words like 'does', 'do', 'are', and 'is'.

Quantitative research questions can be divided into three categories:

Relationship research questions usually leverage words such as 'trends' and 'association' because they include independent and dependent variables. They seek to define or explore trends and interactions between multiple variables.

Comparative research questions tend to analyze the differences between different groups to find an outcome variable. For instance, you may decide to compare two distinct groups where a specific variable is present in one and absent in the other.

Descriptive research questions usually start with the word 'what' and aim to measure how a population will respond to one or more variables.

Qualitative research questions

Like quantitative research questions, these questions are linked to the research design. However, qualitative research questions may deal with a specific or broad study area. This makes them more flexible, very adaptable, and usually non-directional.

Use qualitative research questions when your primary aim is to explain, discover, or explore.

There are seven types of qualitative research questions:

Explanatory research questions investigate particular topic areas that aren't well known.

Contextual research questions describe the workings of what is already in existence.

Evaluative research questions examine the effectiveness of specific paradigms or methods.

Ideological research questions aim to advance existing ideologies.

Descriptive research questions describe an event.

Generative research questions help develop actions and theories by providing new ideas.

Emancipatory research questions increase social action engagement, usually to benefit disadvantaged people.

Mixed-methods studies

With mixed-methods studies, you combine qualitative and quantitative research elements to get answers to your research question. This approach is ideal when you need a more complete picture. through a blend of the two approaches.

Mixed-methods research is excellent in multidisciplinary settings, societal analysis, and complex situations. Consider the following research question examples, which would be ideal candidates for a mixed-methods approach

How can non-voter and voter beliefs about democracy (qualitative) help explain Town X election turnout patterns (quantitative)?

How does students’ perception of their study environment (quantitative) relate to their test score differences (qualitative)?

• Developing a strong research question—a step-by-step guide

Research questions help break up your study into simple steps so you can quickly achieve your objectives and find answers. However, how do you develop a good research question? Here is our step-by-step guide:

1. Choose a topic

The first step is to select a broad research topic for your study. Pick something within your expertise and field that interests you. After all, the research itself will stem from the initial research question.

2. Conduct preliminary research

Once you have a broad topic, dig deeper into the problem by researching past studies in the field and gathering requirements from stakeholders if you work in a business setting.

Through this process, you will discover articles that mention areas not explored in that field or products that didn’t resonate with people’s expectations in a particular industry. For instance, you could explore specific topics that earlier research failed to study or products that failed to meet user needs.

3. Keep your audience in mind

Is your audience interested in the particular field you want to study? Are the research questions in your mind appealing and interesting to the audience? Defining your audience will help you refine your research question and ensure you pick a question that is relatable to your audience.

4. Generate a list of potential questions

Ask yourself numerous open-ended questions on the topic to create a potential list of research questions. You could start with broader questions and narrow them down to more specific ones. Don’t forget that you can challenge existing assumptions or use personal experiences to redefine research issues.

5. Review the questions

Evaluate your list of potential questions to determine which seems most effective. Ensure you consider the finer details of every question and possible outcomes. Doing this helps you determine if the questions meet the requirements of a research question.

6. Construct and evaluate your research question

Consider these two frameworks when constructing a good research question: PICOT and PEO. 

PICOT stands for:

P: Problem or population

I: Indicator or intervention to be studied

C: Comparison groups

O: Outcome of interest

T: Time frame

PEO stands for:

P: Population being studied

E: Exposure to any preexisting conditions

To evaluate your research question once you’ve constructed it, ask yourself the following questions:

Is it clear?

Your study should produce precise data and observations. For qualitative studies, the observations need to be delineable across categories. Quantitative studies must have measurable and empirical data.

Is it specific and focused?

An excellent research question must be specific enough to ensure your testing yields objective results. General or open-ended research questions are often ambiguous and subject to different kinds of interpretation.

Is it sufficiently complex?

Your research needs to yield substantial and consequential results to warrant the study. Merely supporting or reinforcing an existing paper is not good enough.

• Examples of good research questions

A robust research question actively contributes to a specific body of knowledge; it is a question that hasn’t been answered before within your research field.

Here are some examples of good and bad research questions :

Good: How effective are A and B policies at reducing the rates of Z?

Bad: Is A or B a better policy?

The first is more focused and researchable because it isn't based on value judgment. The second fails to give clear criteria for answering the question.

Good: What is the effect of daily Twitter use on the attention span of college students?

Bad: What is the effect of social media use on people's minds?

The first includes specific and well-defined concepts, which the second lacks.

Ensure all terms within your research question have precise meanings. Avoid vague or general language that makes the topic too broad.

• The bottom line

The success of any research starts with formulating the right questions that ensure you collect the most insightful data. A good research question will showcase the objectives of your systematic investigation and emphasize specific contexts.

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Research Aims, Objectives & Questions

The “Golden Thread” Explained Simply (+ Examples)

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

The research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?  

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples  

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

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Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples  

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).  

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples  

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.  

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment 

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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38 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

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Crafting Clear Pathways: Writing Objectives in Research Papers

Struggling to write research objectives? Follow our easy steps to learn how to craft effective and compelling objectives in research papers.

Are you struggling to define the goals and direction of your research? Are you losing yourself while doing research and tend to go astray from the intended research topic? Fear not, as many face the same problem and it is quite understandable to overcome this, a concept called research objective comes into play here.

In this article, we’ll delve into the world of the objectives in research papers and why they are essential for a successful study. We will be studying what they are and how they are used in research.

What is a Research Objective?

A research objective is a clear and specific goal that a researcher aims to achieve through a research study. It serves as a roadmap for the research, providing direction and focus. Research objectives are formulated based on the research questions or hypotheses, and they help in defining the scope of the study and guiding the research design and methodology. They also assist in evaluating the success and outcomes of the research.

Types of Research Objectives

There are typically three main types of objectives in a research paper:

• Exploratory Objectives: These objectives are focused on gaining a deeper understanding of a particular phenomenon, topic, or issue. Exploratory research objectives aim to explore and identify new ideas, insights, or patterns that were previously unknown or poorly understood. This type of objective is commonly used in preliminary or qualitative studies.
• Descriptive Objectives: Descriptive objectives seek to describe and document the characteristics, behaviors, or attributes of a specific population, event, or phenomenon. The purpose is to provide a comprehensive and accurate account of the subject of study. Descriptive research objectives often involve collecting and analyzing data through surveys, observations, or archival research.
• Explanatory or Causal Objectives: Explanatory objectives aim to establish a cause-and-effect relationship between variables or factors. These objectives focus on understanding why certain events or phenomena occur and how they are related to each other. 

Also Read: What are the types of research?

Steps for Writing Objectives in Research Paper

1. identify the research topic:.

Clearly define the subject or topic of your research. This will provide a broad context for developing specific research objectives.

2. Conduct a Literature Review

Review existing literature and research related to your topic. This will help you understand the current state of knowledge, identify any research gaps, and refine your research objectives accordingly.

3. Identify the Research Questions or Hypotheses

Formulate specific research questions or hypotheses that you want to address in your study. These questions should be directly related to your research topic and guide the development of your research objectives.

4. Focus on Specific Goals

Break down the broader research questions or hypothesis into specific goals or objectives. Each objective should focus on a particular aspect of your research topic and be achievable within the scope of your study.

5. Use Clear and Measurable Language

Write your research objectives using clear and precise language. Avoid vague terms and use specific and measurable terms that can be observed, analyzed, or measured.

6. Consider Feasibility

Ensure that your research objectives are feasible within the available resources, time constraints, and ethical considerations. They should be realistic and attainable given the limitations of your study.

7. Prioritize Objectives

If you have multiple research objectives, prioritize them based on their importance and relevance to your overall research goals. This will help you allocate resources and focus your efforts accordingly.

8. Review and Refine

Review your research objectives to ensure they align with your research questions or hypotheses, and revise them if necessary. Seek feedback from peers or advisors to ensure clarity and coherence.

Tips for Writing Objectives in Research Paper

1. be clear and specific.

Clearly state what you intend to achieve with your research. Use specific language that leaves no room for ambiguity or confusion. This ensures that your objectives are well-defined and focused.

2. Use Action Verbs

Begin each research objective with an action verb that describes a measurable action or outcome. This helps make your objectives more actionable and measurable.

3. Align with Research Questions or Hypotheses

Your research objectives should directly address the research questions or hypotheses you have formulated. Ensure there is a clear connection between them to maintain coherence in your study.

4. Be Realistic and Feasible

Set research objectives that are attainable within the constraints of your study, including available resources, time, and ethical considerations. Unrealistic objectives may undermine the validity and reliability of your research.

5. Consider Relevance and Significance

Your research objectives should be relevant to your research topic and contribute to the broader field of study. Consider the potential impact and significance of achieving the objectives.

SMART Goals for Writing Research Objectives

To ensure that your research objectives are well-defined and effectively guide your study, you can apply the SMART framework. SMART stands for Specific, Measurable, Achievable, Relevant, and Time-bound. Here’s how you can make your research objectives SMART:

• Specific : Clearly state what you want to achieve in a precise and specific manner. Avoid vague or generalized language. Specify the population, variables, or phenomena of interest.
• Measurable : Ensure that your research objectives can be quantified or observed in a measurable way. This allows for objective evaluation and assessment of progress.
• Achievable : Set research objectives that are realistic and attainable within the available resources, time, and scope of your study. Consider the feasibility of conducting the research and collecting the necessary data.
• Relevant : Ensure that your research objectives are directly relevant to your research topic and contribute to the broader knowledge or understanding of the field. They should align with the purpose and significance of your study.
• Time-bound : Set a specific timeframe or deadline for achieving your research objectives. This helps create a sense of urgency and provides a clear timeline for your study.

Examples of Research Objectives

Here are some examples of research objectives from various fields of study:

• To examine the relationship between social media usage and self-esteem among young adults aged 18-25 in order to understand the potential impact on mental well-being.
• To assess the effectiveness of a mindfulness-based intervention in reducing stress levels and improving coping mechanisms among individuals diagnosed with anxiety disorders.
• To investigate the factors influencing consumer purchasing decisions in the e-commerce industry, with a focus on the role of online reviews and social media influencers.
• To analyze the effects of climate change on the biodiversity of coral reefs in a specific region, using remote sensing techniques and field surveys.

Importance of Research Objectives

Research objectives play a crucial role in the research process and hold significant importance for several reasons:

• Guiding the Research Process: Research objectives provide a clear roadmap for the entire research process. They help researchers stay focused and on track, ensuring that the study remains purposeful and relevant. 
• Defining the Scope of the Study: Research objectives help in determining the boundaries and scope of the study. They clarify what aspects of the research topic will be explored and what will be excluded. 
• Providing Direction for Data Collection and Analysis: Research objectives assist in identifying the type of data to be collected and the methods of data collection. They also guide the selection of appropriate data analysis techniques. 
• Evaluating the Success of the Study: Research objectives serve as benchmarks for evaluating the success and outcomes of the research. They provide measurable criteria against which the researcher can assess whether the objectives have been met or not. 
• Enhancing Communication and Collaboration: Clearly defined research objectives facilitate effective communication and collaboration among researchers, advisors, and stakeholders. 

Common Mistakes to Avoid While Writing Research Objectives

When writing research objectives, it’s important to be aware of common mistakes and pitfalls that can undermine the effectiveness and clarity of your objectives. Here are some common mistakes to avoid:

• Vague or Ambiguous Language: One of the key mistakes is using vague or ambiguous language that lacks specificity. Ensure that your research objectives are clearly and precisely stated, leaving no room for misinterpretation or confusion.
• Lack of Measurability: Research objectives should be measurable, meaning that they should allow for the collection of data or evidence that can be quantified or observed. Avoid setting objectives that cannot be measured or assessed objectively.
• Lack of Alignment with Research Questions or Hypotheses: Your research objectives should directly align with the research questions or hypotheses you have formulated. Make sure there is a clear connection between them to maintain coherence in your study.
• Overgeneralization : Avoid writing research objectives that are too broad or encompass too many variables or phenomena. Overgeneralized objectives may lead to a lack of focus or feasibility in conducting the research.
• Unrealistic or Unattainable Objectives: Ensure that your research objectives are realistic and attainable within the available resources, time, and scope of your study. Setting unrealistic objectives may compromise the validity and reliability of your research.

In conclusion, research objectives are integral to the success and effectiveness of any research study. They provide a clear direction, focus, and purpose, guiding the entire research process from start to finish. By formulating specific, measurable, achievable, relevant, and time-bound objectives, researchers can define the scope of their study, guide data collection and analysis, and evaluate the outcomes of their research.

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About Sowjanya Pedada

Sowjanya is a passionate writer and an avid reader. She holds MBA in Agribusiness Management and now is working as a content writer. She loves to play with words and hopes to make a difference in the world through her writings. Apart from writing, she is interested in reading fiction novels and doing craftwork. She also loves to travel and explore different cuisines and spend time with her family and friends.

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Frequently asked questions

How do i write a research objective.

Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .

Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.

I will compare …

Frequently asked questions: Writing a research paper

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

Research questions anchor your whole project, so it’s important to spend some time refining them.

In general, they should be:

• Focused and researchable
• Answerable using credible sources
• Complex and arguable
• Feasible and specific
• Relevant and original

All research questions should be:

• Focused on a single problem or issue
• Researchable using primary and/or secondary sources
• Feasible to answer within the timeframe and practical constraints
• Specific enough to answer thoroughly
• Complex enough to develop the answer over the space of a paper or thesis
• Relevant to your field of study and/or society more broadly

A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.

Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.

Your research objectives indicate how you’ll try to address your research problem and should be specific:

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

The main guidelines for formatting a paper in Chicago style are to:

• Use a standard font like 12 pt Times New Roman
• Use 1 inch margins or larger
• Apply double line spacing
• Indent every new paragraph ½ inch
• Include a title page
• Place page numbers in the top right or bottom center
• Cite your sources with author-date citations or Chicago footnotes
• Include a bibliography or reference list

To automatically generate accurate Chicago references, you can use Scribbr’s free Chicago reference generator .

The main guidelines for formatting a paper in MLA style are as follows:

• Use an easily readable font like 12 pt Times New Roman
• Set 1 inch page margins
• Include a four-line MLA heading on the first page
• Center the paper’s title
• Use title case capitalization for headings
• Cite your sources with MLA in-text citations
• List all sources cited on a Works Cited page at the end

To format a paper in APA Style , follow these guidelines:

• Use a standard font like 12 pt Times New Roman or 11 pt Arial
• If submitting for publication, insert a running head on every page
• Apply APA heading styles
• Cite your sources with APA in-text citations
• List all sources cited on a reference page at the end

No, it’s not appropriate to present new arguments or evidence in the conclusion . While you might be tempted to save a striking argument for last, research papers follow a more formal structure than this.

All your findings and arguments should be presented in the body of the text (more specifically in the results and discussion sections if you are following a scientific structure). The conclusion is meant to summarize and reflect on the evidence and arguments you have already presented, not introduce new ones.

The conclusion of a research paper has several key elements you should make sure to include:

• A restatement of the research problem
• A summary of your key arguments and/or findings
• A short discussion of the implications of your research

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

The way you present your research problem in your introduction varies depending on the nature of your research paper . A research paper that presents a sustained argument will usually encapsulate this argument in a thesis statement .

A research paper designed to present the results of empirical research tends to present a research question that it seeks to answer. It may also include a hypothesis —a prediction that will be confirmed or disproved by your research.

The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

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2.1: The Scientific Method

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Hypothesis Testing and The scientific Method

The scientific method is a process of research with defined steps that include data collection and careful observation. The scientific method was used even in ancient times, but it was first documented by England’s Sir Francis Bacon (1561–1626) (Figure \(\PageIndex{5}\)), who set up inductive methods for scientific inquiry.

Observation

Scientific advances begin with observations . This involves noticing a pattern, either directly or indirectly from the literature. An example of a direct observation is noticing that there have been a lot of toads in your yard ever since you turned on the sprinklers, where as an indirect observation would be reading a scientific study reporting high densities of toads in urban areas with watered lawns.

During the Vietnam War (figure \(\PageIndex{6}\)), press reports from North Vietnam documented an increasing rate of birth defects. While this credibility of this information was initially questioned by the U.S., it evoked questions about what could be causing these birth defects. Furthermore, increased incidence of certain cancers and other diseases later emerged in Vietnam veterans who had returned to the U.S. This leads us to the next step of the scientific method, the question.

Figure \(\PageIndex{6}\): A map of Vietnam 1954-1975. Image from Bureau of Public Affairs U.S. Government Printing Office (public domain).

The question step of the scientific method is simply asking, what explains the observed pattern? Multiple questions can stem from a single observation. Scientists and the public began to ask, what is causing the birth defects in Vietnam and diseases in Vietnam veterans? Could it be associated with the widespread military use of the herbicide Agent Orange to clear the forests (figure \(\PageIndex{7-8}\)), which helped identify enemies more easily?

Figure \(\PageIndex{7}\): Agent Orange drums in Vietnam. Image by U.S. Government (public domain).

Figure \(\PageIndex{8}\): A healthy mangrove forest (top), and another forest after application of Agent Orange. Image by unknown author (public domain).

Hypothesis and Prediction

The hypothesis is the expected answer to the question. The best hypotheses state the proposed direction of the effect (increases, decreases, etc.) and explain why the hypothesis could be true.

• OK hypothesis: Agent Orange influences rates of birth defects and disease.
• Better hypothesis: Agent Orange increases the incidence of birth defects and disease.
• Best hypothesis: Agent Orange increases the incidence of birth defects and disease because these health problems have been frequently reported by individuals exposed to this herbicide.

If two or more hypotheses meet this standard, the simpler one is preferred.

Predictions stem from the hypothesis. The prediction explains what results would support hypothesis. The prediction is more specific than the hypothesis because it references the details of the experiment. For example, "If Agent Orange causes health problems, then mice experimentally exposed to TCDD, a contaminant of Agent Orange, during development will have more frequent birth defects than control mice" (figure \(\PageIndex{9}\)).

Figure \(\PageIndex{9}\): The chemical structure of TCDD (2,3,7,8-tetrachlorodibenzo-p-dioxin), which is produced when synthesizing the chemicals in Agent Orange. It contaminates Agent Orange at low but harmful concentrations. Image by Emeldir (public domain).

Hypotheses and predictions must be testable to ensure that it is valid. For example, a hypothesis that depends on what a bear thinks is not testable, because it can never be known what a bear thinks. It should also be falsifiable , meaning that they have the capacity to be tested and demonstrated to be untrue. An example of an unfalsifiable hypothesis is “Botticelli’s Birth of Venus is beautiful.” There is no experiment that might show this statement to be false. To test a hypothesis, a researcher will conduct one or more experiments designed to eliminate one or more of the hypotheses. This is important. A hypothesis can be disproven, or eliminated, but it can never be proven. Science does not deal in proofs like mathematics. If an experiment fails to disprove a hypothesis, then we find support for that explanation, but this is not to say that down the road a better explanation will not be found, or a more carefully designed experiment will be found to falsify the hypothesis.

Hypotheses are tentative explanations and are different from scientific theories. A scientific theory is a widely-accepted, thoroughly tested and confirmed explanation for a set of observations or phenomena. Scientific theory is the foundation of scientific knowledge. In addition, in many scientific disciplines (less so in biology) there are scientific laws , often expressed in mathematical formulas, which describe how elements of nature will behave under certain specific conditions, but they do not offer explanations for why they occur.

Design an Experiment

Next, a scientific study (experiment) is planned to test the hypothesis and determine whether the results match the predictions. Each experiment will have one or more variables. The explanatory variable is what scientists hypothesize might be causing something else. In a manipulative experiment (see below), the explanatory variable is manipulated by the scientist. The response variable is the response, the variable ultimately measured in the study. Controlled variables (confounding factors) might affect the response variable, but they are not the focus of the study. Scientist attempt to standardize the controlled variables so that they do not influence the results. In our previous example, exposure to Agent Orange is the explanatory variable. It is hypothesized to cause a change in health (likelihood of having children with birth defects or developing a disease), the response variable. Many other things could affect health, including diet, exercise, and family history. These are the controlled variables.

There are two main types of scientific studies: experimental studies (manipulative experiments) and observational studies.

In a manipulative experiment , the explanatory variable is altered by the scientists, who then observe the response. In other words, the scientists apply a treatment . An example would be exposing developing mice to TCDD and comparing the rate of birth defects to a control group. The control group is group of test subjects that are as similar as possible to all other test subjects, with the exception that they don’t receive the experimental treatment (those that do receive it are known as the experimental, treatment, or test group ). The purpose of the control group is to establish what the dependent variable would be under normal conditions, in the absence of the experimental treatment. It serves as a baseline to which the test group can be compared. In this example, the control group would contain mice that were not exposed to TCDD but were otherwise handled the same way as the other mice (figure \(\PageIndex{10}\))

Figure \(\PageIndex{10}\): Laboratory mice. In a proper scientific study, the treatment would be applied to multiple mice. Another group of mice would not receive the treatment (the control group). Image by Aaron Logan ( CC-BY ).

In an observational study , scientists examine multiple samples with and without the presumed cause. An example would be monitoring the health of veterans who had varying levels of exposure to Agent Orange.

Scientific studies contain many replicates. Multiple samples ensure that any observed pattern is due to the treatment rather than naturally occurring differences between individuals. A scientific study should also be repeatable , meaning that if it is conducted again, following the same procedure, it should reproduce the same general results. Additionally, multiple studies will ultimately test the same hypothesis.

Finally, the data are collected and the results are analyzed. As described in the Math Blast chapter, statistics can be used to describe the data and summarize data. They also provide a criterion for deciding whether the pattern in the data is strong enough to support the hypothesis.

The manipulative experiment in our example found that mice exposed to high levels of 2,4,5-T (a component of Agent Orange) or TCDD (a contaminant found in Agent Orange) during development had a cleft palate birth defect more frequently than control mice (figure \(\PageIndex{11}\)). Mice embryos were also more likely to die when exposed to TCDD compared to controls.

Figure \(\PageIndex{11}\): Cleft lip and palate, a birth defect in which these structures are split. Image by James Heilman, MD ( CC-BY-SA ).

An observational study found that self-reported exposure to Agent Orange was positively correlated with incidence of multiple diseases in Korean veterans of the Vietnam War, including various cancers, diseases of the cardiovascular and nervous systems, skin diseases, and psychological disorders. Note that a positive correlation simply means that the independent and dependent variables both increase or decrease together, but further data, such as the evidence provided by manipulative experiments is needed to document a cause-and-effect relationship . (A negative correlation occurs when one variable increases as the other decreases.)

Lastly, scientists make a conclusion regarding whether the data support the hypothesis. In the case of Agent Orange, the data, that mice exposed to TCDD and 2,4,5-T had higher frequencies of cleft palate, matches the prediction. Additionally, veterans exposed to Agent Orange had higher rates of certain diseases, further supporting the hypothesis. We can thus accept the hypothesis that Agent Orange increases the incidence of birth defects and disease.

Scientific Method in Practice

In practice, the scientific method is not as rigid and structured as it might first appear. Sometimes an experiment leads to conclusions that favor a change in approach; often, an experiment brings entirely new scientific questions to the puzzle. Many times, science does not operate in a linear fashion; instead, scientists continually draw inferences and make generalizations, finding patterns as their research proceeds (figure \(\PageIndex{12}\)). Even if the hypothesis was supported, scientists may still continue to test it in different ways. For example, scientists explore the impacts of Agent Orange, examining long-term health impacts as Vietnam veterans age.

Scientific findings can influence decision making. In response to evidence regarding the effect of Agent Orange on human health, compensation is now available for Vietnam veterans who were exposed to Agent Orange and develop certain diseases. The use of Agent Orange is also banned in the U.S. Finally, the U.S. has began cleaning sites in Vietnam that are still contaminated with TCDD.

As another simple example, an experiment might be conducted to test the hypothesis that phosphate limits the growth of algae in freshwater ponds. A series of artificial ponds are filled with water and half of them are treated by adding phosphate each week, while the other half are treated by adding a salt that is known not to be used by algae. The variable here is the phosphate (or lack of phosphate), the experimental or treatment cases are the ponds with added phosphate and the control ponds are those with something inert added, such as the salt. Just adding something is also a control against the possibility that adding extra matter to the pond has an effect. If the treated ponds show lesser growth of algae, then we have found support for our hypothesis. If they do not, then we reject our hypothesis. Be aware that rejecting one hypothesis does not determine whether or not the other hypotheses can be accepted; it simply eliminates one hypothesis that is not valid (Figure \(\PageIndex{12}\)). Using the scientific method, the hypotheses that are inconsistent with experimental data are rejected.

Institute of Medicine (US) Committee to Review the Health Effects in Vietnam Veterans of Exposure to Herbicides. Veterans and Agent Orange: Health Effects of Herbicides Used in Vietnam . Washington (DC): National Academies Press (US); 1994. 2, History of the Controversy Over the Use of Herbicides.

Neubert, D., Dillmann, I. Embryotoxic effects in mice treated with 2,4,5-trichlorophenoxyacetic acid and 2,3,7,8-tetrachlorodibenzo-p-dioxin . Naunyn-Schmiedeberg's Arch. Pharmacol. 272, 243–264 (1972).

Stellman, J. M., & Stellman, S. D. (2018). Agent Orange During the Vietnam War: The Lingering Issue of Its Civilian and Military Health Impact . American journal of public health , 108 (6), 726–728.

Yi, S. W., Ohrr, H., Hong, J. S., & Yi, J. J. (2013). Agent Orange exposure and prevalence of self-reported diseases in Korean Vietnam veterans . Journal of preventive medicine and public health = Yebang Uihakhoe chi , 46 (5), 213–225.

American Association for the Advancement of Science (AAAS). 1990. Science for All Americans. AAAS, Washington, DC.

Barnes, B. 1985. About Science. Blackwell Ltd ,London, UK.

Giere, R.N. 2005. Understanding Scientific Reasoning. 5th ed. Wadsworth Publishing, New York, NY.

Kuhn, T.S. 1996. The Structure of Scientific Revolutions. 3rd ed. University of Chicago Press, Chicago, IL.

McCain, G. and E.M. Siegal. 1982. The Game of Science. Holbrook Press Inc., Boston, MA.

Moore, J.A. 1999. Science as a Way of Knowing. Harvard University Press, Boston, MA.

Popper, K. 1979. Objective Knowledge: An Evolutionary Approach. Clarendon Press, Oxford, UK.

Raven, P.H., G.B. Johnson, K.A. Mason, and J. Losos. 2013. Biology. 10th ed. McGraw-Hill, Columbus, OH.

Silver, B.L. 2000. The Ascent of Science. Oxford University Press, Oxford, UK.

Contributors and Attributions

• Modified by Kyle Whittinghill (University of Pittsburgh)

Samantha Fowler (Clayton State University), Rebecca Roush (Sandhills Community College), James Wise (Hampton University). Original content by OpenStax (CC BY 4.0; Access for free at https://cnx.org/contents/b3c1e1d2-83...4-e119a8aafbdd ).

• Modified by Melissa Ha
• 1.2: The Process of Science by OpenStax , is licensed CC BY
• What is Science? from An Introduction to Geology by Chris Johnson et al. (licensed under CC-BY-NC-SA )
• The Process of Science from Environmental Biology by Matthew R. Fisher (licensed under CC-BY )
• Scientific Methods from Biology by John W. Kimball (licensed under CC-BY )
• Scientific Papers from Biology by John W. Kimball ( CC-BY )
• Environmental Science: A Canadian perspective by Bill Freedman Chapter 2: Science as a Way of Understanding the Natural World

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The Committed Objectivity of Science and the Importance of Scientific Knowledge in Ethical and Political Education

Newton duarte.

1 Department of Psychology of Education, Faculty of Science and Languages, University of São Paulo State (UNESP), Av. Waldemar Orlando Paganelli, 117, Jardim dos Flamboyants, Araraquara, São Paulo 14805-286 Brazil

Luciana Massi

2 Department of Education, Faculty of Science and Languages, University of São Paulo State (UNESP), Araraquara, São Paulo Brazil

Lucas André Teixeira

Despite advances in discussions about the nature of science, there is still a paucity of discussion on the ontological dimension of science in science education research that makes it difficult to defend its content and teaching. In this article, the reasons for trusting science and science education are analyzed through three arguments. The first is that both the belligerent obscurantism and fake news of the ultra-right and the postmodern relativism of sections of the leftwing are connected to objective movements from the capitalist socioeconomic reality. The reestablishment of trust in science and its teaching requires an effort to understand the contemporary social contradictions, problems, and challenges. The second argument is that scientific knowledge does not need to abdicate objectivity in order to ground ethical and political positions. The third argument is that the socialization of scientific knowledge through school education is a necessary, albeit insufficient, condition for the ethical–political education of younger generations. The article concludes by stating that it is necessary to overcome the choice between an education that is supposedly neutral in political and ideological terms and an education that rejects the socialization of scientific knowledge in the name of respecting the multiplicity of culturally rooted voices from within the different oppressed groups present in today’s society.

Indeed, it is precisely because the findings of science are a constant threat to the spontaneous consciousness of everyday life sanctified by the authority of culture, that doing and teaching science had a subversive quality in my social milieu. It is the contra-conventional character of science that made it an ally of those of us engaged in an internal critique of some of the inegalitarian elements of our culture. The findings of modern "Western" science enabled us to show—with empirical evidence that was publicly testable—that no matter what the consensus of local community is, no matter what the powers that be claim, some social values and some facts of nature that these values are informed by, are wrong and must be rejected as false. (Nanda, 1997, p. 307).

Introduction

Research in science education has depended directly on advances in the historical, social, and philosophical understanding of science to improve its curricula and methodologies. Villani et al., ( 2010 ) trace the historical development of this research area in Brazil, in parallel with movements abroad, explaining this dependence. Historically, different theoretical and practical conceptions of science teaching were accompanied by different conceptions of science.

Initially, traditional teaching models were coupled with static and supposedly neutral views of science. Next, the technicist perspectives and teaching by discovery or rediscovery adopted premises that overvalued experimentation and the scientific method as teaching instruments, transmitting a vision of empirical and positivist science. For many researchers in the field, the constructivist models, as well as those of alternative conceptions and conceptual change, were accompanied by relative advances in discussions on the nature of science. They advocate an investigative approach based on raising hypotheses, sharing ideas among students, developing argumentation, and establishing collective consensus, thereby simulating the activities of the scientific community. This set of guidelines on the nature of science became consolidated, over time, into what is now called the “consensus view” (Lederman, 1992 ; Lederman et al.,  2002 ; Lederman,  2007 ). Lederman’s theoretical and investigative perspective on the nature of science identifies characteristics of the production of scientific knowledge in the form of lists, such as the famous Lederman Seven, which highlights its social and historical contextualization, its collective development, its empirical and theoretical character, among others. This view is currently criticized, in the sense of transcending lists, adopting a vision of science that considers, mainly through case studies, the economic, social, and political characteristics within the scientific community that impact its relationship with society and differentiate the specific characteristics of each field of knowledge as opposed to a generic reference to science (Allchin, 2011 ; Allchin et al. 2014 ; Clough, 2007 ; Hodson, 2014 ; Irzik and Nola 2014 ; Matthews, 2012 ; Schizas et al., 2016 ).

Although the area identifies these advances, there are many problems to be explored, among which we highlight those related to the ontological dimension of science. Consequently, issues such as the relationship between science and religion (Bagdonas & Silva, 2015 ; Mahner & Bunge, 1996 ) or even the position of the ethnosciences in science education (Zidny et al., 2020 ) remain unresolved.

In this context, the open, democratic and mutually critical debate in the articles that compose the special issue of Science & Education, organized by Matthews ( 2009 ), gains special relevance, in which the relations between science, worldviews, and education are discussed from different perspectives. We agree with Irzik and Nola ( 2009 ), when they state that “The current literature tends to characterize worldviews too narrowly. As we will see, worldviews attempt to answer a range of important questions about life and the world, not all of them religious” (p. 730). We also agree that “science has worldview content” and that this fact “has important implications for science education” (p. 730). Matthews ( 2009 ) expressed his expectation that this particular issue of Science and Education contributes “to a more refined and sophisticated understanding of the interplay between worldviews and science; and indicates how scientific education can contribute to the formation of more informed, intelligent, and responsible worldviews, and thus to a better and more humane culture” (p. 651). It is this same spirit that motivates us to present our contribution to the search for answers to the central question of this special issue: Why trust in Science and Science Education?

As such, in this article, based on historical-dialectical materialism and the ontological and gnosiological dimensions of science, we use three arguments to propose that analysis of the reasons to trust in science and its teaching should consider the objective movement of capitalist society in recent decades: the dialectical unity, in scientific knowledge, of objectivity and ethical–political positioning, which we call committed objectivity and, as a result, the necessary socialization of science through school towards an ethical–political education.

The first argument is that the belligerent obscurantism 1 and fake news of the ultra-right, in addition to postmodern relativism and the denial of scientific knowledge’s objectivity, are expressions, on the level of ideas, of objective movements from the capitalist socioeconomic reality. Thus, the reestablishment of trust in science and science education needs to be seen as part of a larger effort to understand the contradictions, problems, and challenges that capitalist society poses today to humanity as a whole. It is not enough, however, to simply state capitalism’s limitations in overcoming major social problems; as Foster ( 2019 ) pointed out, we need to seek answers to the question: what next?

The second argument is that our choice need not be limited to two options: the anti-scientific attitude sustained by certain worldviews or the defense of scientific knowledge’s objectivity as something that implies political and ideological neutrality. Scientific knowledge does not need to abdicate objectivity in order to substantiate ethical and political positions in the face of the problems that afflict humanity today. The fallible and historically situated character of scientific knowledge does not diminish its importance in understanding natural and social reality and in developing plans for transformative action. The limits, gaps, inconsistencies, and contradictions present in scientific knowledge are surmounted in the historical process of production, dissemination, and incorporation of this knowledge into people’s thinking, practice, and life. Believing that it is possible for science to progress in the production of objective knowledge does not in any way imply that science possesses the absolute, definitive, and unquestionable truth. As Sayer ( 2010 , p. viii) explains:

Of course, social science, like natural science, cannot provide 'a royal road to truth'. No matter how well chosen our methods may be, our ways of thinking may still let us down. Knowledge is fallible, that is, capable of being mistaken about its object. The truth or adequacy of our ideas is a practical matter, and something that we can try to improve. (...) the nature of the world is largely independent of an observer's ideas about it, and it is this that explains both the adequacy and fallibility of our knowledge, such as it is.

In the same way, the fact that science is embedded in social relations that involve struggles, conflicts, and economic and political power, as well as disputes between conflicting worldviews, does not imply the impossibility of knowing what reality is, the internal processes that move it, and the possible directions that these processes may take (Löwy, 1987 ).

Similarly, our third argument is that the democratization of scientific knowledge’s mastery, that is, its socialization through school education, is a necessary albeit insufficient condition for the ethical–political education of younger generations. In this case, it also seems to us to be possible and necessary to go beyond the choice limited to two options: a politically and ideologically neutral education that aims to bring scientific knowledge to all, or an education that rejects the socialization of scientific knowledge in the name of respecting the multiplicity of culturally rooted voices from within the different oppressed groups present in today’s society. We believe that the argument proposed by Wheelahan ( 2010 , p. 145) regarding theoretical knowledge in general is valid when applied to the teaching of scientific knowledge in schools:

Access to theoretical knowledge is an issue of distributional justice because society uses it to conduct its conversation about what it would be like. Society uses theoretical knowledge to think the unthinkable and the not-yet-thought, and this makes such knowledge socially powerful and endows it with the capacity to disrupt existing power relations. It plays this role because it is society's collective representations about the social and natural worlds, and we use it to access these worlds to understand how they are constructed, their process of development and how they can be changed.

In the following three sections we develop our argument.

Science and Its Teaching as Part of the Objective Movement of Capitalist Society

There is nothing new about the observation that every time the contradictions of capitalism become more acute and more evident, cultural changes occur in the direction of moving away from the search for the production and dissemination of objective knowledge about society. Georg Lukács ( 1980 ), in his 1938 essay entitled “Marx and the problem of ideological decline,” argued that from the second half of the nineteenth century onwards, the contradiction between the need for objective knowledge to help solve problems arising from capitalist economic production and the equally necessary diffusion of ideas that prevent people from objectively knowing the society of which they are a part has become increasingly problematic. In the sciences that study society, the ideological struggle against truth shows itself in a more immediately visible way. However, this does not mean that it does not also exist in the natural sciences. This has become particularly evident today through the ideological disputes that have brought to the forefront, in the international media, pseudoscientific explanations that reject and delegitimize scientific evidence that certain productive activities have decisively contributed to global warming and consequent climate change.

Although there is scientific evidence proving the negative impacts on nature generated by the capitalist mode of production and reproduction of social materiality, the legitimacy of this knowledge and its dissemination are hindered by very strong economic and political interests:

Since science provides the basis for the most legitimate discourses in industrial society, those who are questioned by it tend to react by supporting arguments that also have to be presented as scientific, even if they are not. On almost every occasion in recent decades when powerful economic interests are confronted, this has led to the development of a kind of pseudoscientific controversy, whose purpose is to ‘keep the debate alive’ in order to ‘delay’ the approval of that which might hurt those interests. (Leite, 2015 , p. 659)

Science, as a result of ideological disputes, needs to be questioned as a type of knowledge that, in order to reveal the truth, must maintain a constant critical position in relation to the economic, political and cultural interests that limit its objectivity. The contradictory movement of society implies considering various pseudoscientific mechanisms sustained by media apparatuses and dictatorial systems, which relativize scientific knowledge by valuing, controlling, and maintaining ideologies that obscure access to the truth. However, contrary to first impressions, this does not mean that science should remain aloof, distant, and omissive in relation to social problems. The freedom to pursue the truth is not increased by embracing an illusory belief in social disengagement of the practice of producing scientific knowledge.

Over the last decade, the worldwide spread of belligerent obscurantism is a phenomenon that has its origins in the crisis of capitalism that, in the 1970s, put an end to the economic cycle of expansionist growth from the post-World War II period. It was not by chance that, in that same decade, the dictatorship implanted in Chile, under the leadership of General Augusto Pinochet, adopted an economic policy directly guided by Milton Friedman and the Chicago Boys. It was also no coincidence that in 1979, Margaret Thatcher was elected as prime minister of England and Ronald Reagan became president of the USA in 1981. In the same period, postmodernism became a major academic and cultural fad, proclaiming the end of modernity, the emergence of a new society, and a new human condition. Smith ( 1994 ) questions the premise that undeniable social changes produced a post-capitalist society and a postmodern condition. He argues that “the rise of postmodernist thought coincided with a significant conjunctural transition in the history of twentieth-century capitalism; but the ‘restructuring’ that we are now witnessing changes nothing essential about the laws of motion of capitalism” (p. 236). The disdain shown by most proponents of postmodernism on the question of relations between society’s economic base and the political, ideological, and cultural superstructure can be interpreted as the flipside of the neoliberal thesis on the autonomy of economics from politics. In turn, this separation between, on the one hand, the contradictions that move the economic base and, on the other, the social activities at the superstructural level amounted to a denial of the possibility for objective and rational knowledge regarding the movement of social reality as a whole.

Wainwright ( 2018 ) explains that one of the arguments employed in favor of neoliberalism by one of its main theorists, the Austrian Friedrich August von Hayek, is that one should let the market spontaneously determine the directions of society because human beings are unable to know and understand the social totality. As Mackenzie et al. ( 2014 ) point out in their critical analysis of postmodern assertions incorporated into the field of Science Education, postmodernism is emphatically opposed to any theory that aims to explain reality as a totality. The localism of the post-modern conception of knowledge and the centrality of tacit knowledge in the neoliberal view of social practice converge to spread an epistemological perspective that denies the possibility for distinguishing between objectivity and subjectivity. Segal ( 2001 ), explaining the central ideas of Heinz Von Foerster’s constructivism, explains that:

Von Foester - cybernetician, mathematician, physicist, and philosopher - claims that we CONSTRUCT or INVENT reality rather than discover it. He suggests that we fool ourselves by first dividing our world into two realities - the subjective world of our experience, and the so-called objective world of Reality - and then predicating our understanding on matching our experience with a world we assume exists independently of us. (Segal, 2001 , p. 13)

In the educational field, postmodern relativism and anti-realism resulted in a reinvigoration and renewal of progressive pedagogies. This is not a new problem in education: a direct identification between progressive political positions and the so-called progressive pedagogies, on the one hand, and between conservative political positions and so-called traditional education, on the other. Entwistle ( 1979 ) showed that Antonio Gramsci (1891–1937) had already criticized this kind of identification: “In the light of Gramsci’s analysis, it is arguable that we need to reconsider the conventional equation of traditional didactic schooling with political authoritarianism, and the progressive education with democracy” (p. 3). In Gramsci’s time, the fascist regime carried out educational reform inspired by progressive pedagogies. At the end of the twentieth century, many neoliberal governments implemented reforms of educational systems and school curricula also inspired by new progressive pedagogies such as constructivism, multiculturalism, problem-based learning, and competence-based pedagogy. In the spirit of postmodernism, the curriculum reforms of the late twentieth and early twenty-first centuries have operated with “a pastiche of theories and approaches that draw from sometimes opposing theoretical premises, which are then blended by processes or recontextualization” (Wheelahan, 2010 , p. 134).

The advance of the new ultra-right in many countries, aided by fake news, conspiracy theories, and belligerent obscurantism, has triggered the alarm bell for several social and educational groups that had been identifying epistemological relativism with progressive political positions. For example, faced with the denial of global warming, the holocaust and, in the case of Brazil, the crimes committed by the military dictatorship from 1964 to 1985, a sizeable portion of the left had to review the association between the idea of truth and positivism. In fact, this had been foreseen by Hobsbawn ( 1997 , p. VIII) when he stated that:

relativism will not do in history any more than in law courts. Whether the accused in a murder trial is or is not guilty depends on the assessment of old-fashioned positivist evidence, if such evidence is available. Any innocent readers who find themselves in the dock will do well to appeal to it. It is the lawyers of the guilty ones who fall back on post modern lines of defense.

In this context, science and its teaching, as part of the objective movement of capitalist society, play an important social role in education through the possibility of access to objective knowledge. The non-relativization of this type of knowledge can contribute as an instrument that enables the verification of truth in benefit of a world conception that does not imprison the human being, but promotes freedom in the life of individuals. As such, objectivity and subjectivity are united in the historicity of the social process for achieving freedom, since knowledge of nature in its objective existence facilitates the conscious activity of mastering natural processes.

The realization that epistemological relativism is an expression of the objective movement of capitalist society in recent decades underscores the importance of focusing debate on the need to restore trust in science and science education. To be reliable, science cannot absent itself from the ideological struggle that conceals the economic interests that sustain social inequalities. Its gnosiological dimension, as the material expression of the world’s conception, cannot confuse truth with the political and ethical neutrality of an unquestionable science, but rather consider the ontological dimension involved in the search for objectivity. This means that science, as a result of antagonistic economic relations, needs to reveal the contradictions through the involvement of science, scientists, teachers, and students with the social problems and conflicts that mark each society and each era of human history.

In Defense of the Committed Objectivity of Science

Discussion about the objectivity of scientific knowledge has been marked by two false assertions: (1) the positivist syllogism that if there is no neutrality there can be no objectivity; (2) the multiculturalist premise that the fact that the origin of all knowledge is situated historically, geographically, and culturally, as well as influenced by economic and political interests, makes objectivity impossible and entails, among other things, the denial of all knowledge’s universal value. Thus, we realize that objectivity has historically been contested by different hegemonic epistemological perspectives.

The first assertion, namely, that because knowledge is not neutral it cannot be objective either, is a consequence of a positivist syllogism whose major premise is that “there is only objective knowledge where there is neutrality” (Saviani, 2011 , p. 49). The Brazilian educator Dermeval Saviani argues that this association confuses ideological elements, neutrality, with gnosiological aspects, objectivity. It is worth historically situating this author’s text in the context of the debates that took place in Brazil when it was first published.

In the first half of the 1980s, when democratic forces in Brazil were fighting for the end of the dictatorship that had begun in 1964, there was a perspective in the field of critical Brazilian educational thought that tended to identify the defense of knowledge’s objectivity with positivist epistemology and, consequently, with the technicist vision of education adopted by the military dictatorship. Since the technicist conception postulated that education should adopt the assumption that the objectivity of scientific knowledge required its neutrality, many educators who opposed educational technicism believed that it was necessary to oppose the idea that knowledge can be objective. It was in this context that, in 1983, Saviani ( 2011 ) published a text that was later transformed into a book chapter in which the author presented what he called: first approaches to critical historical pedagogy . In this text, the author called attention to the positivist trap in which critical educators were caught, and that they were throwing the baby out with the bathwater by denying knowledge’s objectivity and claiming it was necessary to emphasize non-neutrality. According to Saviani ( 2011 ), certain sociopolitical interests oppose objectivity, while others not only do not do so but, on the contrary, demand the objectivity of knowledge. As such, the author argued that schools, from the perspective of their engagement in the pursuit of the democratization of Brazilian society, should strive towards universalizing the mastery of objective knowledge about nature and society.

Returning to the discussion regarding objectivity, Löwy ( 1987 ) analyzes the sociology of knowledge by critiquing the various epistemological currents and their relations to the attempts at scientific objectivity that emerged within positivism, historicism, and Marxism. Initially, he highlights the effort to achieve objectivity through the “good will” that was present in the positivist ideology of Comte and Durkheim, for example. Löwy ( 1987 ) compares this effort to the children’s story of the Baron Munchausen, who manages to escape from a swamp by pulling himself out by his own hair. In these cases, the identification between objectivity and neutrality remains in the ideological realm, since the positivist effort is in the sense of erasing the interested character of knowledge. Löwy ( 1987 ) also analyzes other attempts, such as Karl Popper’s, who defends the existence of an institutional objectivity of science. This objectivity would be achieved by aspects of scientific knowledge production, such as freedom of criticism, a common language, the public nature of the method and scientific institutions. Thus, Popper does not resolve the problem, but rather transfers it to a higher level (Löwy, 1987 ). There is a relative advance, as the discussion becomes gnosiological, supporting objectivity in methods and institutions. Addressing historicism in its conservative/reactionary and relativist facets, Löwy ( 1987 ) considers the contributions and limitations of Karl Mannheim’s thinking on the need for a critical scientific self-awareness, requiring a new objectivity of scientific knowledge. Although marked by a “sophisticated positivist” relativism, this moment is, according to the author, one of the most fruitful aspects of the historicist tradition for modern sociology, since it problematizes social-scientific objectivity. However, these elements have been constantly manipulated, showing themselves to be fragile in terms of theoretical tools that enable scientific knowledge to be more developed and engaged in its ability to explain reality. Presenting possibilities for advances in a dialectical perspective, Löwy ( 1987 ) draws on Lukács and Goldmann to overcome the relativistic impasse of a contemplative science and purely ethical action through the engaged character that indissolubly unites science and class consciousness, knowledge, and praxis. Therefore, it evinces the interested character of all natural and social scientific knowledge, seeing as class consciousness can permit greater or lesser understanding of reality, depending on the progressive or reactionary role a class plays at a given historical moment.

Löwy ( 1987 ), Lukács ( 2012 ), Saviani ( 2011 ), and Wheelahan ( 2010 ) argue in different ways that the objectivity of knowledge is not necessarily rendered impossible by the fact that production activities are embedded in power relations.

If the world exists objectively and is not a construct of our minds or discourse, then the purpose of knowledge is to understand that objective reality, even if our knowledge is always partial, socially mediated and marked by the social conditions under which it was produced, and is fallible as a consequence. (Wheelahan, 2010 , p. 10)

The fact that scientific knowledge is embedded in the fabric of social power relations is also not an argument for not democratizing access to it. The very decision to democratize scientific education or not is, in itself, an ethical and political position.

Knowledge will inevitably bear the marks of its production because it is socially produced, reworked and modified by communities of knowledge producers, and the state of our knowledge must at any time be regarded as a work-in-progress. However, while knowledge will bear the marks of power and privilege that is not all that it does. Arguments about distributional justice are concerned with ensuring equitable access to knowledge as a work-in-progress so that the less powerful can contribute to the shape and nature of knowledge and this includes participating in defining what is important in knowledge fields. (Wheelahan, 2010 , p. 09)

Lukács ( 2012 ), in his ontology, states that reality exists and can be known objectively. He argues that the natural sciences perform a process of disanthropomorphism, that is, they remove human aspects from the explanation of natural phenomena. One of the aspects of disanthropomorphization is the elimination, in the explanation of natural phenomena, of any remnant of teleology, that is, purely natural processes are not driven by purposes, but by causalities. In the case of the social being, reality is driven by a dialectical relationship between causality and teleology. However, this does not mean a separation between nature and society, which would be impossible, but only the rejection of the anthropomorphic universalization of teleology, which is a specific characteristic of human activity that produces the movement of causalities to achieve certain ends. This discussion shows that objectivity cannot be fully reached, in the sciences of nature and society, without understanding reality as a totality. For Lukács ( 2012 ), science has two possibilities for development: (1) to substantiate a conception of the world based on a materialist, historical, and dialectical ontology; or (2) to fulfill a merely instrumental and technical role, being more or less conscious of market logic. In this second restrictive and contradictory focus, objectivity is limited to technique and avoids as much as possible making extrapolations in terms of worldview. This second position can be exemplified by a passage from Life of Galileo (Brecht, 2015 , p. 97) in which Cardinal Bellarmin says: “We must move with the times, Barberini. If new star charts based on a new hypothesis help our mariners to navigate, then they should make use of them. We only disapprove of such doctrines as run counter to the Scriptures.” Lukács ( 2012 , p. 38) cites this passage to illustrate the cynicism of the two-truth theory that admits the advances of science for practical uses that serve the interests of the ruling class while rejecting out of hand any implication of these advances that might clash with the dominant ideology. The development of the productive forces by the bourgeoisie could not be stopped, so science became limited to a technique fragmented from its ontological dimension. Thus, the natural sciences have a core of objectivity that maintains its validity when separated from the logic of capitalist production. Capitalism needs the advance in knowledge of nature, although it has to curtail the diffusion of knowledge, which still needs to be the privilege of specialists.

In France and England the bourgeoisie had conquered political power. From that time on, the class struggle took on more and more explicit and threatening forms, both in practice and in theory. It sounded the knell of scientific bourgeois economics. It was thenceforth no longer a question whether this or that theorem was true, but whether it was useful to capital or harmful, expedient or inexpedient, in accordance with police regulations or contrary to them. In place of disinterested inquirers there stepped hired prize-fighters; in place of genuine scientific research, the bad conscience and evil intent of apologetics. Still, even the importunate pamphlets with which the Anti-Corn Law League, led by the manufacturers Cobden and Bright, deluged the world offer a historical interest, if no scientific one, on account of their polemic against the landed aristocracy. But since then the free-trade legislation inaugurated by Sir Robert Peel has deprived vulgar economics even of this, its last sting. (Marx, 1990 , p. 97)

As we have shown, being socially engaged, and therefore not neutral, does not mean that scientific knowledge is not objective. Löwy ( 1987 , p. 104—author’s italics) indicates that “bourgeois ideology does not imply the negation of all science, but the existence of barriers that restrict cognitive visibility”. Since knowledge is never on the sidelines of ideological struggle, it has consequences for worldviews and class struggle.

Some postmodern perspectives justify cultural relativism affirming that the available knowledge we have is that which was imposed by the victors. As such, in order to fight for emancipation, they claim that there is no objective knowledge. The reduction of knowledge to a struggle between narratives whose legitimacy is assigned only by power relations had the effect predicted by Hobsbawm (1997), that is, it has served the interests of those who need to conceal the truth. The extreme right has made intense use of this strategy to “rewrite” history, denying the Holocaust, the dictatorship in Brazil, global warming, etc. In opposing postmodern relativism, we affirm that there are political and economic interests that historicize scientific knowledge, but they do not directly imply the non-objectivity of this knowledge. These interests are associated with the objectivity of the material world and, at the same time that science is influenced by the objective undertakings of the class that holds economic power, generating, among other things, the over-specialization of scientific knowledge with a view to its instrumental economic use, this process does not fail to produce objective advances in the sciences. Dialectics is necessary precisely to understand this historical movement of the sciences in its contradictory character, without falling into Manichaeism. An example in this sense is the scientific research aimed at the production of pharmaceuticals. The powerful economic interests that drive this research are well known. It is also known that these interests can lead to processes of induction of diagnoses and treatments not necessarily beneficial to patients, but that serve the interests of industry investors. This requires a permanent critical vigilance in relation to the knowledge produced in the area, but this can only be done with the resources of science itself and not through campaigns that spread prejudice against science, as is the case of anti-vaccine propaganda.

An example of this complexity can be seen in a recent episode involving the dispute between laboratories over the launch of the Covid-19 vaccine. According to an article by Feuerstein ( 2020 ) on the website STAT News , “There are currently nine vaccine candidates in Phase 3 trials. AstraZeneca's is the first Phase 3 Covid-19 vaccine trial known to have been put on hold.” One investor, during a private conference call with investors on Wednesday (September 9, 2020), reported that Pascal Soriot, the CEO of the British-Swedish multinational pharmaceutical and biotechnology company, AstraZeneca, said:

were intended to reassure investors that the company was taking the possible vaccine safety event seriously, and to reverse any damage to the company's stock price. "A vaccine that nobody wants to take is not very useful," said Soriot. To date, AstraZeneca's public statements on the pause have been sparse with details. For instance, the company has not publicly confirmed that this is the second time its trials have been stopped to investigate health events among participants. (Feuerstein, 2020 , September 9)

The repercussion of this episode weeks later, on Nov. 27, 2020, when “Astra shares fell 0.8% by 8:57 a.m. in London trading Friday, bringing the decline this week to about 8% amid questions about trial results” (Ring & Paton, 2020 , November 26).

The contradictory interests between objective knowledge and economic power relations underscore the trust that can be placed in science in the face of human need. As Löwy ( 1987 ) points out, they restrict cognitive visibility. The population, in turn, is left to fend for itself, on a path that increasingly compromises access to the knowledge needed to build an objective view of nature, making room for conceptions that anthropomorphize natural phenomena (Lukács, 2012 ), as we have seen with creationism, flat-earthers and anti-vaccine movements. The absence of access to scientific knowledge causes fear, rejection, and uneasiness in relation to this prophylactic procedure, as indicated by Succi’s studies (2018). She shared data from a survey carried out in 2016, entitled, The State of Vaccine Confidence 2016: Global Insights Through a 67-Country Survey (Larson, et al., 2016 ), to assess people’s perceptions about the safety, efficacy, and importance of vaccines, as well as compatibility with their religious beliefs, interviewing 65,819 people in 67 countries. The results of the survey point out that:

The determinants of vaccine refusal/hesitancy are complex and can be attributed to the confluence of several sociocultural, political, and personal factors; doubts about the actual need for vaccines, concerns about vaccine safety, fear of possible adverse events, misconceptions about the safety and efficacy of vaccines, concerns over a possible “immune system overexposure,” past negative experiences with vaccines, mistrust of the seriousness of the vaccine industry and the healthcare system, heuristic thinking, and philosophical and religious issues may be involved. (Succi, 2018 , p. 576)

The determining factor that appears as the main cause of this context is “The access to information (and misinformation) on vaccines released by the media influences decision-making on whether or not to vaccinate” (Succi, 2018 , p. 576).

Both the hesitations over vaccines and the economic disputes over laboratories also highlight the trust one can have in science education. The scientific knowledge accumulated by biology since the mid-nineteenth century through Darwinian theory seems to have no space as knowledge that enables a disanthropomorphized reflection of reality. We still experience debates about the space for creationism or evolutionism in schools, and there are authors who defend the coexistence of both views in science classes (Sepulveda and El-Hani, 2004 ). Science education, understood as the space for pedagogical work with fundamental concepts of the theory of evolution, seems not to affect the class interest of working populations, as the promotion of a materialist, historical, and dialectical conception of the world in the relationship between nature and society. Basic principles of the evolutionist theory, such as variability, genetic background, and selection, still remain as a valid core to explain sanitary, infectious, and prophylactic principles, and could reveal the truth through a scientific knowledge committed to the exploited classes, especially because they are the most affected and exterminated by epidemics resulting from the way of producing life in capitalism.

Still on Darwinism, considered one of the most important revolutions in science, it is possible to identify several disengaging distortions that, as indicated above, do not invalidate its valid core. Jair Bolsonaro’s Brazil has turned us into a factory of coronavirus variants, proving the authenticity of the theory of evolution on a daily basis. In a human cell, over a 24-h period, coronavirus can produce up to 100,000 copies of itself (Ansede, 2020 , April 03). Each replication of the virus can create several variants, among which some are better adapted to our organism and to the virus’ survival. Despite copious evidence to prove this theory, it is not safe from various pseudoscientific distortions. One of the best known cases is Social Darwinism, which has been constantly revived in history to justify social inequalities as if they were natural. Lukács ( 1981 ) analyzes race theory, from its beginnings in the eighteenth century in Gobineau’s Racial Theory Argument, through Social Darwinism and up to the ideas of Chamberlain as the Founder of Modern Racialism. The author points out that biologism, employing disfigured and deformed biological concepts, has always been the basis of reactionary ideological trends.

Like Lukács ( 1981 ), Saviani ( 2011 ) shows how the bourgeoisie sometimes denies, other times claims—depending on the role it assumes in history—an ideological defense of privileges based on equality/inequality among men and women. Hence, albeit without scientific substantiation, the race theory resurfaces historically, seeking arguments in the scientific theories in force and counting on the backing of scientists. The concept of race has existed since the eighteenth century, but it was in the nineteenth century that it gained more strength as a category used to differentiate human beings and hierarchize their physical, emotional, and cognitive qualities, justifying various forms of exploitation. Gobineau, according to Lukács ( 1981 ), produced the first work that reconstructed the entire universal history based on race theory, reducing all crises, conflicts, and historical and social differences to races. But only with Social Darwinism did this theory manage to assume a modern character of scientificity (Lukács, 1981 ). As such, the theory of evolution, which represented a true revolution in the conception of the world, “became the cliché” capable of unifying the sciences of nature and society (Lukács, 1981 , p. 683). The strength of this ideology refers to its ability to no longer deny the perverse aspects of capitalism, but to affirm and justify them as immutable, natural, and eternal (Lukács, 1981 ). Finally, Chamberlain develops race theory by arguing that the value of science lies in its methodological applicability rather than its truth content (Lukács, 1981 ). Thus, as we observe in the context of maritime expansion, the theory of evolution becomes a technique stripped of its ontological character and its ability to explain the world (Lukács, 1981 , 2012 ).

If science is reduced to an instrumental function, scientific knowledge will be considered important or not for school curricula depending on the assessment of its usefulness in adapting individuals to the status quo of the market society. In circumstances where scientific knowledge can go beyond this adaptive function and produce questioning in relation to dominant worldviews rooted in common sense, all kinds of supposedly epistemological, pedagogical, ethical, and cultural arguments are raised so that this knowledge is not inserted in school curricula, or is removed from them. Feeling helpless, the population resorts to tradition, family life history, friends’ opinions, and pseudoscientific information to the detriment of historical and systematized knowledge. Discussions about the relevance of science in school curricula cannot, therefore, separate epistemological and pedagogical issues from the historical analysis of science as a permanent and dialectical process of approaching the truth. As Saviani ( 2011 , p. 51) states: “Historicization, then, instead of denying the objectivity and universality of knowledge, is the way to rescue them.”

The historicity of knowledge does not only mean that it is transformed throughout history and that knowledge taken as true in a given social and historical context may later be considered partially true or even as entirely false. Likewise, to assume that the process of pursuing the truth is historical does not imply an attitude of total relativization of said truth. It is a process that makes advances, marked by contradictions, struggles, gains, and setbacks, which allow us to affirm that certain knowledge is closer to the truth than others.

Marx’s second thesis on Feuerbach, regarding the relationship between the objective truth of thought and practice, is well known:

The question whether objective truth can be attributed to human thinking is not a question of theory but it is a practical question. Man must prove the truth, i.e., the reality and power, the this-worldliness of his thinking in practice. The dispute over the reality or non reality of thinking which isolates itself from practice is a purely scholastic question. (Marx, 1998 , p. 572)

It turns out that this thesis can be misunderstood if one does not distinguish between the everyday practice of individuals and social practice throughout history. In other words, one must distinguish the relationship between thought and action in the everyday life of individuals from the relationship between theory and practice in the social evolution of science and philosophy. Heller ( 1984 , p. 203) states that everyday knowledge is always opinion, doxa , that is, it is never episteme (science or philosophy) and argues that doxa is verified in practice, but it is not about social practice as a whole but rather the immediate utilitarian practice of everyday life:

As we know, doxa is inseparable from practical activity: it is in practical activity and nowhere else that doxa is verified. But this does not refer to praxis as a whole or even to a major segment of it; it is always in certain types of particular concrete and successful action that doxa is verified. (Heller, 1984 , p. 203)

The relative or absolute, particular or universal character of scientific truths is demonstrated by praxis throughout human history. Praxis, in this sense, is not synonymous with practical activity as distinct from theoretical activity, but is the historical human activity of transforming the world and creating the human world:

In its essence and generality, praxis is the exposure of the mystery of man as an onto-formative being, as a being that forms the (socio-human) reality and therefore grasps and interprets it (i.e. reality both human and extra-human, reality in its totality). Man's praxis is not practical activity as opposed to theorizing; it is the determination of human being as the process of forming reality. (Kosik, 1976 , p. 137)

But this historical understanding of the advancement of scientific knowledge requires a vision that recognizes the existence of development in history, but driven dialectically by contradictions and struggles that can often produce setbacks, stagnation, and even irrecoverable losses. Sayers ( 1985 ) discusses the relations between the progress of knowledge and the nature of truth based on the philosophical reference of Hegelian-Marxist dialectics. In this context, he argues that observation of the existence of historical progress in knowledge does not imply a teleological view of history:

I should make it clear, however, that when I say that the development of knowledge involves progress, I do not mean an inevitable or necessary progress towards a predetermined end. Indeed, I would specifically deny this. For it seems all too possible that humanity will destroy itself, or come so near to doing so as to set the course of history back catastrophically. Unlike the nineteenth century idealists, I am not suggesting that there is a teleology, immanent either in ideas or things, driving them towards a predestined goal. Nevertheless, the development of knowledge, as a matter of fact, has a progressive form. If one looks at the course of history, a pattern of progress is apparent. Or, to put it in a less empiricist manner: the development of knowledge can be adequately and coherently comprehended only in terms of the view that it has involved progress. (Sayers, 1985 , p. 164)

This endless historical approach to truth is analyzed by Lukács ( 1978 ) by reference to two decisive issues for the dialectical method in Marx. One is the dialectic between concrete and abstract in the process by which thought seeks to explain the complexity of concrete reality by taking two paths:

from the concrete reality of singular phenomena to the highest abstractions, and from these again to concrete reality, which - with the help of the abstractions - can now be understood in an ever more approximately exact manner. Here it must be stressed, especially for our considerations, precisely the approximative character of science. (Lukács, 1978 , p. 103)

The other question refers to the dialectic between singularity, particularity, and universality. For Lukács ( 1978 ), science is always in search of universal laws, but with the advance of knowledge that which at one time was interpreted as a universal law is subsequently embedded in broader theories, thus becoming a particular manifestation of laws provisionally deemed universal. Furthermore, according to Lukács ( 1978 ), the scientific theoretical elaboration of new universalities reveals new previously unknown particularities whose study will produce increasingly enriched comprehension of universalities.

But neither the relations between the concrete and the abstract nor the relations between singular, particular, and universal exist only as movements of thought. They exist first and foremost in objective reality itself, and understanding the historical relations between theories and reality requires that we do not lose sight of the question involving the relations between theory and practice, provided that practice is not confused with everyday utilitarianism and theory with pragmatic thinking. Sayers ( 1985 , p. 179) quotes Hegel who stated that “the truth is whole,” but Sayers adds that “the whole involved in knowledge is firstofall primarily real and practical in character.” The universality of knowledge advances historically with the widening and deepening of social practice as a whole:

The increasing system and order of our ideas is based upon and reflects an extension and intensification of our practical activity in the world. In the course of historical development, we have extended not only our theoretical understanding of the world; for along with this widening and deepening of scientific understanding, has gone the development of new techniques and practical abilities, in relation to an increasing range of natural forces and phenomena. A deeper and more extensive vision and understanding of the world goes hand in hand with a wider and more intensive practical relationship to reality. Theory and practice form a necessary unity. (Sayers, 1985 , p.179)

Therein lies the necessarily engaged character of scientific objectivity. The production and also the diffusion of scientific knowledge is part of human practice in its totality, that is, the historical effort of humanity to bring about transformations of the natural and social world towards the construction of conditions increasingly favorable to the dignity of life. Oftentimes, science has been and continues to be used to the contrary, that is, in the destruction of nature and human life itself, the exploitation and domination of human beings, generating alienating social processes that subjugate and alienate humanity itself. However, this does not invalidate the thesis defended here that the objectivity of scientific knowledge is necessary in facing the great challenges posed to humanity. The fact that science is, in certain social circumstances, directed to destructive and dehumanizing ends does not prove the human incapacity to master science. It merely shows that we can make ill-judged decisions about the destination we assign to the objective processes we set in motion. To conclude from these poor decisions that science contains an intrinsically dehumanizing rationality is to adopt a fetishistic view of science, attributing to it powers that it does not have.

For those who are used to considering scientific objectivity as synonymous with axiological and political neutrality, the term committed objectivity will sound like a paradox, as with Kelly’s ( 1986 ) use of the term committed impartiality. The difference, however, is that Kelly argues that the paradoxical character of the term committed impartiality in the positioning of teachers regarding controversial issues in school does not imply incoherence, whereas by employing the term committed objectivity, we do not intend to indicate a paradox because we believe that, in this case, it does not exist. As we have tried to show, the historical quest of science for objectivity is an ethical and political engagement with the social horizon of humanity’s emancipation as a whole.

Guiding science to the humanization of life and making scientific objectivity an engagement for the formation of a worldview geared towards the emancipation of all human beings from the many forms of exploitation and domination that currently prevail in social relations entails science no longer serving the restricted interests of political and economic elites, instead becoming the heritage of all humanity. A part of this process in democratizing science must be accomplished through education.

The Socialization of Science as Part of the Ethical–Political Education of Younger Generations

According to Moore and Muller ( 1999 ), conceptions about school knowledge and curriculum have been influenced since the 1970s by the English current of the New Sociology of Education, which questioned the objectivity of knowledge. In the 1980s and 1990s, that questioning intensified through the influence of post-modern and post-structural relativism. This broad and heterogeneous current of thought, besides spreading a fundamentally negative view of scientific knowledge, decisively contributed to the incorporation, through common consensus among educators, of the idea that school should focus on everyday and practical knowledge, sidelining or even abandoning the effort to master scientific and theoretical knowledge. This kind of pedagogical orientation is linked to two conceptions of the world. One of them is neoliberalism, which imprisons the horizons of society and people’s lives to an eternal adaptation to market logic. In this worldview, the knowledge worked on in school should always be aimed at the practical resolution of daily capitalist problems, and any kind of intellectual production that does not serve this purpose should be excluded from school curricula. The other worldview is of the increasing fragmentation of society and culture into identity groups that consider themselves owners of an experience that cannot be accessed or understood by any person from another group, as Gandesha ( 2018 , November 19) explained:

I would suggest (though I can’t show this here) that rather than an individualistic, rights-based model, identity politics is based on a particular, in my view reified, account of experience as expressed in the statement ‘You wouldn’t understand because it’s a Black, Asian or queer, thing.’ It is a staking out of a proprietary relation to an experience understood not as a process and a social relation but as a thing.

Obviously, this worldview excludes the possibility for a historical construction of a universally valid knowledge, since all knowledge will be connected to some identity. And any attempt to argue for the validity of scientific knowledge beyond a specific cultural context will be seen as a reproduction of colonizing attitudes. The scientist and historian of science, Meera Nanda ( 1997 ) advocates a quite different position from this one:

The sociological theories of science which see natural science as purely local and context-specific practice contradict the very rationale that made it possible for me to learn modern science while growing up in a small and rather provincial city in Punjab. The entire idea of adopting modern scientific education in non-Western countries is premised on a belief in the universality or trans-contextuality of scientific knowledge. (Nanda, 1997 , p. 306)

Our argument is that science education is necessary for the ethical and political education of younger generations because the problems humanity is facing today require structural social changes that will hardly occur without popular mobilization accompanied by an adequate understanding of the fundamental processes that produce the movement of nature and society. In order for people to be able to adopt ethical and political positions on contemporary reality and future possibilities, they need to know reality not as something static, but as movements that have generating dynamics that can be studied, understood, and within certain limits, modified or redirected. But to achieve this, it is necessary to go beyond daily appearances. Participation in discussions about the processes that drive natural and social reality requires the mastery of theories and abstract conceptual systems. The president of Brazil, Jair Bolsonaro, in trying to justify the use of chloroquine as a preventive treatment for Covid-19, claimed in January 2021 that 200 people living in the same building as him had been contaminated with the virus and none of them had been hospitalized because they had undergone “early treatment” with chloroquine and ivermectin (Andrade, 2021 , January 15). This is the type of reasoning easily assimilated by people who analyze reality from immediate daily experiences. The president clearly employed this rhetorical artifice because he was convinced that a large number of people would not only accept this type of argument, but would also identify with a president who “thinks like us.” This line of thinking is limited to doxa and has difficulty dealing with abstractions. Gandesha ( 2018 , November 19), commenting on the problematic nature of false concreteness, quotes Moishe Postone when he analyzes the relationships between the feeling of insecurity in contemporary capitalism, the difficulty in understanding the abstract structures of capital, and conspiracy theories: “That is, the sense of the loss of control that people have over their lives (which is real), becomes attributed, not to the abstract structures of capital, which are very difficult to apprehend, but to a Jewish conspiracy.” This example clearly shows the links between the neo-fascist views that have gained significant political and sociocultural space in various countries and the limitations of the ways in which one thinks about the world.

Saviani ( 2011 , p. 14) stated in the early 1980s that the school’s task is to socialize the mastery of systematized knowledge or episteme , differentiating this type of knowledge from doxa , or “spontaneous knowledge based on everyday experience.” New Zealand researcher Elizabeth Rata ( 2012a , p. 1) makes a similar distinction, employing the terms “disciplinary knowledge and social knowledge.” She argues that:

There is a type of knowledge that should be created in universities and taught in schools and to all students regardless of race, religion, and culture. That knowledge-variously known as academic, disciplinary, epistemic, erudite, scientific, esoteric, rational, abstract, and objective-is the disciplinary knowledge of the sciences, arts, humanities, and social sciences. (Rata, 2012a , p. 1)

However, according to the author, in recent decades, school curricula have undergone successive reformulations that have moved this type of knowledge to the background, being replaced by a social knowledge which she says is also known as “doxa, culture, beliefs, everyday knowledge, common sense, tacit knowledge, and folk knowledge” (Rata, 2012a , p. 1). Like Saviani ( 2011 ), who states that access, through school education, to systematized knowledge, namely, to the episteme , does not detract from the importance that popular knowledge, or doxa , has in people’s lives, Rata ( 2012a , p. 1) claims that “disciplinary knowledge and social knowledge are both important—each for its own purpose”. These purposes, however, are quite distinct:

Social knowledge comes from an individual’s experience within a socio-cultural group. It is the beliefs, values, and practices that reinforce an individual’s identification with the group and ensure the group's cohesion. Disciplinary knowledge, on the other hand, disturbs that common sense understanding of the world. It provides the means for doubt, criticism, and judgement- intellectual tools that change individuals and change the world. (Rata, 2012a , p.1)

Rata ( 2012b , pp. 104–105) opposes the loss of distinction between these two types of knowledge resulting from postmodern relativist and socio-constructivist positions that consider all knowledge to be ideological and justified purely in terms of power relations. The author argues that such a view fails to consider the fundamental differences between scientific knowledge and the beliefs present in worldviews belonging to specific cultures: “However, the status of scientific knowledge is seriously eroded when the same status is awarded to social knowledge. This equalising of status has occurred in the case of indigenous knowledge in universities in New Zealand, for example” (Rata, 2012b , p. 105).

At the same time, the importance of scientific knowledge for the curriculum is also eroded by visions that seek to attune school education to the demands of the contemporary capitalist economy. As Wheelahan ( 2010 ) shows, curriculum reforms undertaken since the 1990s in several countries around the world have moved theoretical knowledge away from school education, instead focusing on an instrumental view of learning that would supposedly prepare students for an imagined world of work that “consisted of the ‘natural’ free market populated by entrepreneurial, flexible workers who took responsibility for their firms’ outcomes, but without the hierarchical (and expensive) management structures characteristic of Fordism” (Wheelahan, 2010 , p. 129).

If, however, we agree with Rata ( 2012a , 2012b ), Saviani ( 2011 ), and Wheelahan ( 2010 ) that school education should constitute a socially organized effort for the democratization of access to epistemic knowledge, it becomes necessary to inquire whether the democratic perspective itself would not require teaching to focus only on the specific knowledge of the natural sciences while avoiding political positions. Our argument is that this is neither possible nor desirable.

Let’s start with the argument about the impossibility of teaching the natural sciences in a neutral manner. If we seek neutrality in this teaching, a first concern would be to avoid controversial issues. It is not the purpose of this article to analyze the existing literature on controversial issues in school and the different criteria proposed by authors to define what a controversial issue is. But we would point out that the decision regarding which issues are controversial involves political and ethical positions. There is, for example, an insurmountable inconsistency in the approach of trying to eliminate controversial issues from curricula and school debate in the name of educational neutrality given that the elimination of these issues is, in itself, the result of ethical and political judgments, which negates the premise of neutrality. This becomes even more evident when we see that, depending on the type of common sense in a given sociocultural context, some topics are considered absolutely normal and uncontroversial because they do not contradict the prevailing worldview, while other topics may be considered controversial and even offensive for the opposite reason.

Would it not be possible, however, to address controversial issues in a neutral way at school? The literature is also extensive in this regard, and it won’t be possible here to analyze the various lines of analysis. Teachers can indeed adopt strategies to conduct classroom activities in such a way as to avoid having to state their personal positions on controversial topics. Nonetheless, these strategies very often have negative consequences for a proper conceptual understanding of the knowledge being studied. Let us leave this discussion for another time, however, and focus our attention on something that seems decisive to us: the search for truth. We have already cited authors who claim that the school curriculum should be a constant search for an approximation to the truth. Paula McAvoy makes a distinction between the explicitness of teachers’ political positions and the commitment to truth.

Political views reflect beliefs and choices that individuals in a democratic society are allowed to make for themselves. In contrast, if a student in a history class wanted to argue that the Holocaust did not happen and a teacher uses evidence and argumentation to try to convince the student that it did happen, the teacher is not sharing a political view. Instead, the teacher is trying to correct the student’s factual misconception. (McAvoy, 2017 , p. 375)

We agree that the teacher should present facts and arguments that demonstrate that the Holocaust existed, just as, in the context of Brazilian reality, the teacher should present facts and arguments that demonstrate that a dictatorship existed from 1964 to 1985. However, just as some students and parents of students will consider that the teacher is taking a political position by teaching about the Holocaust, so too in Brazil will students and parents of students who are followers of Jair Bolsonaro consider that the Brazilian political regime from 1964 to 1985 was not a dictatorship but a necessary effort to rid the country of the danger of communism.

Commitment to truth becomes a political position when there are economic, political, and ideological interests that move in the opposite direction. This is not a historically recent phenomenon, but it has been accentuated in recent years as a result of the worldwide advance of belligerent obscurantism.

Although the examples of the Holocaust and the Brazilian dictatorship are from the area of social history, the argument is also valid for the natural sciences, not only because of the existing relationships between the various areas of knowledge, but also because of the fact that a significant part of the objects of study in the natural sciences is directly or indirectly connected to the study of the relationships between society and nature. Thus, it may be possible to keep the study of certain specific topics away from directly ethical and political positions, but the attitude of permanent search for scientific approximation to the truth tends to produce, in the study of natural sciences as a whole, the need for positions on the consequences of the choices that contemporary society makes regarding its relations with nature. In the examples cited throughout this text, an ethical and political position of defending scientific truth implies not accepting alternative explanations to the theory of evolution, such as creationism. It also implies not accepting that the ideas of common sense or the ethnosciences have the same ontological and epistemological status as scientific ones.

In addition to asserting the impossibility of ethical and political neutrality being adopted as a guiding principle for the teaching of natural sciences in schools, we also argue that it is undesirable. Firstly, because that would convey to students a mistaken image of both scientific endeavor and the significance of the natural sciences for society and people’s lives. The teaching of natural sciences should not aim at purely instrumental purposes, but rather to educate in ways of knowing and analyzing the world that allow human beings to make ethical and political decisions based on assessments of objective possibilities. Secondly, because the first two decades of this century have shown forcefully that environmental destruction and the accelerating advance of a culture of fear and hatred need to be confronted in a broad, deep, and urgent way if we want to build a solid foundation for the dignity of life to benefit present and future human generations. The opposite to the cultivation of hatred and disrespect for democratic debate is not omission or neutrality, but a position that has the courage to make itself explicit, being permanently open to a revision of positions when objective evidence and rational arguments demand it.

Why trust in science and science education? In relation to science, the arguments we present in this article seek to base trust in scientific knowledge on historical, dialectical, and materialist analyses. Historically, scientific activities have achieved a relative autonomy in relation to the production and reproduction of the materiality necessary for human life, but this does not mean that scientific activities may have a self-justifying existence detached from social practice in its totality. Scientific knowledge is one of the expressions of consciousness, which does not exist except in the form of a being that develops consciousness of itself and the world. As argued by Marx and Engels ( 1998 ) in The German Ideology , in order for human beings to develop consciousness, they need to produce and reproduce their objective existence as living beings and, in this process, also produce and reproduce social relations and ideas about nature and society. Science, as the most developed form of objective knowledge of the world, dialectically expresses the contradictions of human history and allows human beings to make choices regarding the possibilities of intervening in objectively existing processes to direct them in accordance with the ethical and political value of respecting the dignity of life. Put this way, the question of trust in science shows that it is not a naive and unconditional trust, that is, it is not a relationship of faith. Heller ( 1984 , pp. 209–210) makes a distinction between “blind faith” and “trust,” clarifying that they are not epistemological categories, or rather, they are not types of knowledge, but two different types of sentiment in the relations between people and knowledge or between people and other people, institutions, etc. It is our understanding that the relationship between people and scientific knowledge should be accompanied by the feeling of trust, but not of faith, since faith is a feeling that stands above the objective confirmation or refutation of an idea. Although faith is a feeling more clearly identifiable in the field of religions, it also shows itself in other phenomena, such as the fanatical faith of people in certain leaders. The followers of Trump in the USA and of Bolsonaro in Brazil blindly believe whatever their leader claims, even if the claims are in absolute and proven disagreement with the objective evidence and, not infrequently, with their leaders’ own previous claims. It is also the faith in fake news and conspiracy theories that causes these fanatical followers to reject a priori scientific knowledge no matter how well-grounded it is in objective evidence and consistent rational argumentation. One does not combat the faith of the denialists by cultivating faith in what scientists say. Trusting science does not mean blindly following scientists; to the extent of each person’s capacity for comprehension, it entails trying to evaluate the debates among scientists, their arguments, their evidence, and the rigor with which they carry out their investigations.

This goes back to the issue of trust in science education. No science education curriculum will ever be perfect, just as no science teaching strategy will ever be infallible. But it is necessary that we move toward agreement on certain principles that seem self-evident, but that have been rejected for a variety of reasons. One such principle is that there is scientific knowledge that explains objective reality more truthfully than other knowledge. This scientific knowledge should be taught to all children, adolescents, and young people, without any distinction. Another principle is that this kind of knowledge cannot be learned spontaneously, because its learning requires the systematic acquisition of ways of acting, thinking, and feeling, which does not occur without a deliberate and institutionally organized teaching activity. A third principle is that without the social valorization of teachers, ranging from their teacher education courses to their working and living conditions (including their retirement), there is no possibility of achieving this kind of education. Finally, the fourth principle is that the goal in terms of educational policy should be the universalization of free, secular, and high-quality education, without which the principle of democracy in education cannot be realized. Just as we argue that trust in science is not diminished but strengthened by the recognition of its links to the materiality and dialecticity of the historical process in the praxis of humanity as a whole, so too trust in science education is strengthened by the recognition that there is still much for us to grapple with in order to achieve the ideal of democratic education.

Declarations

The authors declare that they have no conflict of interest.

1 We define belligerent obscurantism as the individual and collective attitude of permanent struggle against the advance of knowledge and its diffusion. We qualify this obscurantism as belligerent both for its ostensibly aggressive attitude against scientists, teachers, artists and journalists, and also due to its vision of social life as a constant war in which the other is treated as an enemy to be slaughtered and, if possible, eliminated.

This article was translated from the original Portuguese by Tony O’Sullivan [email protected]

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STEM Integration in K-12 Education

Status, prospects, and an agenda for research.

STEM Integration in K-12 Education examines current efforts to connect the STEM disciplines in K-12 education. This report identifies and characterizes existing approaches to integrated STEM education, both in formal and after- and out-of-school settings. The report reviews the evidence for the impact of integrated approaches on various student outcomes, and it proposes a set of priority research questions to advance the understanding of integrated STEM education. STEM Integration in K-12 Education proposes a framework to provide a common perspective and vocabulary for researchers, practitioners, and others to identify, discuss, and investigate specific integrated STEM initiatives within the K-12 education system of the United States.

STEM Integration in K-12 Education makes recommendations for designers of integrated STEM experiences, assessment developers, and researchers to design and document effective integrated STEM education. This report will help to further their work and improve the chances that some forms of integrated STEM education will make a positive difference in student learning and interest and other valued outcomes.

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Science, health, and public trust.

September 8, 2021

Explaining How Research Works

We’ve heard “follow the science” a lot during the pandemic. But it seems science has taken us on a long and winding road filled with twists and turns, even changing directions at times. That’s led some people to feel they can’t trust science. But when what we know changes, it often means science is working.

Explaining the scientific process may be one way that science communicators can help maintain public trust in science. Placing research in the bigger context of its field and where it fits into the scientific process can help people better understand and interpret new findings as they emerge. A single study usually uncovers only a piece of a larger puzzle.

Questions about how the world works are often investigated on many different levels. For example, scientists can look at the different atoms in a molecule, cells in a tissue, or how different tissues or systems affect each other. Researchers often must choose one or a finite number of ways to investigate a question. It can take many different studies using different approaches to start piecing the whole picture together.

Sometimes it might seem like research results contradict each other. But often, studies are just looking at different aspects of the same problem. Researchers can also investigate a question using different techniques or timeframes. That may lead them to arrive at different conclusions from the same data.

Using the data available at the time of their study, scientists develop different explanations, or models. New information may mean that a novel model needs to be developed to account for it. The models that prevail are those that can withstand the test of time and incorporate new information. Science is a constantly evolving and self-correcting process.

Scientists gain more confidence about a model through the scientific process. They replicate each other’s work. They present at conferences. And papers undergo peer review, in which experts in the field review the work before it can be published in scientific journals. This helps ensure that the study is up to current scientific standards and maintains a level of integrity. Peer reviewers may find problems with the experiments or think different experiments are needed to justify the conclusions. They might even offer new ways to interpret the data.

It’s important for science communicators to consider which stage a study is at in the scientific process when deciding whether to cover it. Some studies are posted on preprint servers for other scientists to start weighing in on and haven’t yet been fully vetted. Results that haven't yet been subjected to scientific scrutiny should be reported on with care and context to avoid confusion or frustration from readers.

We’ve developed a one-page guide, "How Research Works: Understanding the Process of Science" to help communicators put the process of science into perspective. We hope it can serve as a useful resource to help explain why science changes—and why it’s important to expect that change. Please take a look and share your thoughts with us by sending an email to  [email protected].

Below are some additional resources:

• Discoveries in Basic Science: A Perfectly Imperfect Process
• When Clinical Research Is in the News
• What is Basic Science and Why is it Important?
• ​ What is a Research Organism?
• What Are Clinical Trials and Studies?
• Basic Research – Digital Media Kit
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Research-Based Practices for Engaging Students in STEM Learning

Innovative and effective practices at Cleveland’s MC2 STEM High School are driving learning and higher achievement for students in a district where every student qualifies for free or reduced-price meals.

The STEM School Movement

Science, technology, engineering, and math (STEM) specialty schools have existed in the United States for over 100 years, fueled in the 1950s by the Cold War space race and recently reinvigorated by concern over U.S. students’ modest performance in math and science as compared to their international peers (Means et al., 2008). This is troubling because, according to the National Research Council (2011), “more than half of the tremendous growth to per capita income in the 20th century can be accounted for by U.S. advances in science and technology.” In addition, businesses in the United States have voiced concern over the supply and availability of STEM workers and experts are concerned that the demand for STEM labor will only increase with time (U.S. Department of Commerce, 2011, 2012). Thus, the primary goal of the STEM school movement is to promote a future STEM workforce and maintain the U.S. position as a leader in innovation. There is also the need for citizens and consumers to be informed and engaged in everyday decisions that involve scientific arguments -- from policy debates that will have consequences for their health and safety to the products they consume and lifestyle choices they make.

One STEM school that is helping its students develop an array of skills to succeed in college and the workforce is MC 2 STEM High School (MC 2 STEM) in Cleveland, Ohio. Cleveland Metropolitan School District is one of the most economically disadvantaged school districts in the nation, with a free or reduced-price lunch rate of 100 percent. In 2011, just six out of ten students from the school district graduated high school on time. But at MC 2 STEM, which opened its doors in 2008, 95 percent of the first class graduated high school within four years. Students who have attended MC 2 STEM have not only graduated high school, they have also achieved the school’s requirements for mastery of every state standard. An integration of several research-based practices helps to promote student success and a caring environment at this small school:

• interdisciplinary project-based learning with real-world application
• challenging goals with multiple opportunities to show and develop learning
• community partnerships that provide tutors, mentors, internships, and service learning experiences.

Preliminary research on successful STEM schools indicates that cultivating partnerships with industry, higher education, nonprofits, museums, and research centers is important for engaging students in STEM learning through internships, mentorships, interdisciplinary project-based learning, and early college experiences (Means, 2008; National Research Council, 2011). MC 2 STEM is part of the Ohio STEM Learning Network , a network of ten STEM schools, developed with support from the Bill and Melinda Gates Foundation and in collaboration with the State of Ohio and various other partners. The Ohio STEM Learning Network is designed around five common principles . As a part of this network, MC 2 STEM is an inclusive STEM school that accepts students via lottery, as opposed to competitive selection, and is committed to the idea that STEM talent is something that can be developed, rather than something innate that must be identified (Means, 2008).

Interdisciplinary Project-Based Learning with Real-World Application

Project-based learning (PBL) has been shown to improve students' understanding of science, as well as their problem-solving and collaboration skills, to a greater extent than traditional methods (Geier et al., 2008; Gordon, Rogers, Comfort, Gavula, and McGee, 2001; Kolodner et al., 2003; Lee, Buxton, Lewis, and LeRoy, 2006; Liu, Hsieh, Cho, and Schallert, 2006; Lynch, Kuipers, Pyke, and Szesze, 2005; Marx et al., 2004; Schneider, Krajcik, Marx, and Soloway, 2001). Students who learn science or technology through project-based learning also report that they find it more engaging than traditional instructional techniques (Geier et al., 2008; Yazzie-Mintz, 2010).

PBL is the biggest component at MC 2 STEM and is perhaps even more engaging to students because of its interdisciplinary content. Interdisciplinary curricula have been shown by several studies to support students’ engagement and learning (Taylor and Parsons, 2011), and specifically integrating science with reading comprehension and writing lessons has been shown by several studies to improve students’ understanding in both science and English language arts (Pearson, Moje, and Greenleaf, 2010).

MC 2 STEM's transdisciplinary capstone projects blend science, English language arts, social studies, fine arts, engineering, and math, and are designed to transcend in-school and out-of-school environments. Their projects more closely resemble the tasks and ambiguities inherent in real life and help to make schoolwork more relevant to students’ lives, as well as more transparently linked to the skills needed to succeed in the working world. For example, in the “Bridges" capstone (PDF) , students learn about the mathematical and engineering concepts necessary to construct bridges, as well as the symbolic meaning of bridges in literature, history, and social studies.

In accord with the recommendations of PBL scholars and practitioners, capstone projects at MC 2 STEM are designed by starting with the learning objectives -- in this case, the Common Core standards (e.g., Wiggins and McTighe, 2005; Buck Institute for Education, 2012). Instructors of different subjects work together to think of a larger thematic concept that covers the state standards, and then they break down the larger thematic concept into units that address each state standard. (See a process model and planning activities for designing these types of transdisciplinary projects.)

In addition to the Common Core state standards, career-readiness standards for engineering and technology are also incorporated into several of the capstone projects at MC 2 STEM. For example, all students complete a Sophomore General Electric Project (PDF) , which is designed with GE Lighting employees to address current industry needs. According to Principal Jeffrey McClellan, if instructors are having difficulty coming up with a unit for a particular benchmark, industry partners have been helpful in brainstorming and explaining how particular state standards are used in their work, which results in more realistic capstone units.

(See our Resources and Downloads for PBL design documents and other resources from MC 2 STEM for transdisciplinary PBL.)

Challenging Goals with Multiple Opportunities to Show and Develop Learning

The combination of high expectations and adequate supports has been shown by several meta-analyses to be one of the most impactful strategies for improving academic achievement (Hattie, 2009). In order for challenging goals to be effective, Hattie (2011) asserts that they must be presented in a situation that is structured so that students can achieve them, students must be committed to them, and students must receive frequent feedback so they can direct and evaluate their actions accordingly. (See a flow chart of the multiple opportunities that MC 2 STEM students have for mastering benchmarks.)

MC 2 STEM is a challenging learning environment that holds high expectations for all students, while also providing multiple forms of support for students to show and develop learning. The MC 2 STEM graduation requirements state that in order to earn high school credit, students must achieve mastery (PDF) (greater than or equal to 90 percent in grades 9 and 10, and greater than or equal to 70 percent in grades 11 and 12) on each and every state standard. In addition, students must participate in 60 hours of community and/or STEM service and complete a GE sophomore project as well as a senior project in which they address an original research question.

About half of MC 2 STEM students fulfill all mastery requirements in the first three years. If a student doesn’t master a benchmark during a specific capstone, they are not required to retake that course. Instead, the missing benchmark is noted on their grade-card and teachers work with the student to integrate those benchmarks into subsequent capstones. (The digital grade-cards (PDF) provide a real-time picture of student progress toward mastery, and the school uses the 21st Century Partnership for STEM Education’s online grade-card system, which is a proficiency-based assessment that gives access to the school’s parents and teachers.) About 40 percent of the state standards are assessed through capstone projects, and the rest of the standards are assessed through more traditional in-class methods such as quizzes and presentations. During most classes, students work in groups based on the particular benchmark activities or assessments that they are mastering, while the teacher and tutors walk around and provide assistance.

Ohio’s Credit Flexibility Plan has played an important role in redesigning the high school experience at MC 2 STEM to enable in-depth learning. Schools that adopt the program can award high school course credit for fulfilling the state’s learning objectives as an alternative to seat-time. (Read more about the policy.) Credit Flexibility supports the Post Secondary Enrollment Option Program provided by MC 2 STEM, which allows students to earn college and high school credits simultaneously. Students also earn high school credit for internship experiences and typically up to two years of early college credit. Principal McClellan has a refrain at MC 2 STEM that reinforces high expectations, rather than the time students spend to achieve them: “Time is the variable. Knowledge is the constant.”

Students also participate in many extended-learning activities to support their learning, including summer learning at Case Western Reserve University and tutoring and mentorship programs. Students in grade nine meet with NASA employees four school days a year at NASA Glenn Research Center, and about one-third of freshmen work with NASA tutors after school for one hour, once or twice per week. Throughout the time they are working with the school, NASA tutors work with the same students so relationships can develop. Similarly, in grade ten, GE employees tutor students once or twice per week during lunch, and each tutor works with the same student for the entire time they are in the tutoring program. In addition, all sophomores spend two lunch periods per month with a GE mentor. Students report feeling cared about and supported at the school at a level that is above the district’s average, according to the district’s 2010 Conditions for Learning Survey.

The dropout-prevention research has also emphasized that “close mentoring and monitoring of students” is critical (Fairfax County Public Schools, 2011). According to McClellan, more often than not, simply asking a student why they haven’t been meeting expectations is the first step toward addressing the issue that is holding them back. MC 2 STEM is a small learning environment with approximately 300 students; however, the school’s design also incorporates frequent feedback into the curriculum and successfully increases its capacity for tutoring and mentoring through community partnerships with NASA, GE, and the Jewish Federation of Cleveland, as well as with interns and UTeach candidates from Cleveland State University. As described below, community partnerships also help to provide students with feedback from diverse stakeholders through internships and service-learning.

Community Partnerships That Provide Tutors, Mentors, Internships, and Service-Learning Experiences

Project-based learning helps to connect schoolwork with the work of professionals, and these connections are made further transparent through professional mentoring as well as internship and service-learning experiences. As MC 2 STEM students demonstrate mastery of state requirements, they earn the opportunity to participate in paid and unpaid internships (PDF) for high school credit. The principal determines internship readiness, with input from the guidance counselor and professional partners where appropriate. The potential employer interviews the student and decides if the student is hired for their internship. Currently over 50 percent of seniors and 40 percent of juniors are participating in paid internships, and about 90 percent of the class of 2012 participated in an internship prior to graduation. In addition to internships, all students are required to complete 40 hours of community service.

Research supports the potential benefits of internships or apprenticeships and community service for academic achievement and student engagement when these experiences are closely connected with curricular objectives (Bell, Blair, Crawford, and Lederman, 2003; Billig, 2007). Rigorous studies from the career-academy literature have also shown that integrating academic and work experiences can have positive impacts on students’ later earnings. Graduates of career-themed high schools that emphasized the connection between school and getting a good job earned 11 percent more per year, on average, than graduates of traditional high schools eight years after graduating (Stern et al., 2010). Similarly, the dropout-prevention literature emphasizes the importance of making school relevant to students’ lives and making sure that school is engaging and challenging. In a 2006 survey of students who dropped out of high school, 81 percent said that if schools provided opportunities for real-world learning , including internships and service-learning, it would have improved their chances of graduating high school (Bridgeland, Dilulio, and Morison, 2006). The study also found that clarifying the links between school and getting a job may convince more students to stay in school (Bridgeland et al., 2006).

Bibliography

Bell, R. L., Blair, L. M., Crawford, B. A., and Lederman, N. G. (2003). Just Do It? Impact of a Science Apprenticeship on High School Students’ Understandings of the Nature of Science and Scientific Inquiry. Journal of Research in Science Teaching, 40 (5), 487-509.

Billig, S. H. (2007). Unpacking What Works in Service-Learning Promising Research-Based Practices to Improve Student Outcomes. Growing to Greatness , p. 18-28. National Youth Leadership Council.

Bridgeland, J. M., Dilulio, J. J., and Morison, K. B. (2006). The Silent Epidemic: Perspectives of High School Dropouts.

Buck Institute for Education. (2009). Does PBL Work?

Fairfax County Public Schools. (2011). Bringing the Dropout Challenge into Focus. Fairfax County, VA: Department of Professional Learning and Accountability, Office of Program Evaluation.

Geier, R., Blumenfeld, P. C., Marx, R. W., Krajcik, J. S., Fishman, B., Soloway, E., et al. (2008). Standardized Test Outcomes for Students Engaged in Inquiry-Based Science Curricula in the Context of Urban Reform. Journal of Research in Science Teaching, 45 (8), 922–939.

Gordon, P. R., Rogers, A. M., Comfort, M., Gavula, N., and McGee, B. P. (2001). A Taste of Problem-Based Learning Increases Achievement of Urban Minority Middle-School Students. Educational Horizons, 79 (4), 171-175.

Hattie, J. A. C. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement. New York: Routledge.

Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., and Puntambekar, S. (2003). Problem-Based Learning Meets Case-Based Reasoning in the Middle-School Science Classroom: Putting Learning by Design into Practice. The Journal of the Learning Sciences, 12 (4), 495-547.

Lee, O., Buxton, C., Lewis, S., and LeRoy, K. (2006). Science Inquiry and Student Diversity: Enhanced Abilities and Continuing Difficulties After an Instructional Intervention. Journal of Research in Science Teaching, 43 (7), 607-636.

Liu, M., Hsieh, P., Cho, Y. J., and Schallert, D. L. (2006). Middle School Students’ Self-efficacy, Attitudes, and Achievement in a Computer-Enhanced Problem-Based Learning Environment. Journal of Interactive Learning Research, 17 (3), 225-242.

Lynch, S., Kuipers, J., Pyke, C., and Szesze, M. (2005). Examining the Effects of a Highly Rated Science Curriculum Unit on Diverse Students: Results from a Planning Grant. Journal of Research in Science Teaching, 42 (8), 912–946.

Marx, R. W., Blumenfeld, P. C., Krajcik, J. S., Fishman, B., Soloway, E., Geier, R., et al. (2004). Inquiry-Based Science in the Middle Grades: Assessment of Learning in Urban Systemic Reform. Journal of Research in Science Teaching, 41 (10), 1063–1080.

Means, B., Confrey, J., House, A., and Bhanot, R. (2008). STEM High Schools Specialized Science Technology Engineering and Mathematics Secondary Schools in the U.S. SRI Project P17858.

National Research Council - Committee on Highly Successful Science Programs for K-12 Science Education, Board on Science Education and Board on Testing and Assessment, Division of Behavioral and Social Sciences and Education. (2011). Successful K-12 STEM Education: Identifying Effective Approaches in Science, Technology, Engineering, and Mathematics. Washington, DC: The National Academies Press.

Pearson, P. D., Moje, E., and Greenleaf, C. (2010). Literacy and Science: Each in Service of the Other. Science , 328, 459-463.

Schneider, R. M., Krajcik, J., Marx, R. W., and Soloway, E. (2002). Performance of Students in Project Based Science Classrooms on a National Measure of Science Achievement. Journal of Research in Science Teaching, 38 (7), 410-422.

Stern, D., Dayton, C. and Raby, M. (2010). Career Academies: A Proven Strategy to Prepare High School Students for College and Careers. Berkeley, CA: University of California at Berkeley, Career Academy Support Network.

Taylor, L. and Parsons, J. (2011). Improving Student Engagement. Current Issues in Education, 14 (1).

U.S. Department of Commerce, Economics and Statistics Administration. (2011). STEM: Good Jobs Now and for the Future. (ESA Issue Brief #03-11.)

U.S. Department of Commerce. (2012). The Competitiveness and Innovative Capacity of the United States.

Wiggins, G. and McTighe, J. (2005). Understanding by Design. Expanded 2nd Ed. Alexandria, VA: Association for Supervision and Curriculum Development.

Yazzie-Mintz, E. (2010). Charting the Path from Engagement to Achievement: A Report on the 2009 High School Survey of Student Engagement.

Mc2 Stem High School

Per pupil expenditures, free / reduced lunch, demographics:.

12% individualized education programs 2% English-language learners

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Marketing Research: Planning, Process, Practice

Student resources, multiple choice quizzes.

Try these quizzes to test your understanding.

1. Reality in marketing research is ______.

2. The contribution of marketing research to organisational value is a trade-off between ______.

• benefits and sacrifices
• profit and losses
• good and bad

3. Ontology is the science that deals with ______.

• ethics in marketing
• the nature of reality
• knowledge creation

4. Human perception affects ______.

• epistemology

5. Epistemology focuses on ______.

• the process of marketing research

6. A piece of marketing research should ultimately aim to satisfy which of the following statements?

• something is true
• something is false
• something is important

7. A research paradigm essentially comprises every ______ made by a researcher.

8. It is hard to produce ______ theory (in marketing).

• middle-range
• substantive

9. A conceptualisation can be thought of as the mid-point between secondary and ______ research.

10. Deductive reasoning can be characterised as ______.

• introspective

11. Inductive reasoning is typically seen as ______.

• theory-driven

12. Theory has ______ power.

13. Abductive reasoning accepts the idea of ______ information.

14. Descriptive research typically looks at ______ issues.

• summarising

15. A research objective stems directly from a(n) ______.

• research question

16. Marketing research maintains the importance of its ______ at all times.

17. A model is a ______.

• hypothetical explanatory structure or mechanism
• flexible instrument for primary research
• personal interpretation of a phenomenon

18. Explanatory is a type of research aiming at ______.

• providing absolute certainties about life
• shedding light on the causes behind an issue
• dealing with different realities

19. Researchers in marketing should initially reflect more about ______.

• research questions
• ontological perspectives
• data collection

20. Marketing research is about making sense of ______.

Understanding Stem Cell Research

What's a stem cell?

The foundational building blocks of living organisms, stem cells are defined by two characteristics:   

• They can make copies of themselves, or  self-renew
• They can  differentiate , or develop into more specialized cells  

In humans, there are different types of stem cells that originate from different parts of the body and emerge during different times in our lives. These include embryonic stem cells, which only exist during the earliest stages of development, and tissue-specific stem cells, which arise during fetal development and persist throughout life.

"Stem cells are the foundation of organisms, the stalk from which everything buds and branches.” Alexander Capron Bioethicist, World Health Organization

What are the different types of stem cells?

Tissue-Specific Stem Cells

Tissue-specific stem cells, sometimes referred to as adult or somatic stem cells, contribute to the body’s ability to create new cells that can restore damaged organs and tissues. They also replace cells that are lost in normal day-to-day living.

Scientists now know that small populations of tissue-specific stem cells reside in many organs and tissues, including the brain, skeletal muscle, skin, heart, intestines and liver. While tissue-specific stem cells can help the body repair by producing all the cell types within their designated tissues, their ability to regenerate is limited and decreases over time. 

Blood stem cells, also known as hematopoietic stem cells, are found in the bone marrow and generate the different kinds of blood cells needed over a person’s lifespan. This includes red blood cells, white blood cells — also known as immune cells — and platelets. Transplants of blood stem cells have been used to treat patients with blood and immune diseases such as leukemia and aplastic anemia for more than 50 years. Today, the sources of blood stem cells used for transplantation include bone marrow, umbilical cord blood and peripheral blood.

Human Embryonic Stem Cells

In 1998, scientists succeeded in isolating human embryonic stem cells, or hESCs, for the first time. Since then, the more versatile and flexible regenerative potential of hESCs has proved vital to scientific research, enabling scientists to learn about human developmental processes that would otherwise be inaccessible. Unlike tissue-specific stem cells, hESCs have two distinct capabilities: They can replicate indefinitely, and they’re pluripotent, meaning they can produce the more than 200 cell types found in the human body through a process called differentiation.

Induced Pluripotent Stem Cells

In 2006, a team in Japan showed it was possible to induce pluripotency in mature cells, creating what are known as induced pluripotent stem cells, or iPSCs. Shortly after, center members Drs. Kathrin Plath , William Lowry , Amander Clark and April Pyle were the first in California to report the successful generation of iPSCs.

iPSCs originate from cells — such as skin or blood — that are removed from a person and reprogrammed back to a pluripotent state. Like hESCs, these reprogrammed cells can replicate indefinitely as well as differentiate into any cell type in the human body. Since iPSCs are made from a patient’s own cells, therapies created from these cells could potentially be perfectly matched to the patient. 

How are stem cells used in research?

Visit our  Research Area pages to learn how our multidisciplinary teams of scientists, clinicians and engineers are conducting stem cell research that’s driving medical and scientific knowledge in new directions, fundamentally changing the understanding and treatment of disease.

Where do we get stem cells for research? 

All of the human embryonic stem cells currently used in research come from cell lines that have been approved for research and registered with the National Institutes of Health . The original hESCs used to establish these lines come from embryos that are donated from consenting individuals or couples who have unused embryos after in vitro fertilization, or IVF, procedures. The embryonic stem cells are isolated from the inner cell mass of the blastocyst, a stage in early human embryonic development that occurs within the first four to six days after fertilization. Once hESCs are isolated, the cells may be kept alive and multiplied under specific laboratory conditions. Visit the California Institute for Regenerative Medicine's page on stem cell research to learn more about this process.

The human tissue — typically skin or blood — used to create induced pluripotent stem cell lines is donated by consenting individuals under specific research protocols.

For information about stem cell therapies and the availability of stem cell clinical trials at and beyond UCLA, visit our For Patients and Families page.