education problem solver

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Teaching problem solving.

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Tips and Techniques

Expert vs. novice problem solvers, communicate.

• Have students  identify specific problems, difficulties, or confusions . Don’t waste time working through problems that students already understand.
• If students are unable to articulate their concerns, determine where they are having trouble by  asking them to identify the specific concepts or principles associated with the problem.
• In a one-on-one tutoring session, ask the student to  work his/her problem out loud . This slows down the thinking process, making it more accurate and allowing you to access understanding.
• When working with larger groups you can ask students to provide a written “two-column solution.” Have students write up their solution to a problem by putting all their calculations in one column and all of their reasoning (in complete sentences) in the other column. This helps them to think critically about their own problem solving and helps you to more easily identify where they may be having problems. Two-Column Solution (Math) Two-Column Solution (Physics)

Encourage Independence

• Model the problem solving process rather than just giving students the answer. As you work through the problem, consider how a novice might struggle with the concepts and make your thinking clear
• Have students work through problems on their own. Ask directing questions or give helpful suggestions, but  provide only minimal assistance and only when needed to overcome obstacles.
• Don’t fear  group work ! Students can frequently help each other, and talking about a problem helps them think more critically about the steps needed to solve the problem. Additionally, group work helps students realize that problems often have multiple solution strategies, some that might be more effective than others

Be sensitive

• Frequently, when working problems, students are unsure of themselves. This lack of confidence may hamper their learning. It is important to recognize this when students come to us for help, and to give each student some feeling of mastery. Do this by providing  positive reinforcement to let students know when they have mastered a new concept or skill.

Encourage Thoroughness and Patience

• Try to communicate that  the process is more important than the answer so that the student learns that it is OK to not have an instant solution. This is learned through your acceptance of his/her pace of doing things, through your refusal to let anxiety pressure you into giving the right answer, and through your example of problem solving through a step-by step process.

Experts (teachers) in a particular field are often so fluent in solving problems from that field that they can find it difficult to articulate the problem solving principles and strategies they use to novices (students) in their field because these principles and strategies are second nature to the expert. To teach students problem solving skills,  a teacher should be aware of principles and strategies of good problem solving in his or her discipline .

The mathematician George Polya captured the problem solving principles and strategies he used in his discipline in the book  How to Solve It: A New Aspect of Mathematical Method (Princeton University Press, 1957). The book includes  a summary of Polya’s problem solving heuristic as well as advice on the teaching of problem solving.

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Why Every Educator Needs to Teach Problem-Solving Skills

Strong problem-solving skills will help students be more resilient and will increase their academic and career success .

Want to learn more about how to measure and teach students’ higher-order skills, including problem solving, critical thinking, and written communication?

Problem-solving skills are essential in school, careers, and life.

Problem-solving skills are important for every student to master. They help individuals navigate everyday life and find solutions to complex issues and challenges. These skills are especially valuable in the workplace, where employees are often required to solve problems and make decisions quickly and effectively.

Problem-solving skills are also needed for students’ personal growth and development because they help individuals overcome obstacles and achieve their goals. By developing strong problem-solving skills, students can improve their overall quality of life and become more successful in their personal and professional endeavors.

Problem-Solving Skills Help Students…

   develop resilience.

Problem-solving skills are an integral part of resilience and the ability to persevere through challenges and adversity. To effectively work through and solve a problem, students must be able to think critically and creatively. Critical and creative thinking help students approach a problem objectively, analyze its components, and determine different ways to go about finding a solution.  

This process in turn helps students build self-efficacy . When students are able to analyze and solve a problem, this increases their confidence, and they begin to realize the power they have to advocate for themselves and make meaningful change.

When students gain confidence in their ability to work through problems and attain their goals, they also begin to build a growth mindset . According to leading resilience researcher, Carol Dweck, “in a growth mindset, people believe that their most basic abilities can be developed through dedication and hard work—brains and talent are just the starting point. This view creates a love of learning and a resilience that is essential for great accomplishment.”

    Set and Achieve Goals

Students who possess strong problem-solving skills are better equipped to set and achieve their goals. By learning how to identify problems, think critically, and develop solutions, students can become more self-sufficient and confident in their ability to achieve their goals. Additionally, problem-solving skills are used in virtually all fields, disciplines, and career paths, which makes them important for everyone. Building strong problem-solving skills will help students enhance their academic and career performance and become more competitive as they begin to seek full-time employment after graduation or pursue additional education and training.

  Resolve Conflicts

In addition to increased social and emotional skills like self-efficacy and goal-setting, problem-solving skills teach students how to cooperate with others and work through disagreements and conflicts. Problem-solving promotes “thinking outside the box” and approaching a conflict by searching for different solutions. This is a very different (and more effective!) method than a more stagnant approach that focuses on placing blame or getting stuck on elements of a situation that can’t be changed.

While it’s natural to get frustrated or feel stuck when working through a conflict, students with strong problem-solving skills will be able to work through these obstacles, think more rationally, and address the situation with a more solution-oriented approach. These skills will be valuable for students in school, their careers, and throughout their lives.

    Achieve Success

We are all faced with problems every day. Problems arise in our personal lives, in school and in our jobs, and in our interactions with others. Employers especially are looking for candidates with strong problem-solving skills. In today’s job market, most jobs require the ability to analyze and effectively resolve complex issues. Students with strong problem-solving skills will stand out from other applicants and will have a more desirable skill set.

In a recent opinion piece published by The Hechinger Report , Virgel Hammonds, Chief Learning Officer at KnowledgeWorks, stated “Our world presents increasingly complex challenges. Education must adapt so that it nurtures problem solvers and critical thinkers.” Yet, the “traditional K–12 education system leaves little room for students to engage in real-world problem-solving scenarios.” This is the reason that a growing number of K–12 school districts and higher education institutions are transforming their instructional approach to personalized and competency-based learning, which encourage students to make decisions, problem solve and think critically as they take ownership of and direct their educational journey.

Problem-Solving Skills Can Be Measured and Taught

Research shows that problem-solving skills can be measured and taught. One effective method is through performance-based assessments which require students to demonstrate or apply their knowledge and higher-order skills to create a response or product or do a task.

What Are Performance-Based Assessments?

With the No Child Left Behind Act (2002), the use of standardized testing became the primary way to measure student learning in the U.S. The legislative requirements of this act shifted the emphasis to standardized testing, and this led to a  decline in nontraditional testing methods .

But   many educators, policy makers, and parents have concerns with standardized tests. Some of the top issues include that they don’t provide feedback on how students can perform better, they don’t value creativity, they are not representative of diverse populations, and they can be disadvantageous to lower-income students.

While standardized tests are still the norm, U.S. Secretary of Education Miguel Cardona is encouraging states and districts to move away from traditional multiple choice and short response tests and instead use performance-based assessment, competency-based assessments, and other more authentic methods of measuring students abilities and skills rather than rote learning. 

Performance-based assessments  measure whether students can apply the skills and knowledge learned from a unit of study. Typically, a performance task challenges students to use their higher-order skills to complete a project or process. Tasks can range from an essay to a complex proposal or design.

Preview a Performance-Based Assessment

Want a closer look at how performance-based assessments work?  Preview CAE’s K–12 and Higher Education assessments and see how CAE’s tools help students develop critical thinking, problem-solving, and written communication skills.

Performance-Based Assessments Help Students Build and Practice Problem-Solving Skills

In addition to effectively measuring students’ higher-order skills, including their problem-solving skills, performance-based assessments can help students practice and build these skills. Through the assessment process, students are given opportunities to practically apply their knowledge in real-world situations. By demonstrating their understanding of a topic, students are required to put what they’ve learned into practice through activities such as presentations, experiments, and simulations. 

This type of problem-solving assessment tool requires students to analyze information and choose how to approach the presented problems. This process enhances their critical thinking skills and creativity, as well as their problem-solving skills. Unlike traditional assessments based on memorization or reciting facts, performance-based assessments focus on the students’ decisions and solutions, and through these tasks students learn to bridge the gap between theory and practice.

Performance-based assessments like CAE’s College and Career Readiness Assessment (CRA+) and Collegiate Learning Assessment (CLA+) provide students with in-depth reports that show them which higher-order skills they are strongest in and which they should continue to develop. This feedback helps students and their teachers plan instruction and supports to deepen their learning and improve their mastery of critical skills.

Explore CAE’s Problem-Solving Assessments

CAE offers performance-based assessments that measure student proficiency in higher-order skills including problem solving, critical thinking, and written communication.

• College and Career Readiness Assessment (CCRA+) for secondary education and
• Collegiate Learning Assessment (CLA+) for higher education.

Our solution also includes instructional materials, practice models, and professional development.

We can help you create a program to build students’ problem-solving skills that includes:

• Measuring students’ problem-solving skills through a performance-based assessment    
• Using the problem-solving assessment data to inform instruction and tailor interventions
• Teaching students problem-solving skills and providing practice opportunities in real-life scenarios
• Supporting educators with quality professional development

Get started with our problem-solving assessment tools to measure and build students’ problem-solving skills today! These skills will be invaluable to students now and in the future.

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Learn more about cae’s suite of products and let’s get started measuring and teaching students important higher-order skills like problem solving..

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Educational leaders’ problem-solving for educational improvement: Belief validity testing in conversations

• Open access
• Published: 01 October 2021
• Volume 24 , pages 133–181, ( 2023 )

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• Claire Sinnema   ORCID: orcid.org/0000-0002-6707-6726 1 ,
• Frauke Meyer 1 ,
• Deidre Le Fevre 1 ,
• Hamish Chalmers 1 &
• Viviane Robinson 1  

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Educational leaders’ effectiveness in solving problems is vital to school and system-level efforts to address macrosystem problems of educational inequity and social injustice. Leaders’ problem-solving conversation attempts are typically influenced by three types of beliefs—beliefs about the nature of the problem, about what causes it, and about how to solve it. Effective problem solving demands testing the validity of these beliefs—the focus of our investigation. We analyzed 43 conversations between leaders and staff about equity related problems including teaching effectiveness. We first determined the types of beliefs held and the validity testing behaviors employed drawing on fine-grained coding frameworks. The quantification of these allowed us to use cross tabs and chi-square tests of independence to explore the relationship between leaders’ use of validity testing behaviors (those identified as more routine or more robust, and those relating to both advocacy and inquiry) and belief type. Leaders tended to avoid discussion of problem causes, advocate more than inquire, bypass disagreements, and rarely explore logic between solutions and problem causes. There was a significant relationship between belief type and the likelihood that leaders will test the validity of those beliefs—beliefs about problem causes were the least likely to be tested. The patterns found here are likely to impact whether micro and mesosystem problems, and ultimately exo and macrosystem problems, are solved. Capability building in belief validity testing is vital for leadership professional learning to ensure curriculum, social justice and equity policy aspirations are realized in practice.

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This study examines the extent to which leaders, in their conversations with others, test rather than assume the validity of their own and others’ beliefs about the nature, causes of, and solutions to problems of teaching and learning that arise in their sphere of responsibility. We define a problem as a gap between the current and desired state, plus the demand that the gap be reduced (Robinson, 1993 ). We position this focus within the broader context of educational change, and educational improvement in particular, since effective discussion of such problems is central to improvement and vital for addressing issues of educational equity and social justice.

Educational improvement and leaders’ role in problem solving

Educational leaders work in a discretionary problem-solving space. Ball ( 2018 ) describes discretionary spaces as the micro level practices of the teacher. It is imperative to attend to what happens in these spaces because the specific talk and actions that occur in particular moments (for example, what the teacher says or does when one student responds in a particular way to his or her question) impact all participants in the classroom and shape macro level educational issues including legacies of racism, oppression, and marginalization of particular groups of students. A parallel exists, we argue, for leaders’ problem solving—how capable leaders are at dealing with micro-level problems in the conversational moment impacts whether a school or network achieves its improvement goals. For example, how a leader deals with problems with a particular teacher or with a particular student or group of students is subtly but strongly related to the solving of equity problems at the exo and macro levels. Problem solving effectiveness is also related to challenges in the realization of curriculum reform aspirations, including curriculum reform depth, spread, reach, and pace (Sinnema & Stoll, 2020b ).

The conversations leaders have with others in their schools in their efforts to solve educational problems are situated in a broader environment which they both influence and are influenced by. We draw here on Bronfonbrenner’s ( 1992 ) ecological systems theory to construct a nested model of educational problem solving (see Fig.  1 ). Bronfenbrenner focused on the environment around children, and set out five interrelated systems that he professed influence a child’s development. We propose that these systems can also be used to understand another type of learner—educators, including leaders and teachers—in the context of educational problem solving.

Nested model of educational problem solving

Bronfenbrenner’s ( 1977 ) microsystem sets out the immediate environment, parents, siblings, teachers, and peers as influencers of and influenced by children. We propose the micro system for educators to include those they have direct contact with including their students, other teachers in their classroom and school, the school board, and the parent community. Bronfenbrenner’s meso system referred to the interactions between a child’s microsystems. In the same way, when foregrounding the ecological system around educators, we suggest attention to the problems that occur in the interactions between students, teachers, school leaders, their boards, and communities. In the exo system, Bronfenbrenner directs attention to other social structures (formal and informal), which do not themselves contain the child, but indirectly influence them as they affect one of the microsystems. In the same way, we suggest educational ministries, departments and agencies function to influence educators. The macro system as theorized by Bronfenbrenner focuses on how child development is influenced by cultural elements established in society, including prevalent beliefs, attitudes, and perceptions. In our model, we recognise how such cultural elements of Bronfenbrenner’s macro system also relate to educators in that dominant and pervasive beliefs, attitudes and perceptions create and perpetuate educational problems, including those relating to educational inequity, bias, racism, social injustice, and underachievement. The chronosystem, as Bronfenbrenner describes, shows the role of environmental changes across a lifetime, which influences development. In a similar way, educators′ professional transitions and professional milestones influence and are influenced by other system levels, and in the context of our work, their problem solving approaches.

Leaders’ effectiveness in discussions about problems related to the micro and mesosystem contributes greatly to the success of exosystem reform efforts, and those efforts, in turn, influence the beliefs, attitudes, and ideologies of the macrosystem. As Fig.  1 shows, improvement goals (indicated by the arrows moving from the current to a desired state) in the exo or macrosystem are unlikely to be achieved without associated improvement in the micro and mesosystem involving students, teachers, and groups of teachers, schools and their boards and parent communities. Similarly, the level of improvement in the macro and exosystems is limited by the extent to which more improvement goals at the micro and mesosystem are achieved through solving problems relating to students’ experience and school and classroom practices including curriculum, teaching, and assessment. As well as drawing on Bronfenbrenner’s ecological systems theory, our nested model of problem solving draws on problem solving theory to draw attention to how gaps between current and desired states at each of the system levels also influence each other (Newell & Simon, 1972 ). Efforts to solve problems in any one system (to move from current state toward a more desired state) are supported by similar moves at other interrelated systems. For example, the success of a teacher seeking to solve a curriculum problem (demand from parents to focus on core knowledge in traditional learning domains, for example)—a problem related to the microsystem and mesosystem—will be influenced by how similar problems are recognised, attended to, and solved by those in the ministries, departments and agencies in the exosystem.

In considering the role of educational leaders in this nested model of problem solving, we take a capability perspective (Mumford et al., 2000 ) rather than a leadership style perspective (Bedell-Avers et al., 2008 ). School leaders (including those with formal and informal leadership positions) require particular capabilities if they are to enact ambitious policies and solve complex problems related to enhancing equity for marginalized and disadvantaged groups of students (Mavrogordato & White, 2020 ). Too often, micro and mesosystem problems remain unsolved which is problematic not only for those directly involved, but also for the resolution of the related exo and macrosystem problems. The ill-structured nature of the problems school leaders face, and the social nature of the problem-solving process, contribute to the ineffectiveness of leaders’ problem-solving efforts and the persistence of important microsystem and mesosystem problems in schools.

Ill-structured problems

The problems that leaders need to solve are typically ill-structured rather than clearly defined, complex rather that than straight-forward, and adaptive rather than routine challenges (Bedell-Avers et al., 2008 ; Heifetz et al., 2009 ; Leithwood & Stager, 1989 ; Leithwood & Steinbach, 1992 , 1995 ; Mumford & Connelly, 1991 ; Mumford et al., 2000 ; Zaccaro et al., 2000 ). As Mumford and Connelly explain, “even if their problems are not totally unprecedented, leaders are, […] likely to be grappling with unique problems for which there is no clear-cut predefined solution” (Mumford & Connelly, 1991 , p. 294). Most such problems are difficult to solve because they can be construed in various ways and lack clear criteria for what counts as a good solution. Mumford et al. ( 2000 ) highlight the particular difficulties in solving ill-structured problems with regard to accessing, evaluating and using relevant information:

Not only is it difficult in many organizational settings for leaders to say exactly what the problem is, it may not be clear exactly what information should be brought to bear on the problem. There is a plethora of available information in complex organizational systems, only some of which is relevant to the problem. Further, it may be difficult to obtain accurate, timely information and identify key diagnostic information. As a result, leaders must actively seek and carefully evaluate information bearing on potential problems and goal attainment. (p. 14)

Problems in schools are complex. Each single problem can comprise multiple educational dimensions (learners, learning, curriculum, teaching, assessment) as well as relational, organizational, psychological, social, cultural, and political dimensions. In response to a teaching problem, for example, a single right or wrong answer is almost never at play; there are typically countless possible ‘responses’ to the problem of how to teach effectively in any given situation.

Problem solving as socially situated

Educational leaders’ problem solving is typically social because multiple people are usually involved in defining, explaining, and solving any given problem (Mumford et al., 2000 ). When there are multiple parties invested in addressing a problem, they typically hold diverse perspectives on how to describe (frame, perceive, and communicate about problems), explain (identify causes which lead to the problem), and solve the problem. Argyris and Schön ( 1974 ) argue that effective leaders must manage the complexity of integrating multiple and diverse perspectives, not only because all parties need to be internally committed to solutions, but also because quality solutions rely on a wide range of perspectives and evidence. Somewhat paradoxically, while the multiple perspectives involved in social problem solving add to their inherent complexity, these perspectives are a resource for educational change, and for the development of more effective solutions (Argyris & Schön, 1974 ). The social nature of problem solving requires high trust so participants can provide relevant, accurate, and timely information (rather than distort or withhold it), recognize their interdependence, and avoid controlling others. In high trust relationships, as Zand’s early work in this field established, “there is less socially generated uncertainty and problems are solved more effectively” (Zand, 1972 , p. 238).

Leaders’ capabilities in problem solving

Leadership research has established the centrality of capability in problem solving to leadership effectiveness generally (Marcy & Mumford, 2010 ; Mumford et al., 2000 , 2007 ) and to educational leadership in particular. Leithwood and Stager ( 1989 ), for example, consider “administrator’s problem-solving processes as crucial to an understanding of why principals act as they do and why some principals are more effective than others” (p. 127). Similarly, Robinson ( 1995 , 2001 , 2010 ) positions the ability to solve complex problems as central to all other dimensions of effective educational leadership. Unsurprisingly, problem solving is often prominent in standards for school leaders/leadership and is included in tools for the assessment of school leadership (Goldring et al., 2009 ). Furthermore, its importance is heightened given the increasing demand and complexity in standards for teaching (Sinnema, Meyer & Aitken, 2016) and the trend toward leadership across networks of schools (Sinnema, Daly, Liou, & Rodway, 2020a ) and the added complexity of such problem solving where a system perspective is necessary.

Empirical research on leaders’ practice has revealed that there is a need for capability building in problem solving (Le Fevre et al., 2015 ; Robinson et al., 2020 ; Sinnema et al., 2013 ; Sinnema et al., 2016 ; Smith, 1997 ; Spillane et al., 2009 ; Timperley & Robinson, 1998 ; Zaccaro et al., 2000 ). Some studies have compared the capability of leaders with varying experience. For example, Leithwood and Stager ( 1989 ) noted differences in problem solving approaches between novice and expert principals when responding to problem scenarios, particularly when the scenarios described ill-structured problems. Principals classified as ‘experts’ were more likely to collect information rather than make assumptions, and perceived unstructured problems to be manageable, whereas typical principals found these problems stressful. Expert principals also consulted extensively to get relevant information and find ways to deal with constraints. In contrast, novice principals consulted less frequently and tended to see constraints as obstacles (Leithwood & Stager, 1989 ). Allison and Allison ( 1993 ) reported that while experienced principals were better than novices at developing abstract problem-solving goals, they were less interested in the detail of how they would pursue these goals. Similar differences were found in Spillane et al.’s ( 2009 ) work that found expert principals to be better at interpreting problems and reflecting on their own actions compared with aspiring principals. More recent work (Sinnema et al., 2021 ) highlights that educators perceptions of discussion quality is positively associated with both new learning for the educator (learning that influences their practice) and improved practice (practices that reach students)—the more robust and helpful educators report their professional discussion to be, the more likely they are to report improvement in their practice. This supports the demand for quality conversation in educational teams.

Solving problems related to teaching and learning that occur in the micro or mesosystem usually requires conversations that demand high levels of interpersonal skill. Skill development is important because leaders tend to have difficulty inquiring deeply into the viewpoints of others (Le Fevre & Robinson, 2015 ; Le Fevre et al., 2015 ; Robinson & Le Fevre, 2011 ). In a close analysis of 43 conversation transcripts, Le Fevre et al. ( 2015 ) showed that when leaders anticipated or encountered diverse views, they tended to ask leading or loaded rather than genuine questions. This pattern was explained by their judgmental thinking, and their desire to avoid negative emotion and stay in control of the conversation. In a related study of leaders’ conversations, a considerable difference was found between the way educational leaders described their problem before and during the conversation with those involved (Sinnema et al., 2013 ). Prior to the conversation, privately, they tended to describe their problem as more serious and more urgent than they did in the conversation they held later with the person concerned.

One of the reasons for the mismatch between their private descriptions and public disclosures was the judgmental framing of their beliefs about the other party’s intentions, attitudes, and/or motivations (Peeters & Robinson, 2015 ). If leaders are not willing or able to reframe such privately-held beliefs in a more respectful manner, they will avoid addressing problems through fear of provoking negative emotion, and neither party will be able to critique the reasoning that leads to the belief in question (Robinson et al., 2020 ). When that happens, beliefs based on faulty reasoning may prevail, problem solutions may be based only on that which is discussable, and the problem may persist.

A model of effective problem-solving conversations

We present below a normative model of effective problem-solving conversations (Fig.  2 ) in which testing the validity of relevant beliefs plays a central role. Leaders test their beliefs about a problem when they draw on a set of validity testing behaviors and enact those behaviors, through their inquiry and advocacy, in ways that are consistent with the three interpersonal values included in the model. The model proposes that these processes increase the effectiveness of social problem solving, with effectiveness understood as progressing the task of solving the problem while maintaining or improving the leader’s relationship with those involved. In formulating this model, we drew on the previously discussed research on problem solving and theories of interpersonal and organisational effectiveness.

Model of effective problem-solving conversations

The role of beliefs in problem solving

Beliefs are important in the context of problem solving because they shape decisions about what constitutes a problem and how it can be explained and resolved. Beliefs link the object of the belief (e.g., a teacher’s planning) to some attribute (e.g., copied from the internet). In the context of school problems these attributes are usually tightly linked to a negative evaluation of the object of the belief (Fishbein & Ajzen, 1975 ). Problem solving, therefore, requires explicit attention by leaders to the validity of the information on which their own and others’ beliefs are based. The model draws on the work of Mumford et al. ( 2000 ) by highlighting three types of beliefs that are central to how people solve problems—beliefs about whether and why a situation is problematic (we refer to these as problem description beliefs); beliefs about the precursors of the problem situation (we refer to these as problem explanation beliefs); and beliefs about strategies which could, would, or should improve the situation (we refer to these as problem solution beliefs). With regard to problem explanation beliefs, it is important that attention is not limited to surface level factors, but also encompasses consideration of deeper related issues in the broader social context and how they contribute to any given problem.

The role of values in problem-solving conversations

Figure  2 proposes that problem solving effectiveness is increased when leaders’ validity testing behaviors are consistent with three values—respecting the views of others, seeking to maximize validity of their own and others’ beliefs, and building internal commitment to decisions reached. The inclusion of these three values in the model means that our validity testing behaviors must be conceptualized and measured in ways that capture their interpersonal (respect and internal commitment) and epistemic (valid information) underpinnings. Without this conceptual underpinning, it is likely to be difficult to identify the validity testing behaviors that are associated with effectiveness. For example, the act of seeking agreement can be done in a coercive or a respectful manner, so it is important to define and measure this behavior in ways that distinguish between the two. How this and similar distinctions were accomplished is described in the subsequent section on the five validity testing behaviors.

The three values in Fig.  2 are based on the theories and practice of interpersonal and organizational effectiveness developed by Argyris and Schön ( 1974 , 1978 , 1996 ) and applied more recently in a range of educational leadership research contexts (Hannah et al., 2018 ; Patuawa et al., 2021 ; Sinnema et al., 2021a ). We have drawn on the work of Argyris and Schön because their theories explain the dilemma many leaders experience between the two components of problem solving effectiveness and indicate how that dilemma can be avoided or resolved.

Seeking to maximize the validity of information is important because leaders’ beliefs have powerful consequences for the lives and learning of teachers and students and can limit or support educational change efforts. Leaders who behave consistently with the validity of information value are truth seekers rather than truth claimers in that they are open-minded and thus more attentive to the information that disconfirms rather than confirms their beliefs. Rather than assuming the validity of their beliefs and trying to impose them on others, their stance is one of seeking to detect and correct errors in their own and others′ thinking (Robinson, 2017 ).

The value of respect is closely linked to the value of maximizing the validity of information. Leaders increase validity by listening carefully to the views of others, especially if those views differ from their own. Listening carefully requires the accordance of worth and respect, rather than private or public dismissal of views that diverge from or challenge one’s own. If leaders’ conversations are guided by the two values of valid information and respect, then the third value of fostering internal commitment is also likely to be present. Teachers become internally committed to courses of action when their concerns have been listened to and directly addressed as part of the problem-solving process.

The role of validity testing behaviors in problem solving

Figure  2 includes five behaviors designed to test the validity of the three types of belief involved in problem solving. They are: 1) disclosing beliefs; 2) providing grounds; 3) exploring difference; 4) examining logic; and 5) seeking agreement. These behaviors enable leaders to check the validity of their beliefs by engaging in open minded disclosure and discussion of their thinking. While these behaviors are most closely linked to the value of maximizing valid information, the values of respect and internal commitment are also involved in these behaviors. For example, it is respectful to honestly and clearly disclose one’s beliefs about a problem to the other person concerned (advocacy), and to do so in ways that make the grounds for the belief testable and open to revision. It is also respectful to combine advocacy of one’s own beliefs with inquiry into others’ reactions to those beliefs and with inquiry into their own beliefs. When leaders encounter doubts and disagreements, they build internal rather than external commitment by being open minded and genuinely interested in understanding the grounds for them (Spiegel, 2012 ). By listening to and responding directly to others’ concerns, they build internal commitment to the process and outcomes of the problem solving.

Advocacy and inquiry dimensions

Each of the five validity testing behaviors can take the form of a statement (advocacy) or a question (inquiry). A leader’s advocacy contributes to problem solving effectiveness when it communicates his or her beliefs and the grounds for them, in a manner that is consistent with the three values. Such disclosure enables others to understand and critically evaluate the leader’s thinking (Tompkins, 2013 ). Respectful inquiry is equally important, as it invites the other person into the conversation, builds the trust they need for frank disclosure of their views, and signals that diverse views are welcomed. Explicit inquiry for others’ views is particularly important when there is a power imbalance between the parties, and when silence suggests that some are reluctant to disclose their views. Across their careers, leaders tend to rely more heavily on advocating their own views than on genuinely inquiring into the views of others (Robinson & Le Fevre, 2011 ). It is the combination of advocacy and inquiry behaviors, that enables all parties to collaborate in formulating a more valid understanding of the nature of the problem and of how it may be solved.

The five validity testing behaviors

Disclosing beliefs is the first and most essential validity testing behavior because beliefs cannot be publicly tested, using the subsequent four behaviors, if they are not disclosed. This behavior includes leaders’ advocacy of their own beliefs and their inquiry into others’ beliefs, including reactions to their own beliefs (Peeters & Robinson, 2015 ; Robinson & Le Fevre, 2011 ).

Honest and respectful disclosure ensures that all the information that is believed to be relevant to the problem, including that which might trigger an emotional reaction, is shared and available for validity testing (Robinson & Le Fevre, 2011 ; Robinson et al., 2020 ; Tjosvold et al., 2005 ). Respectful disclosure has been linked with follower trust. The empirical work of Norman et al. ( 2010 ), for example, showed that leaders who disclose more, and are more transparent in their communication, instill higher levels of trust in those they work with.

Providing grounds , the second validity testing behavior, is concerned with leaders expressing their beliefs in a way that makes the reasoning that led to them testable (advocacy) and invites others to do the same (inquiry). When leaders clearly explain the grounds for their beliefs and invite the other party to critique their relevance or accuracy, the validity or otherwise of the belief becomes more apparent. Both advocacy and inquiry about the grounds for beliefs can lead to a strengthening, revision, or abandonment of the beliefs for either or both parties (Myran & Sutherland, 2016 ; Robinson & Le Fevre, 2011 ; Robinson et al., 2020 ).

Exploring difference is the third validity testing behavior. It is essential because two parties simply disclosing beliefs and the grounds for them is insufficient for arriving at a joint solution, particularly when such disclosure reveals that there are differences in beliefs about the accuracy and implications of the evidence or differences about the soundness of arguments. Exploring difference through advocacy is seen in such behaviors as identifying and signaling differing beliefs and evaluating contrary evidence that underpins those differing beliefs. An inquiry approach to exploring difference (Timperley & Parr, 2005 ) occurs when a leader inquires into the other party’s beliefs about difference, or their response to the leaders’ beliefs about difference.

Exploring differences in beliefs is key to increasing validity in problem solving efforts (Mumford et al., 2007 ; Robinson & Le Fevre, 2011 ; Tjosvold et al., 2005 ) because it can lead to more integrative solutions and enhance the commitment from both parties to work with each other in the future (Tjosvold et al., 2005 ). Leaders who are able to engage with diverse beliefs are more likely to detect and challenge any faulty reasoning and consequently improve solution development (Le Fevre & Robinson, 2015 ). In contrast, when leaders do not engage with different beliefs, either by not recognizing or by intentionally ignoring them, validity testing is more limited. Such disengagement may be the result of negative attributions about the other person, such as that they are resistant, stubborn, or lazy. Such attributions reduce opportunities for the rigorous public testing that is afforded by the exchange and critical examination of competing views.

Examining logic , the fourth validity testing behavior, highlights the importance of devising a solution that adequately addresses the nature of the problem at hand and its causes. To develop an effective solution both parties must be able to evaluate the logic that links problems to their assumed causes and solutions. This behavior is present when the leader suggests or critiques the relationship between possible causes of and solutions to the identified problem. In its inquiry form, the leader seeks such information from the other party. As Zaccaro et al. ( 2000 ) explain, good problem solvers have skills and expertise in selecting the information to attend to in their effort to “understand the parameters of problems and therefore the dimensions and characteristics of a likely solution” (p. 44–45). These characteristics may include solution timeframes, resource capacities, an emphasis on organizational versus personal goals, and navigation of the degree of risk allowed by the problem approach. Explicitly exploring beliefs is key to ensuring the logic linking problem causes and any proposed solution. Taking account of a potentially complex set of contributing factors when crafting logical solutions, and testing the validity of beliefs about them, is likely to support effective problem solving. This requires what Copland ( 2010 ) describes as a creative process with similarities to clinical reasoning in medicine, in which “the initial framing of the problem is fundamental to the development of a useful solution” (p. 587).

Seeking agreement , the fifth validity testing behavior, signals the importance of warranted agreement about problem beliefs. We use the term ‘warranted’ to make clear that the goal is not merely getting the other party to agree (either that something is a problem, that a particular cause is involved, or that particular actions should be carried out to solve it)—mere agreement is insufficient. Rather, the goal is for warranted agreement whereby both parties have explored and critiqued the beliefs (and their grounds) of the other party in ways that provide a strong basis for the agreement. Both parties must come to some form of agreement on beliefs because successful solution implementation occurs in a social context, in that it relies on the commitment of all parties to carry it out (Mumford et al., 2000 ; Robinson & Le Fevre, 2011 ; Tjosvold et al., 2005 ). Where full agreement does not occur, the parties must at least be clear about where agreement/disagreement lies and why.

Testing the validity of beliefs using these five behaviors, and underpinned by the values described earlier is, we argue, necessary if conversations are to lead to two types of improvement—progress on the task (i.e., solving the problem) and improving the relationship between those involved in the conversation (i.e., ensuring those relationship between the problem-solvers is intact and enhanced through the process). We draw attention here to those improvement purposes as distinct from those underpinning work in the educational leadership field that takes a neo-managerialist perspective. The rise of neo-managerialism is argued to redefine school management and leadership along managerial lines and hence contribute to schools that are inequitable, reductionist, and inauthentic (Thrupp & Willmott, 2003 ). School leaders, when impacted by neo-managerialism, need to be (and are seen as) “self-interested, opportunistic innovators and risk-takers who exploit information and situations to produce radical change.” In contrast, the model we propose rejects self-interest. Our model emphasizes on deep respect for the views of others and the relentless pursuit of genuine shared commitment to understanding and solving problems that impact on children and young people through collaborative engagement in joint problem solving. Rather than permitting leaders to exploit others, our model requires leaders to be adept at using both inquiry and advocacy together with listening to both progress the task (solving problems) and simultaneously enhance the relationship between those involved. We position this model of social problem solving effectiveness as a tool for addressing social justice concerns—it intentionally dismisses problem solving approaches that privilege organizational efficiency indicators and ignore the wellbeing of learners and issues of inequity, racism, bias, and social injustice within and beyond educational contexts.

Methodology

The following section outlines the purpose of the study, the participants, and the mixed methods approach to data collection and analysis.

Research purpose

Our prior qualitative research (Robinson et al., 2020 ) involving in-depth case studies of three educational leaders revealed problematic patterns in leaders’ approach to problem-solving conversations: little disclosure of causal beliefs, little public testing of beliefs that might trigger negative emotions, and agreement on solutions that were misaligned with causal beliefs. The present investigation sought to understand if a quantitative methodological approach would reveal similar patterns and examine the relationship between belief types and leaders’ use of validity testing behaviors. Thus, our overarching research question was: to what extent do leaders test the validity of their beliefs in conversations with those directly involved in the analysis and resolution of the problem? Our argument is that while new experiences might motivate change in beliefs (Bonner et al., 2020 ), new insights gained through testing the validity of beliefs is also imperative to change. The sub-questions were:

What is the relative frequency in the types of beliefs leaders hold about problems involving others?

To what extent do leaders employ validity testing behaviors in conversations about those problems?

Are there differential patterns in leaders’ validity testing of the different belief types?

Participants

The participants were 43 students in a graduate course on educational leadership in New Zealand who identified an important on the job problem that they intended to discuss with the person directly involved.

The mixed methods approach

The study took a mixed methods approach using a partially mixed sequential equal status design; (QUAL → QUAN) (Leech & Onwuegbuzie, 2009 ). The five stages of sourcing and analyzing data and making interpretations are summarised in Fig.  3 below and outlined in more detail in the following sections (with reference in brackets to the numbered phases in the figure). We describe the study as partially mixed because, as Leech & Onwuegbuzie, 2009 explain, in partially mixed methods “both the quantitative and qualitative elements are conducted either concurrently or sequentially in their entirety before being mixed at the data interpretation stage” (p. 267).

Overview of mixed methods approach

Stage 1: Qualitative data collection

Three data sources were used to reveal participants’ beliefs about the problem they were seeking to address. The first source was their response to nine open ended items in a questionnaire focused on a real problem the participant had attempted to address but that still required attention (1a). The items were about: the nature and history of the problem; its importance; their own and others’ contribution to it; the causes of the problem; and the approach to and effectiveness of prior attempts to resolve it.

The second source (1b) was the transcript of a real conversation (typically between 5 and 10 minutes duration) the leaders held with the other person involved in the problem, and the third was the leaders’ own annotations of their unspoken thoughts and feelings during the course of the conversation (1c). The transcription was placed in the right-hand column (RHC) of a split page with the annotations recorded at the appropriate place in the left-hand column (LHC). The LHC method was originally developed by Argyris and Schön ( 1974 ) as a way of examining discrepancies between people’s espoused and enacted interpersonal values. Referring to data about each leader’s behavior (as recorded in the transcript of the conversation) and their thoughts (as indicated in the LHC) was important since the model specifies validity testing behaviors that are motivated by the values of respect, valid information, and internal commitment. Since motives cannot be revealed by speech alone, we also needed access to the thoughts that drove their behavior, hence our use of the LHC data collection technique. This approach allowed us to respond to Leithwood and Stager’s ( 1989 ) criticism that much research on effective problem solving gives results that “reveal little or nothing about how actions were selected or created and treat the administrator’s mind as a ‘black box’” (p. 127).

Stage 2: Qualitative analysis

The three stages of qualitative analysis focused on identifying discrete beliefs in the three qualitative data sources, distilling those discrete beliefs into key beliefs, and identifying leaders’ use of validity testing behaviors.

Stage 2a: Analyzing types of beliefs about problems

For this stage, we developed and applied coding rules (see Table 1 ) for the identification of the three types of beliefs in the three sources described earlier—leaders’ questionnaire responses, conversation transcript (RHC), and unexpressed thoughts (LHC). We identified 903 discrete beliefs (utterances or thoughts) from the 43 transcripts, annotations, and questionnaires and recorded these on a spreadsheet (2a). While our model proposes that leaders’ inquiry will surface and test the beliefs of others, we quantify in this study only the leaders’ beliefs.

Stage 2b: Distilling discrete beliefs into key beliefs

Next, we distilled the 903 discrete beliefs into key beliefs (KBs) (2b). This was a complex process and involved multiple iterations across the research team to determine, check, and test the coding rules. The final set of rules for distilling key beliefs were:

Beliefs should be made more succinct in the key belief statement, and key words should be retained as much as possible

Judgment quality (i.e., negative or positive) of the belief needs to be retained in the key belief

Key beliefs should use overarching terms where possible

The meaning and the object of the belief need to stay constant in the key belief

When reducing overlap, the key idea of both beliefs need to be captured in the key beliefs

Distinctive beliefs need to be summarized on their own and not combined with other beliefs

The subject of the belief must be retained in the key belief—own belief versus restated belief of other

All belief statements must be accounted for in key beliefs

These rules were applied to the process of distilling multiple related beliefs into statements of key beliefs as illustrated by the example in the table below (Table 2 ).

Further examples of how the rules were applied are outlined in ' Appendix A '. The number of discrete beliefs for each leader ranged from 7 to 35, with an average of 21, and the number of key beliefs for each leader ranged between 4 and 14, with an average of eight key beliefs. Frequency counts were used to identify any patterns in the types of key beliefs which were held privately (not revealed in the conversation but signalled in the left hand column or questionnaire) or conveyed publicly (in conversation with the other party).

Stage 2c: Analyzing leaders’ use of validity testing behaviors

We then developed and applied coding rules for the five validity testing behaviors (VTB) outlined in our model (disclosing beliefs, providing grounds, exploring difference, examining logic, and seeking agreement). Separate rules were established for the inquiry and advocacy aspects of each VTB, generating ten coding rules in all (Table 3 ).

These rules, summarised in the table below, and outlined more fully in ' Appendix A ', encompassed inclusion and exclusion criteria for the advocacy and inquiry dimensions of each validity testing behavior. For example, the inclusion rule for the VTB of ‘Disclosing Beliefs’ required leaders to disclose their beliefs about the nature, and/or causes, and/or possible solutions to the problem, in ways that were consistent with the three values included in the model. The associated exclusion rule signalled that this criterion was not met if, for example, the leader asked a question in order to steer the other person toward their own views without having ever disclosed their own views, or if they distorted the urgency or seriousness of the problem related to what they had expressed privately. The exclusion rules also noted how thoughts expressed in the left hand column would exclude the verbal utterance from being treated as disclosure—for example if there were contradictions between the right hand (spoken) and left hand column (thoughts), or if the thoughts indicated that the disclosure had been distorted in order to minimise negative emotion.

The coding rules reflected the values of respect and internal commitment in addition to the valid information value that was foregrounded in the analysis. The emphasis on inquiry, for example (into others’ beliefs and/or responses to the beliefs already expressed by the leader), recognised that internal commitment would be impossible if the other party held contrary views that had not been disclosed and discussed. Similarly, the focus on leaders advocating their beliefs, grounds for those beliefs and views about the logic linking solutions to problem causes recognise that it is respectful to make those transparent to another party rather than impose a solution in the absence of such disclosure.

The coding rules were applied to all 43 transcripts and the qualitative analysis was carried out using NVivo 10. A random sample of 10% of the utterances coded to a VTB category was checked independently by two members of the research team following the initial analysis by a third member. Any discrepancies in the coding were resolved, and data were recoded if needed. Descriptive analyses then enabled us to compare the frequency of leaders’ use of the five validity testing behaviors.

Stage 3: Data transformation: From qualitative to quantitative data

We carried out transformation of our data set (Burke et al., 2004 ), from qualitative to quantitative, to allow us to carry out statistical analysis to answer our research questions. The databases that resulted from our data transformation, with text from the qualitative coding along with numeric codes, are detailed next. In database 1, key beliefs were all entered as cases with indications in adjacent columns as to the belief type category they related to, and the source/s of the belief (questionnaire, transcript or unspoken thoughts/feelings). A unique identifier was created for each key belief.

In database 2, each utterance identified as meeting the VTB coding rules were entered in column 1. The broader context of the utterance from the original transcript was then examined to establish the type of belief (description, explanation, or solution) the VTB was being applied to, with this recorded numerically alongside the VTB utterance itself. For example, the following utterance had been coded to indicate that it met the ‘providing grounds’ coding rule, and in this phase it was also coded to indicate that it was in relation to a ‘problem description’ belief type:

“I noticed on the feedback form that a number of students, if I’ve got the numbers right here, um, seven out of ten students in your class said that you don’t normally start the lesson with a ‘Do Now’ or a starter activity.” (case 21)

A third database listed all of the unique identifiers for each leader’s key beliefs (KB) in the first column. Subsequent columns were set up for each of the 10 validity testing codes (the five validity testing behaviors for both inquiry and advocacy). The NVivo coding for the VTBs was then examined, one piece of coding at a time, to identify which key belief the utterance was associated with. Each cell that intersected the appropriate key belief and VTB was increased by one as a VTB utterance was associated with a key belief. Our database included variables for both the frequency of each VTB (the number of instances the behavior was used) and a parallel version with just a dichotomous variable indicating the presence or absence or each VTB. The dichotomous variable was used for our subsequent analysis because multiple utterances indicating a certain validity testing behavior were not deemed to necessarily constitute better quality belief validity testing than one utterance.

Stage 4: Quantitative analysis

The first phase of quantitative analysis involved the calculation of frequency counts for the three belief types (4a). Next, frequencies were calculated for the five validity testing behaviors, and for those behaviors in relation to each belief type (4b).

The final and most complex stage of the quantitative analysis, stages 4c through 4f, involved looking for patterns across the two sets of data created through the prior analyses (belief type and validity testing behaviors) to investigate whether leaders might be more inclined to use certain validity testing behaviors in conjunction with a particular belief type.

Stage 4a: Analyzing for relationships between belief type and VTB

We investigated the relationship between belief type and VTB, first, for all key beliefs. Given initial findings about variability in the frequency of the VTBs, we chose not to use all five VTBs separately in our analysis, but rather the three categories of: 1) None (key beliefs that had no VTB applied to them); 2) VTB—Routine (the sum of VTBs 1 and 2; given those were much more prevalent than others in the case of both advocacy and inquiry); and 3) VTB—Robust (the sum of the VTBs 3, 4 and 5 given these were all much less prevalent than VTBs 1 and 2, again including both advocacy and/or inquiry). Cross tabs were prepared and a chi-square test of independence was performed on the data from all 331 key beliefs.

Stage 4b: Analyzing for relationships between belief type and VTB

Next, because more than half (54.7%, 181) of the 331 key beliefs were not tested by leaders using any one of the VTBs, we analyzed a sub-set of the database, selecting only those key beliefs where leaders had disclosed the belief (using advocacy and/or inquiry). The reason for this was to ensure that any relationships established statistically were not unduly influenced by the data collection procedure which limited the time for the conversation to 10 minutes, during which it would not be feasible to fully disclose and address all key beliefs held by the leader. For this subset we prepared cross tabs and carried out chi-square tests of independence for the 145 key beliefs that leaders had disclosed. We again investigated the relationship between key belief type and VTBs, this time using a VTB variable with two categories: 1) More routine only and 2) More routine and robust.

Stage 4c: Analyzing for relationships between belief type and advocacy/inquiry dimensions of validity testing

Next, we investigated the relationship between key belief type and the advocacy and inquiry dimensions of validity testing. This analysis was to provide insight into whether leaders might be more or less inclined to use certain VTBs for certain types of belief. Specifically, we compared the frequency of utterances about beliefs of all three types for the categories of 1) No advocacy or inquiry, 2) Advocacy only, 3) Inquiry only, and 4) Advocacy and inquiry (4e). Cross tabs were prepared, and a chi-square test of independence was performed on the data from all 331 key beliefs. Finally, we again worked with the subset of 145 key beliefs that had been disclosed, comparing the frequency of utterances coded to 1) Advocacy or inquiry only, or 2) Both advocacy and inquiry (4f).

Below, we highlight findings in relation to the research questions guiding our analysis about: the relative frequency in the types of beliefs leaders hold about problems involving others; the extent to which leaders employ validity testing behaviors in conversations about those problems; and differential patterns in leaders’ validity testing of the different belief types. We make our interpretations based on the statistical analysis and draw on insights from the qualitative analysis to illustrate those results.

Belief types

Leaders’ key beliefs about the problem were evenly distributed between the three belief types, suggesting that when they think about a problem, leaders think, though not necessarily in a systematic way, about the nature of, explanation for, and solutions to their problem (see Table 4 ). These numbers include beliefs that were communicated and also those recorded privately in the questionnaire or in writing on the conversation transcripts.

Patterns in validity testing

The majority of the 331 key beliefs (54.7%, 181) were not tested by leaders using any one of the VTBs, not even the behavior of disclosing the belief. Our analysis of the VTBs that leaders did use (see Table 5 ) shows the wide variation in frequency of use with some, arguably the more robust ones, hardly used at all.

The first pattern was more frequent disclosure of key beliefs than provision of the grounds for them. The lower levels of providing grounds is concerning because it has implications for the likelihood of those in the conversation subsequently reaching agreement and being able to develop solutions logically aligned to the problem (VTB4). The logical solution if it is the time that guided reading takes that is preventing a teacher doing ‘shared book reading’ (as Leader 20 believed to be the case) is quite different to the solution that is logical if in fact the reason is something different, for example uncertainty about how to go about ‘shared book reading’, lack of shared book resources, or a misunderstanding that school policy requires greater time on shared reading.

The second pattern was a tendency for leaders to advocate much more than they inquire— there was more than double the proportion of advocacy than inquiry overall and for some behaviors the difference between advocacy and inquiry was up to seven times greater. This suggests that leaders were more comfortable disclosing their own beliefs, providing the grounds for their own beliefs and expressing their own assumptions about agreement, and less comfortable in inquiring in ways that created space and invited the other person in the conversation to reveal their beliefs.

A third pattern revealed in this analysis was the difference in the ratio of inquiry to advocacy between VTB1 (disclosing beliefs)—a ratio of close to 1:2 and VTB2 (providing grounds)—a ratio of close to 1:7. Leaders are more likely to seek others’ reactions when they disclose their beliefs than when they give their grounds for those beliefs. This might suggest that leaders assume the validity of their own beliefs (and therefore do not see the need to inquire into grounds) or that they do not have the skills to share the grounds associated with the beliefs they hold.

Fourthly, there was an absence of attention to three of the VTBs outlined in our model—in only very few of the 329 validity testing utterances the 43 leaders used were they exploring difference (11 instances), examining logic (4 instances) or seeking agreement (22 instances). In Case 22, for example, the leader claimed that learning intentions should be displayed and understood by children and expressed concern that the teacher was not displaying them, and that her students thus did not understand the purpose of the activities they were doing. While the teacher signaled her disagreement with both of those claims—“I do learning intentions, it’s all in my modelling books I can show them to you if you want” and “I think the children know why they are learning what they are learning”—the fact that there were differences in their beliefs was not explicitly signaled, and the differences were not explored. The conversation went on, with each continuing to assume the accuracy of their own beliefs. They were unable to reach agreement on a solution to the problem because they had not established and explored the lack of agreement about the nature of the problem itself. We presume from these findings, and from our prior qualitative work in this field, that those VTBs are much more difficult, and therefore much less likely to be used than the behaviors of disclosing beliefs and providing grounds.

The relationship between belief type and validity testing behaviors

The relationship between belief type and category of validity testing behavior was significant ( Χ 2 (4) = 61.96,  p  < 0.001). It was notable that problem explanation beliefs were far less likely than problem description or problem solution beliefs to be subject to any validity testing (the validity of more than 80% of PEBs was not tested) and, when they were tested, it was typically with the more routine rather than robust VTBs (see Table 6 ).

Problem explanation beliefs were also most likely to not be tested at all; more than 80% of the problem explanation beliefs were not the focus of any validity testing. Further, problem description beliefs were less likely than problem solution beliefs to be the target of both routine and robust validity testing behaviors—12% of PDBs and 18% of PSBs were tested using both routine and robust VTBs.

Two important assumptions underpin the study reported here. The first is that problems of equity must be solved, not only in the macrosystem and exosystem, but also as they occur in the day to day practices of leaders and teachers in micro and mesosystems. The second is that conversations are the key practice in which problem solving occurs in the micro and mesosystems, and that is why we focused on conversation quality. We focused on validity testing as an indicator of quality by closely analyzing transcripts of conversations between 43 individual leaders and a teacher they were discussing problems with.

Our findings suggest a considerable gap between our normative model of effective problem solving conversations and the practices of our sample of leaders. While beliefs about what problems are, and proposed solutions to them are shared relatively often, rarely is attention given to beliefs about the causes of problems. Further, while leaders do seem to be able to disclose and provide grounds for their beliefs about problems, they do so less often for beliefs about problem cause than other belief types. In addition, the critical validity testing behaviors of exploring difference, examining logic, and seeking agreement are very rare. Learning how to test the validity of beliefs is, therefore, a relevant focus for educational leaders’ goals (Bendikson et al., 2020 ; Meyer et al., 2019 ; Sinnema & Robinson, 2012 ) as well as a means for achieving other goals.

The patterns we found are problematic from the point of view of problem solving in schools generally but are particularly problematic from the point of view of macrosystem problems relating to equity. In New Zealand, for example, the underachievement and attendance issues of Pasifika students is a macrosystem problem that has been the target of many attempts to address through a range of policies and initiatives. Those efforts include a Pasifika Education Plan (Ministry of Education, 2013 ) and a cultural competencies framework for teachers of Pasifika learners—‘Tapasa’ (Ministry of Education, 2018 ) At the level of the mesosystem, many schools have strategic plans and school-wide programmes for interactions seeking to address those issues.

Resolving such equity issues demands that macro and exosystem initiatives are also reflected in the interactions of educators—hence our investigation of leaders’ problem-solving conversations and attention to whether leaders have the skills required to solve problems in conversations that contribute to aspirations in the exo and macrosystem, include of excellence and equity in new and demanding national curricula (Sinnema et al., 2020a ; Sinnema, Stoll, 2020a ). An example of an exosystem framework—the competencies framework for teachers of Pacific students in New Zealand—is useful here. It requires that teachers “establish and maintain collaborative and respectful relationships and professional behaviors that enhance learning and wellbeing for Pasifika learners” (Ministry of Education, 2018 , p. 12). The success of this national framework is influenced by and also influences the success that leaders in school settings have at solving problems in the conversations they have about related micro and mesosystem problems.

To illustrate this point, we draw here on the example of one case from our sample that showed how problem-solving conversation capability is related to the success or otherwise of system level aspirations of this type. In the case of Leader 36, under-developed skill in problem solving talk likely stymied the success of the equity-focused system initiatives. Leader 36 had been alerted by the parents of a Pasifika student that their daughter “feels that she is being unfairly treated, picked on and being made to feel very uncomfortable in the teacher’s class.” In the conversation with Leader 36, the teacher described having established a good relationship with the student, but also having had a range of issues with her including that she was too talkative, that led the teacher to treat her in ways the teacher acknowledged could have made her feel picked on and consequently reluctant to come to school.

The teacher also told the leader that there were issues with uniform irregularities (which the teacher picked on) and general non conformity—“No, she doesn’t [conform]. She often comes with improper footwear, incorrect jacket, comes late to school, she puts make up on, there are quite a few things that aren’t going on correctly….”. The teacher suggested that the student was “drawing the wrong type of attention from me as a teacher, which has had a negative effect on her.” The teacher described to the leader a recent incident:

[The student] had come to class with her hair looking quite shabby so I quietly asked [the student] “Did you wake up late this morning?” and then she but I can’t remember, I made a comment like “it looks like you didn’t take too much interest in yourself.” To me, I thought there was nothing wrong with the comment as it did not happen publicly; it happened in class and I had walked up to her. Following that, [her] Mum sends another email about girls and image and [says] that I am picking on her again. I’m quite baffled as to what is happening here. (case 36)

This troubling example represented a critical discretionary moment. The pattern of belief validity testing identified through our analysis of this case (see Table 7 ), however, mirrors some of the patterns evident in the wider sample.

The leader, like the student’s parents, believed that the teacher had been offensive in her communication with the student and also that the relationship between the teacher and student would be negatively impacted as a result. These two problem description beliefs were disclosed by the leader during her conversation with the teacher. However, while her disclosure of her belief about the problem description involved both advocating the belief, and inquiring into the other’s perception of it, the provision of grounds for the belief involved advocacy only. She reported the basis of the concern (the email from the student’s parents about their daughter feeling unfairly treated, picked on, and uncomfortable in class) but did not explicitly inquire into the grounds. This may be explained in this case through the teacher offering her own account of the situation that matched the parent’s report. Leader 36 also disclosed in her conversation with the teacher, her problem solution key belief that they should hold a restorative meeting between the teacher, the student, and herself.

What Leader 36 did not disclose was her belief about the explanation for the problem—that the teacher did not adequately understand the student personally, or their culture. The problem explanation belief (KB4) that she did inquire into was one the teacher raised—suggesting that the student has “compliance issues” that led the teacher to respond negatively to the student’s communication style—and that the teacher agreed with. The leader did not use any of the more robust but important validity testing behaviors for any of the key beliefs they held, either about problem description, explanation or solutions. And most importantly, this conversation highlights how policies and initiatives developed by those in the macrosystem, aimed at addressing equity issues, can be thwarted through well-intentioned but ultimately unsuccessful efforts of educators as they operate in the micro and mesosystem in what we referred to earlier as a discretionary problem solving space. The teacher’s treatment of the Pasifika student in our example was in stark contrast to the respectful and strong relationships demanded by the exosystem policy, the framework for teachers of Pasifika students. Furthermore, while the leader recognized the problem, issues of culture were avoided—they were not skilled enough in disclosing and testing their beliefs in the course of the conversation to contribute to broader equity concerns. The skill gap resonates with the findings of much prior work in this field (Le Fevre et al., 2015 ; Robinson et al., 2020 ; Sinnema et al., 2013 ; Smith, 1997 ; Spillane et al., 2009 ; Timperley & Robinson, 1998 ; Zaccaro et al., 2000 ), and highlights the importance of leaders, and those working with them in leadership development efforts, to recognize the interactions between the eco-systems outlined in the nested model of problem solving detailed in Fig.  1 .

The reluctance of Leader 36 to disclose and discuss her belief that the teacher misunderstands the student and her culture is important given the wider research evidence about the nature of the beliefs teachers may hold about indigenous and minority learners. The expectations teachers hold for these groups are typically lower and more negative than for white students (Gay, 2005 ; Meissel et al., 2017 ). In evidence from the New Zealand context, Turner et al. ( 2015 ), for example, found expectations to differ according to ethnicity with higher expectations for Asian and European students than for Māori and Pasifika students, even when controlling for achievement, due to troubling teacher beliefs about students’ home backgrounds, motivations, and aspirations. These are just the kind of beliefs that leaders must be able to confront in conversations with their teachers.

We use this example to illustrate both the interrelatedness of problems across the ecosystem, and the urgency of leadership development intervention in this area. Our normative model of effective problem solving conversations (Fig.  2 ), we suggest, provides a useful framework for the design of educational leadership intervention in this area. It shows how validity testing behaviors should embody both advocacy and inquiry and be used to explore not only perceptions of problem descriptions and solutions, but also problem causes. In this way, we hope to offer insights into how the dilemma between trust and accountability (Ehren et al., 2020 ) might be solved through increased interpersonal effectiveness. The combination of inquiry with advocacy also marks this approach out from neo-liberal approaches that emphasize leaders staying in control and predominantly advocating authoritarian perspectives of educational leadership. The interpersonal effectiveness theory that we draw on (Argyris & Schön, 1974 ) positions such unilateral control as ineffective, arguing for a mutual learning alternative. The work of problem solving is, we argue, joint work, requiring shared commitment and control.

Our findings also call for more research explicitly designed to investigate linkages between the systems. Case studies are needed, of macro and exosystem inequity problems backward mapped to initiatives and interactions that occur in schools related to those problems and initiatives. Such research could capture the complex ways in which power plays out “in relation to structural inequalities (of class, disability, ethnicity, gender, nationality, race, sexuality, and so forth)” and in relation to “more shifting and fluid inequalities that play out at the symbolic and cultural levels (for example, in ways that construct who “has” potential)” (Burke & Whitty, 2018 , p. 274).

Leadership development in problem solving should be approached in ways that surface and test the validity of leaders’ beliefs, so that they similarly learn to surface and test others’ beliefs in their leadership work. That is important not only from a workforce development point of view, but also from a social justice point of view since leaders’ capabilities in this area are inextricably linked to the success of educational systems in tackling urgent equity concerns.

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Sinnema, C., Meyer, F., Le Fevre, D. et al. Educational leaders’ problem-solving for educational improvement: Belief validity testing in conversations. J Educ Change 24 , 133–181 (2023). https://doi.org/10.1007/s10833-021-09437-z

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Teaching problem solving

Strategies for teaching problem solving apply across disciplines and instructional contexts. First, introduce the problem and explain how people in your discipline generally make sense of the given information. Then, explain how to apply these approaches to solve the problem.

Introducing the problem

Explaining how people in your discipline understand and interpret these types of problems can help students develop the skills they need to understand the problem (and find a solution). After introducing how you would go about solving a problem, you could then ask students to:

• frame the problem in their own words
• define key terms and concepts
• determine statements that accurately represent the givens of a problem
• identify analogous problems
• determine what information is needed to solve the problem

Working on solutions

In the solution phase, one develops and then implements a coherent plan for solving the problem. As you help students with this phase, you might ask them to:

• identify the general model or procedure they have in mind for solving the problem
• set sub-goals for solving the problem
• identify necessary operations and steps
• draw conclusions
• carry out necessary operations

You can help students tackle a problem effectively by asking them to:

• systematically explain each step and its rationale
• explain how they would approach solving the problem
• help you solve the problem by posing questions at key points in the process
• work together in small groups (3 to 5 students) to solve the problem and then have the solution presented to the rest of the class (either by you or by a student in the group)

In all cases, the more you get the students to articulate their own understandings of the problem and potential solutions, the more you can help them develop their expertise in approaching problems in your discipline.

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• Our Mission

Guiding Students to Be Independent Problem-Solvers in STEM Classrooms

Teaching high school students how to plan to solve a problem in science, technology, engineering, and math is a crucial step.

Teaching students to become independent problem-solvers can be a challenging task, especially with virtual teaching during the pandemic. For some students, solving problems is not intuitive, and they need to learn how to think about solving problems from a general perspective. As experts, teachers often do not realize that there are implicit skills and ways of thinking that may not be obvious or known to our students.

5 Strategies to Explicitly Model and Teach Problem-Solving Skills

1. Model hidden thinking involved in solving a problem. When solving a problem, I talk about every aspect of what I am doing out loud. In fact, I over-talk, providing reasoning for every step. For example, when solving a dimensional-analysis problem, I will include descriptions like, “OK, I am going to look for any numbers that I can cancel. I know I can cancel or reduce if I see a number in the numerator and another number in the denominator that have a common factor.”

I will even include moments of vulnerability and model the fact that I don’t always know what to do, but I will discuss my options and my decision process. I sometimes intentionally make mistakes and then use methods to check my work to correct my errors. It’s essential that we explicitly show students this internal dialogue to model problem-solving.

2. Facilitate student talk during problem-solving. I do my best to never solve problems for students, even if they ask me. This includes whole-class lessons and working with students in small groups or individually. Using the Socratic method, I ask many questions of the students. The questions can be as simple as “What do we do next?” or “What are options of what we can do?”

Once during a classroom observation, I was told that in a span of 10 minutes, I asked more than 72 questions. This models the questions that the students can use in self-talk to guide them in the problem-solving process. After the first test, many students say that they could hear my voice asking them the same questions over and over, but what they’re really learning are advanced problem-solving skills they can extend to future contexts.

We can also provide deeper understanding with questions such as “Why do we do that?” These provide reasoning and value to the actions of each step in the problem-solving process, further solidifying the students’ understanding of the concepts and skills.

3. Include discussion for planning for each problem. Teachers instinctively plan problems. Students, as novice learners, often do not know how to plan a problem. They look at a problem, see it as foreign, and don’t know where to begin. They give up.

Research shows that planning how to solve the problem is an essential step for novice learners. Provide a structure or protocol for students. It can include the following: identify and write the data with units for a problem, identify equations to be used, identify and write what they’re trying to solve for, draw a relevant vector diagram, and brainstorm possible steps.

4. Emphasize the process, not final answers. Often, when checking individual work, we ask for the final answers. But what if instead of asking who has the answer, we ask who has the method to solve it? When students ask for correct answers, it’s natural to provide an immediate response. Instead, we should reply with guiding questions to facilitate the process of their solving the problems for themselves.

Often, I don’t even calculate the answer in the final step and ask if we all agree on the steps. The conversation is especially valuable when different methods are volunteered, and we can analyze the advantages of each. I want the students to check our work and not look at a simple result at the end of the problem to confirm their work. This shifts students’ attention to look at the details of the steps and not glance at the end of the work for the final answer. Further, grading can include points for steps and not the final solution.

5. Teach explicitly problem solving. After solving problems, students can create their own problem-solving strategy that they write on a note card. Collect responses from students and create a class protocol that you post on your learning management system or in your physical classroom space. Scaffold further with a two-column approach. In the left column, students show the work, and in the right column, they explain and justify what they did and why. The act of adding a justification will make students think about their actions. This will improve the connection between conceptual ideas and the problem-solving itself.

These are only a few strategies to get your students intentionally thinking about problem-solving from a general perspective beyond focusing on specific problems and memorizing steps. There are many ways to model and teach the skill of problem-solving that encourage them to think about the process explicitly.

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• Problem Solving in STEM

Solving problems is a key component of many science, math, and engineering classes.  If a goal of a class is for students to emerge with the ability to solve new kinds of problems or to use new problem-solving techniques, then students need numerous opportunities to develop the skills necessary to approach and answer different types of problems.  Problem solving during section or class allows students to develop their confidence in these skills under your guidance, better preparing them to succeed on their homework and exams. This page offers advice about strategies for facilitating problem solving during class.

How do I decide which problems to cover in section or class?

In-class problem solving should reinforce the major concepts from the class and provide the opportunity for theoretical concepts to become more concrete. If students have a problem set for homework, then in-class problem solving should prepare students for the types of problems that they will see on their homework. You may wish to include some simpler problems both in the interest of time and to help students gain confidence, but it is ideal if the complexity of at least some of the in-class problems mirrors the level of difficulty of the homework. You may also want to ask your students ahead of time which skills or concepts they find confusing, and include some problems that are directly targeted to their concerns.

You have given your students a problem to solve in class. What are some strategies to work through it?

• Try to give your students a chance to grapple with the problems as much as possible.  Offering them the chance to do the problem themselves allows them to learn from their mistakes in the presence of your expertise as their teacher. (If time is limited, they may not be able to get all the way through multi-step problems, in which case it can help to prioritize giving them a chance to tackle the most challenging steps.)
• When you do want to teach by solving the problem yourself at the board, talk through the logic of how you choose to apply certain approaches to solve certain problems.  This way you can externalize the type of thinking you hope your students internalize when they solve similar problems themselves.
• Start by setting up the problem on the board (e.g you might write down key variables and equations; draw a figure illustrating the question).  Ask students to start solving the problem, either independently or in small groups.  As they are working on the problem, walk around to hear what they are saying and see what they are writing down. If several students seem stuck, it might be a good to collect the whole class again to clarify any confusion.  After students have made progress, bring the everyone back together and have students guide you as to what to write on the board.
• It can help to first ask students to work on the problem by themselves for a minute, and then get into small groups to work on the problem collaboratively.
• If you have ample board space, have students work in small groups at the board while solving the problem.  That way you can monitor their progress by standing back and watching what they put up on the board.
• If you have several problems you would like to have the students practice, but not enough time for everyone to do all of them, you can assign different groups of students to work on different – but related - problems.

When do you want students to work in groups to solve problems?

• Don’t ask students to work in groups for straightforward problems that most students could solve independently in a short amount of time.
• Do have students work in groups for thought-provoking problems, where students will benefit from meaningful collaboration.
• Even in cases where you plan to have students work in groups, it can be useful to give students some time to work on their own before collaborating with others.  This ensures that every student engages with the problem and is ready to contribute to a discussion.

What are some benefits of having students work in groups?

• Students bring different strengths, different knowledge, and different ideas for how to solve a problem; collaboration can help students work through problems that are more challenging than they might be able to tackle on their own.
• In working in a group, students might consider multiple ways to approach a problem, thus enriching their repertoire of strategies.
• Students who think they understand the material will gain a deeper understanding by explaining concepts to their peers.

What are some strategies for helping students to form groups?  

• Instruct students to work with the person (or people) sitting next to them.
• Count off.  (e.g. 1, 2, 3, 4; all the 1’s find each other and form a group, etc)
• Hand out playing cards; students need to find the person with the same number card. (There are many variants to this.  For example, you can print pictures of images that go together [rain and umbrella]; each person gets a card and needs to find their partner[s].)
• Based on what you know about the students, assign groups in advance. List the groups on the board.
• Note: Always have students take the time to introduce themselves to each other in a new group.

What should you do while your students are working on problems?

• Walk around and talk to students. Observing their work gives you a sense of what people understand and what they are struggling with. Answer students’ questions, and ask them questions that lead in a productive direction if they are stuck.
• If you discover that many people have the same question—or that someone has a misunderstanding that others might have—you might stop everyone and discuss a key idea with the entire class.

After students work on a problem during class, what are strategies to have them share their answers and their thinking?

• Ask for volunteers to share answers. Depending on the nature of the problem, student might provide answers verbally or by writing on the board. As a variant, for questions where a variety of answers are relevant, ask for at least three volunteers before anyone shares their ideas.
• Use online polling software for students to respond to a multiple-choice question anonymously.
• If students are working in groups, assign reporters ahead of time. For example, the person with the next birthday could be responsible for sharing their group’s work with the class.
• Cold call. To reduce student anxiety about cold calling, it can help to identify students who seem to have the correct answer as you were walking around the class and checking in on their progress solving the assigned problem. You may even want to warn the student ahead of time: "This is a great answer! Do you mind if I call on you when we come back together as a class?"
• Have students write an answer on a notecard that they turn in to you.  If your goal is to understand whether students in general solved a problem correctly, the notecards could be submitted anonymously; if you wish to assess individual students’ work, you would want to ask students to put their names on their notecard.  
• Use a jigsaw strategy, where you rearrange groups such that each new group is comprised of people who came from different initial groups and had solved different problems.  Students now are responsible for teaching the other students in their new group how to solve their problem.
• Have a representative from each group explain their problem to the class.
• Have a representative from each group draw or write the answer on the board.

What happens if a student gives a wrong answer?

• Ask for their reasoning so that you can understand where they went wrong.
• Ask if anyone else has other ideas. You can also ask this sometimes when an answer is right.
• Cultivate an environment where it’s okay to be wrong. Emphasize that you are all learning together, and that you learn through making mistakes.
• Do make sure that you clarify what the correct answer is before moving on.
• Once the correct answer is given, go through some answer-checking techniques that can distinguish between correct and incorrect answers. This can help prepare students to verify their future work.

How can you make your classroom inclusive?

• The goal is that everyone is thinking, talking, and sharing their ideas, and that everyone feels valued and respected. Use a variety of teaching strategies (independent work and group work; allow students to talk to each other before they talk to the class). Create an environment where it is normal to struggle and make mistakes.
• See Kimberly Tanner’s article on strategies to promoste student engagement and cultivate classroom equity. 

A few final notes…

• Make sure that you have worked all of the problems and also thought about alternative approaches to solving them.
• Board work matters. You should have a plan beforehand of what you will write on the board, where, when, what needs to be added, and what can be erased when. If students are going to write their answers on the board, you need to also have a plan for making sure that everyone gets to the correct answer. Students will copy what is on the board and use it as their notes for later study, so correct and logical information must be written there.

For more information...

Tipsheet: Problem Solving in STEM Sections

Tanner, K. D. (2013). Structure matters: twenty-one teaching strategies to promote student engagement and cultivate classroom equity . CBE-Life Sciences Education, 12(3), 322-331.

• Designing Your Course
• A Teaching Timeline: From Pre-Term Planning to the Final Exam
• The First Day of Class
• Group Agreements
• Classroom Debate
• Flipped Classrooms
• Leading Discussions
• Polling & Clickers
• Teaching with Cases
• Engaged Scholarship
• Devices in the Classroom
• Beyond the Classroom
• On Professionalism
• Getting Feedback
• Equitable & Inclusive Teaching
• Advising and Mentoring
• Teaching and Your Career
• Teaching Remotely
• Tools and Platforms
• The Science of Learning
• Bok Publications
• Other Resources Around Campus

Our site is BRAND NEW . Using our creative problem-solving skills we have repositioned ourselves. FPSPI is now using the Future Problem Solving name. A new cleaner look. More content. Easier navigation. More upgrades to come!

Global Issues

Community projects, creative writing, storytelling, problem-solving method, real world issues, future scenarios.

• Authentic Assessments

5Cs of Learning

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• DEIB Commitment
• International Conference
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Future-Ready

Discover our education programs, world finals​ june 5-9, 2024.

Join us at our International Conference to celebrate 50 years. At Indiana University Bloomington this year, our highest level competition brings together thousands of champion problem solvers.

Ready for work, life, and to create a better future

Our proven educational outcomes are life changing for students. We prepare young people to find solutions, take relevant action, and be a force for positive change. Our model ignites curiosity in real world issues and equips students with complex problem-solving skills. Once learned, these skills ensure students are ready to succeed in their classes today and in their work and life tomorrow. And in the age of AI, it’s more important than ever to make sure young people learn how to think and solve problems.

As our world and educators are confronted with a range of unprecedented challenges, Future Problem Solving helps students keep pace. Our standard-based and skill-based programs meaningfully engage young people in all the places and spaces they learn. With Future Problem Solving, students learn how to think, not what to think, and gain lifelong learning skills.

Our Competition Programs

Problem-solving skills stay for life, k-12 students each year, states within the u.s., countries around the world, years of equipping problem-solvers, our approach, building student agency.

Our proven 6-step process equips students with a problem-solving model to develop relevant action plans for any situation.

Our problem-solving situations highlight important challenges from business, civics, science, society, and technology.

Authentic Assessment

Our rubric-based evaluations provide learner-focused feedback to assess student learning and strengthen important skills.

Our future scenes are imagined storylines that present creative and futuristic problems to solve with current topic information.

Our interdisciplinary problem-solving process infuses important 21st Century Learning skills throughout all our programs.

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The future we want.

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Real issues engage and inspire learning.

Air Quality

How will the quality of air, a globally shared resource essential for human health and prosperity, impact us in the future?

Artificial Intelligence (AI)

How will the emerging uses of artificial intelligence (AI) impact how we work, live, play, and learn in the future?

How will emerging technologies and changing economies impact how the world uses currency in the future?

Throwaway Society

How will “throw-away” consumerism impact the environment, businesses, and consumers in the future?

Future Problem Solving Students – A Five Year Study

A comparison of reading and mathematics performance between students participating in a future problem solving program and nonparticipants.

Data from the The Minnesota Comprehensive Assessment (MCA) was collected by Grandview Middle School and provided to Scholastic Testing Service, Inc. for statistical analysis.

Findings reported by Scholastic Testing Service, Inc. Performance data on the MCA was collected from 2010-2014 for students in grade 6 at Grandview Middle School in Mound, MN (Westonka Public School District). Students were identified as either FPS: students participating in a Future Problem Solving program, or Non-FPS: students not participating in the program. Summary statistics using Reading and Mathematics Scaled Scores were developed for each group of students by year and across years. To determine if the mean scores across the years were significantly different, t-tests were used. A Cohen’s d test was then performed to measure the effect of the size of the found differences.

In all cases, students participating in the Future Problem Solving Program performed significantly higher on the MCA in both areas of Mathematics and Reading.

Effects of Group Training in Problem-Solving Style on Future Problem-Solving Performance

The journal of creative behavior (jcb) of the creative education foundation.

Seventy-five participants from one suburban high school formed 21 teams with 3–4 members each for Future Problem Solving (FPS). Students were selected to participate in either the regular FPS or an enhanced FPS, where multiple group training activities grounded in problem-solving style were incorporated into a 9-week treatment period.

An ANCOVA procedure was used to examine the difference in team responses to a creative problem-solving scenario for members of each group, after accounting for initial differences in creative problem-solving performance, years of experience in FPS, and creative thinking related to fluency, flexibility, and originality. The ANCOVA resulted in a significant difference in problem-solving performance in favor of students in the treatment group (F(1, 57) = 8.21, p = .006, partial eta squared = .126, medium), while there were no significant differences in years of experience or creativity scores. This result led researchers to conclude that students in both groups had equivalent creative ability and that participation in the group activities emphasizing problem-solving style significantly contributed to creative performance.

In the comparison group, a total of 47% had scores that qualified for entry to the state competition. In contrast, 89% of the students in the treatment group had scores that qualified them for the state bowl. None of the teams from the comparison group qualified for the international competition, while two teams from the treatment group were selected, with one earning sixth place.

The results of this study suggest that problem-solving performance by team members can be improved through direct instruction in problem-solving style, particularly when there is a focus on group dynamics.

The Journal of Creative Behavior, Vol. 0, Iss. 0, pp. 1–12 © 2017 by the Creative Education Foundation, Inc. DOI: 10.1002/jocb.176

Future Problem Solving Program International—Second Generation Study

“how important was future problem solving in the development of your following skill sets”.

In 2011, a team of researchers from the University of Virginia submitted a report titled “Future Problem Solving Program International—Second Generation Study.” (Callahan, Alimin, & Uguz, 2012). The study, based on a survey, collected data from over 150 Future Problem Solving alumni to understand the impact of their participation in Future Problem Solving as students or volunteers.

Percentage of Alumni Rating Important and Extremely Important in Developing Skill Sets

• 96% Look at the “Big Picture”
• 93% Critical Thinking
• 93% Teamwork and Collaboration
• 93% Identify and Solve Problems
• 93% Time Management
• 90% Researching
• 90% Evaluation and Decision Making
• 86% Creativity and Innovation
• 86% Written Communication

The report captured alumni’s positive experiences as students in Future Problem Solving and documented that the alumni continued to utilize the FPS-structured approach to solving problems in their adult lives.

Executive Director

A seasoned educator, April Michele has served as the Executive Director since 2018 and been with Future Problem Solving more than a decade. Her background in advanced curriculum strategies and highly engaging learning techniques translates well in the development of materials, publications, training, and marketing for the organization and its global network. April’s expertise includes pedagogy and strategies for critical and creative thinking and providing quality educational services for students and adults worldwide.

Prior to joining Future Problem Solving, April taught elementary and middle grades, spending most of her classroom career in gifted education. She earned the National Board certification (NBPTS) as a Middle Childhood/Generalist and later served as a National Board assessor for the certification of others. In addition, April facilitated the Theory and Development of Creativity course for the state of Florida’s certification of teachers. She has also collaborated on a variety of special projects through the Department of Education. Beyond her U.S. education credentials, she has been trained for the International Baccalaureate Middle Years Programme (MYP) in Humanities.

A graduate of the University of Central Florida with a bachelor’s in Elementary Education and the University of South Florida with a master’s in Gifted Education, April’s passion is providing a challenging curriculum for 21st century students so they are equipped with the problem-solving and ethical leadership skills they need to thrive in the future. As a board member in her local Rotary Club, she facilitates problem solving in leadership at the Rotary Youth Leadership Awards (RYLA). She is also a certified Project Management Professional (PMP) from the Project Management Institute and earned her certificate in Nonprofit Management from the Edyth Bush Institute at Rollins College.

10 Ways to Tackle Education’s Urgent Challenges

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To America’s resilient educators:

Take a moment to reflect on your many accomplishments during the pandemic, as well as the challenges you have faced.

You’ve supported your teams, your students, your school families and communities, all while balancing your own lives. In spite of every obstacle, you pushed through because that’s what you do. Every day.

And then, this spring, the sun seemed to shine a bit brighter. The safe and reliable vaccines that were slowing the spread of the virus forecasted a return to a normal-ish school year ahead. But COVID-19 had another plan, and its name was the Delta variant.

So here we are. And it’s complicated.

The cover of this year’s Big Ideas report from Education Week and the 10 essays inside reflect this moment and the constellation of emotions we know you’re experiencing: hope, excitement, grief, urgency, trepidation, and a deep sense of purpose.

In the report, we ask hard questions about education’s big challenges and offer some solutions. Keep scrolling for a roundup of these challenges and some new ways to think about them.

The report also includes results from an exclusive survey on educator stress, what you did well during the pandemic, and more .

Please connect with us on social media by using #K12BigIdeas or by emailing [email protected] . May the year ahead be a safe and fruitful one for you.

1. Schools are doing too much

We’re asking schools to accomplish more than what their funding allows and we’re asking their employees to do far more than they’ve been trained to do. Read more.

2. Student homelessness

The pandemic has only made student homelessness situation more volatile. Schools don’t have to go it alone. Read more.

3. Racism in schools

Born and raised in India, reporter Eesha Pendharkar isn’t convinced that America’s anti-racist efforts are enough to make students of color feel like they belong. Read more.

4. Teacher mental health

The pandemic has put teachers through the wringer. Administrators must think about their educators’ well-being differently. Read more.

5. Educator grief

Faced with so many loses stemming from the pandemic, what can be done to help teachers manage their own grief? Read more.

6. The well-being of school leaders

By overlooking the well-being of their school leaders, districts could limit how much their schools can flourish. Read more.

7. Remote learning

Educators in schools who were technologically prepared for the pandemic say the remote-learning emergency has provided new opportunities to explore better ways to connect with students and adapt instruction. Read more.

8. Setting students up for success

Educators know a lot more about students’ home learning environments than before the pandemic. How might schools build on that awareness and use it to improve their future work? Read more.

9. Parent engagement

When school went remote, families got a better sense of what their children were learning. It’s something schools can build on, if they can make key cultural shifts. Read more.

10. Knowing your purpose

We can’t build resilient schools until we agree on what education’s core role should be. And right now, we don’t agree. Read more.

A version of this article appeared in the September 15, 2021 edition of Education Week as Editor’s Note

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Article contents

Problem solving.

• Richard E. Mayer Richard E. Mayer University of California, Santa Barbara
• https://doi.org/10.1093/acrefore/9780190264093.013.860
• Published online: 30 October 2019

Problem solving refers to cognitive processing directed at achieving a goal when the problem solver does not initially know a solution method. A problem exists when someone has a goal but does not know how to achieve it. Problems can be classified as routine or non-routine, and as well-defined or ill-defined. The major cognitive processes in problem solving are representing, planning, executing, and monitoring. The major kinds of knowledge required for problem solving are facts, concepts, procedures, strategies, and beliefs. The theoretical approaches that have developed over the history of research on problem are associationism, Gestalt, and information processing. Each of these approaches involves fundamental issues in problem solving such as the nature of transfer, insight, and goal-directed heuristics, respectively. Some current research topics in problem solving include decision making, intelligence and creativity, teaching of thinking skills, expert problem solving, analogical reasoning, mathematical and scientific thinking, everyday thinking, and the cognitive neuroscience of problem solving. Common theme concerns the domain specificity of problem solving and a focus on problem solving in authentic contexts.

• problem solving
• decision making
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• expert problem solving
• analogical reasoning
• mathematical thinking
• scientific thinking
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Teaching Problem-Solving Skills

Many instructors design opportunities for students to solve “problems”. But are their students solving true problems or merely participating in practice exercises? The former stresses critical thinking and decision­ making skills whereas the latter requires only the application of previously learned procedures.

Problem solving is often broadly defined as "the ability to understand the environment, identify complex problems, review related information to develop, evaluate strategies and implement solutions to build the desired outcome" (Fissore, C. et al, 2021). True problem solving is the process of applying a method – not known in advance – to a problem that is subject to a specific set of conditions and that the problem solver has not seen before, in order to obtain a satisfactory solution.

Below you will find some basic principles for teaching problem solving and one model to implement in your classroom teaching.

Principles for teaching problem solving

• Model a useful problem-solving method . Problem solving can be difficult and sometimes tedious. Show students how to be patient and persistent, and how to follow a structured method, such as Woods’ model described below. Articulate your method as you use it so students see the connections.
• Teach within a specific context . Teach problem-solving skills in the context in which they will be used by students (e.g., mole fraction calculations in a chemistry course). Use real-life problems in explanations, examples, and exams. Do not teach problem solving as an independent, abstract skill.
• Help students understand the problem . In order to solve problems, students need to define the end goal. This step is crucial to successful learning of problem-solving skills. If you succeed at helping students answer the questions “what?” and “why?”, finding the answer to “how?” will be easier.
• Take enough time . When planning a lecture/tutorial, budget enough time for: understanding the problem and defining the goal (both individually and as a class); dealing with questions from you and your students; making, finding, and fixing mistakes; and solving entire problems in a single session.
• Ask questions and make suggestions . Ask students to predict “what would happen if …” or explain why something happened. This will help them to develop analytical and deductive thinking skills. Also, ask questions and make suggestions about strategies to encourage students to reflect on the problem-solving strategies that they use.
• Link errors to misconceptions . Use errors as evidence of misconceptions, not carelessness or random guessing. Make an effort to isolate the misconception and correct it, then teach students to do this by themselves. We can all learn from mistakes.

Woods’ problem-solving model

Define the problem.

• The system . Have students identify the system under study (e.g., a metal bridge subject to certain forces) by interpreting the information provided in the problem statement. Drawing a diagram is a great way to do this.
• Known(s) and concepts . List what is known about the problem, and identify the knowledge needed to understand (and eventually) solve it.
• Unknown(s) . Once you have a list of knowns, identifying the unknown(s) becomes simpler. One unknown is generally the answer to the problem, but there may be other unknowns. Be sure that students understand what they are expected to find.
• Units and symbols . One key aspect in problem solving is teaching students how to select, interpret, and use units and symbols. Emphasize the use of units whenever applicable. Develop a habit of using appropriate units and symbols yourself at all times.
• Constraints . All problems have some stated or implied constraints. Teach students to look for the words "only", "must", "neglect", or "assume" to help identify the constraints.
• Criteria for success . Help students consider, from the beginning, what a logical type of answer would be. What characteristics will it possess? For example, a quantitative problem will require an answer in some form of numerical units (e.g., $/kg product, square cm, etc.) while an optimization problem requires an answer in the form of either a numerical maximum or minimum.

Think about it

• “Let it simmer”.  Use this stage to ponder the problem. Ideally, students will develop a mental image of the problem at hand during this stage.
• Identify specific pieces of knowledge . Students need to determine by themselves the required background knowledge from illustrations, examples and problems covered in the course.
• Collect information . Encourage students to collect pertinent information such as conversion factors, constants, and tables needed to solve the problem.

Plan a solution

• Consider possible strategies . Often, the type of solution will be determined by the type of problem. Some common problem-solving strategies are: compute; simplify; use an equation; make a model, diagram, table, or chart; or work backwards.
• Choose the best strategy . Help students to choose the best strategy by reminding them again what they are required to find or calculate.

Carry out the plan

• Be patient . Most problems are not solved quickly or on the first attempt. In other cases, executing the solution may be the easiest step.
• Be persistent . If a plan does not work immediately, do not let students get discouraged. Encourage them to try a different strategy and keep trying.

Encourage students to reflect. Once a solution has been reached, students should ask themselves the following questions:

• Does the answer make sense?
• Does it fit with the criteria established in step 1?
• Did I answer the question(s)?
• What did I learn by doing this?
• Could I have done the problem another way?

If you would like support applying these tips to your own teaching, CTE staff members are here to help.  View the  CTE Support  page to find the most relevant staff member to contact. 

• Fissore, C., Marchisio, M., Roman, F., & Sacchet, M. (2021). Development of problem solving skills with Maple in higher education. In: Corless, R.M., Gerhard, J., Kotsireas, I.S. (eds) Maple in Mathematics Education and Research. MC 2020. Communications in Computer and Information Science, vol 1414. Springer, Cham. https://doi.org/10.1007/978-3-030-81698-8_15
• Foshay, R., & Kirkley, J. (1998). Principles for Teaching Problem Solving. TRO Learning Inc., Edina MN.  (PDF) Principles for Teaching Problem Solving (researchgate.net)
• Hayes, J.R. (1989). The Complete Problem Solver. 2nd Edition. Hillsdale, NJ: Lawrence Erlbaum Associates.
• Woods, D.R., Wright, J.D., Hoffman, T.W., Swartman, R.K., Doig, I.D. (1975). Teaching Problem solving Skills.
• Engineering Education. Vol 1, No. 1. p. 238. Washington, DC: The American Society for Engineering Education.

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The global education challenge: Scaling up to tackle the learning crisis

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Alice albright alice albright chief executive officer - global partnership for education @alicealbright.

July 25, 2019

The following is one of eight briefs commissioned for the 16th annual Brookings Blum Roundtable, “2020 and beyond: Maintaining the bipartisan narrative on US global development.”

Addressing today’s massive global education crisis requires some disruption and the development of a new 21st-century aid delivery model built on a strong operational public-private partnership and results-based financing model that rewards political leadership and progress on overcoming priority obstacles to equitable access and learning in least developed countries (LDCs) and lower-middle-income countries (LMICs). Success will also require a more efficient and unified global education architecture. More money alone will not fix the problem. Addressing this global challenge requires new champions at the highest level and new approaches.

Key data points

In an era when youth are the fastest-growing segment of the population in many parts of the world, new data from the UNESCO Institute for Statistics (UIS) reveals that an estimated 263 million children and young people are out of school, overwhelmingly in LDCs and LMICs. 1 On current trends, the International Commission on Financing Education Opportunity reported in 2016 that, a far larger number—825 million young people—will not have the basic literacy, numeracy, and digital skills to compete for the jobs of 2030. 2 Absent a significant political and financial investment in their education, beginning with basic education, there is a serious risk that this youth “bulge” will drive instability and constrain economic growth.

Despite progress in gender parity, it will take about 100 years to reach true gender equality at secondary school level in LDCs and LMICs. Lack of education and related employment opportunities in these countries presents national, regional, and global security risks.

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Among global education’s most urgent challenges is a severe lack of trained teachers, particularly female teachers. An additional 9 million trained teachers are needed in sub-Saharan Africa by 2030.

Refugees and internally displaced people, now numbering over 70 million, constitute a global crisis. Two-thirds of the people in this group are women and children; host countries, many fragile themselves, struggle to provide access to education to such people.

Highlighted below are actions and reforms that could lead the way toward solving the crisis:

• Leadership to jump-start transformation. The next U.S. administration should convene a high-level White House conference of sovereign donors, developing country leaders, key multilateral organizations, private sector and major philanthropists/foundations, and civil society to jump-start and energize a new, 10-year global response to this challenge. A key goal of this decadelong effort should be to transform education systems in the world’s poorest countries, particularly for girls and women, within a generation. That implies advancing much faster than the 100-plus years required if current programs and commitments remain as is.
• A whole-of-government leadership response. Such transformation of currently weak education systems in scores of countries over a generation will require sustained top-level political leadership, accompanied by substantial new donor and developing country investments. To ensure sustained attention for this initiative over multiple years, the U.S. administration will need to designate senior officials in the State Department, USAID, the National Security Council, the Office of Management and Budget, and elsewhere to form a whole-of-government leadership response that can energize other governments and actors.
• Teacher training and deployment at scale. A key component of a new global highest-level effort, based on securing progress against the Sustainable Development Goals and the Addis 2030 Framework, should be the training and deployment of 9 million new qualified teachers, particularly female teachers, in sub-Saharan Africa where they are most needed. Over 90 percent of the Global Partnership for Education’s education sector implementation grants have included investments in teacher development and training and 76 percent in the provision of learning materials.
• Foster positive disruption by engaging community level non-state actors who are providing education services in marginal areas where national systems do not reach the population. Related to this, increased financial and technical support to national governments are required to strengthen their non-state actor regulatory frameworks. Such frameworks must ensure that any non-state actors operate without discrimination and prioritize access for the most marginalized. The ideological divide on this issue—featuring a strong resistance by defenders of public education to tap into the capacities and networks of non-state actors—must be resolved if we are to achieve a rapid breakthrough.
• Confirm the appropriate roles for technology in equitably advancing access and quality of education, including in the initial and ongoing training of teachers and administrators, delivery of distance education to marginalized communities and assessment of learning, strengthening of basic systems, and increased efficiency of systems. This is not primarily about how various gadgets can help advance education goals.
• Commodity component. Availability of appropriate learning materials for every child sitting in a classroom—right level, right language, and right subject matter. Lack of books and other learning materials is a persistent problem throughout education systems—from early grades through to teaching colleges. Teachers need books and other materials to do their jobs. Consider how the USAID-hosted Global Book Alliance, working to address costs and supply chain issues, distribution challenges, and more can be strengthened and supported to produce the model(s) that can overcome these challenges.

Annual high-level stock take at the G-7. The next U.S. administration can work with G-7 partners to secure agreement on an annual stocktaking of progress against this new global education agenda at the upcoming G-7 summits. This also will help ensure sustained focus and pressure to deliver especially on equity and inclusion. Global Partnership for Education’s participation at the G-7 Gender Equality Advisory Council is helping ensure that momentum is maintained to mobilize the necessary political leadership and expertise at country level to rapidly step up progress in gender equality, in and through education. 3 Also consider a role for the G-20, given participation by some developing country partners.

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• “263 Million Children and Youth Are Out of School.” UNESCO UIS. July 15, 2016. http://uis.unesco.org/en/news/263-million-children-and-youth-are-out-school.
• “The Learning Generation: Investing in education for a changing world.” The International Commission on Financing Global Education Opportunity. 2016. https://report.educationcommission.org/downloads/.
• “Influencing the most powerful nations to invest in the power of girls.” Global Partnership for Education. March 12, 2019. https://www.globalpartnership.org/blog/influencing-most-powerful-nations-invest-power-girls.

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Problem-Solving Model for Improving Student Achievement

Principal Leadership Magazine, Vol. 5, Number 4, December 2004

Counseling 101 column, a problem-solving model for improving student achievement.

Problem solving is an alternative to assessments and diagnostic categories as a means to identify students who need special services.

By Andrea Canter

Andrea Canter recently retired from Minneapolis Public Schools where she served as lead psychologist and helped implement a district-wide problem solving model. She currently is a consultant to the National Association of School Psychologists (NASP) and editor of its newspaper, Communiquè . “Counseling 101” is provided by NASP ( www.nasponline.org ).

The implementation of the No Child Left Behind Act (NCLB) has prompted renewed efforts to hold schools and students accountable for meeting high academic standards. At the same time, Congress has been debating the reauthorization of the Individuals With Disabilities Education Act (IDEA), which has heightened concerns that NCLB will indeed “leave behind” many students who have disabilities or other barriers to learning. This convergence of efforts to address the needs of at-risk students while simultaneously implementing high academic standards has focused attention on a number of proposals and pilot projects that are generally referred to as problem-solving models. A more specific approach to addressing academic difficulties, response to intervention (RTI), has often been proposed as a component of problem solving.

What Is Problem Solving?

A problem-solving model is a systematic approach that reviews student strengths and weaknesses, identifies evidence-based instructional interventions, frequently collects data to monitor student progress, and evaluates the effectiveness of interventions implemented with the student. Problem solving is a model that first solves student difficulties within general education classrooms. If problem-solving interventions are not successful in general education classrooms, the cycle of selecting intervention strategies and collecting data is repeated with the help of a building-level or grade-level intervention assistance or problem-solving team. Rather than relying primarily on test scores (e.g., from an IQ or math test), the student’s response to general education interventions becomes the primary determinant of his or her need for special education evaluation and services (Marston, 2002; Reschly & Tilly, 1999).

Why Is a New Approach Needed?

Although much of the early implementation of problem-solving models has involved elementary schools, problem solving also has significant potential to improve outcomes for secondary school students. Therefore, it is important for secondary school administrators to understand the basic concepts of problem solving and consider how components of this model could mesh with the needs of their schools and students. Because Congress will likely include RTI options in its reauthorization of special education law and regulations regarding learning disabilities, it is also important for school personnel to be familiar with the pros and cons of the problem-solving model.

Student outcomes. Regardless of state or federal mandates, schools need to change the way they address academic problems. More than 25 years of special education legislation and funding have failed to demonstrate either the cost effectiveness or the validity of aligning instruction to diagnostic classifications (Fletcher et al., 2002; Reschly & Tilly, 1999; Ysseldyke & Marston, 1999). Placement in special education programs has not guaranteed significant academic gains or better life outcomes for students with disabilities. Time-consuming assessments that are intended to differentiate students with disabilities from those with low achievement have not resulted in better instruction for struggling students.

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Dilemma of learning disabilities. The learning disabilities (LD) classification has proven especially problematic. Researchers and policymakers representing diverse philosophies regarding disability are generally in agreement that the current process needs revision (Fletcher et al., 2002). Traditionally, if a student with LD is to be served in special education, an evaluation using individual intelligence tests and norm-referenced achievement tests is required to document an ability/achievement discrepancy. This model has been criticized for the following reasons:

• A reliance on intelligence tests in general and with students from ethnic and linguistic minority populations in particular
• A focus on within-child deficiencies that often ignore quality of instruction and environmental factors
• The limited applicability of norm-referenced information to actual classroom teaching
• The burgeoning identification of students as disabled
• The resulting allocation of personnel to responsibilities (classification) that are significantly removed from direct service to students (Ysseldyke & Marston, 1999).

Wait to fail. A major flaw in the current system of identifying student needs is what has been dubbed the wait to fail approach in which students are not considered eligible for support until their skills are widely discrepant from expectations. This runs counter to years of research demonstrating the importance of early intervention (President’s Commission on Excellence in Special Education, 2002). Thus, a number of students fail to receive any remedial services until they reach the intermediate grades or middle school, by which time they often exhibit motivational problems and behavioral problems as well as academic deficits.

For other students, although problems are noted when they are in the early grades, referral is delayed until they fail graduation or high school standards tests, increasing the probability that they will drop out. Their school records often indicate that teachers and parents expressed concern for these students in the early grades, which sometimes resulted in referral for assessments, but did not result in qualification for special education or other services.

Call for evidence-based programs. One of the major tenets of NCLB is the implementation of scientifically based interventions to improve student performance. The traditional models used by most schools today lack such scientifically based evidence. There are, however, many programs and instructional strategies that have demonstrated positive outcomes for diverse student populations and needs (National Reading Panel, 2000). It is clear that schools need systemic approaches to identify and resolve student achievement problems and access proven instructional strategies.

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How It Works

Although problem-solving steps can be described in several stages, the steps essentially reflect the scientific method of defining and describing a problem (e.g., Ted does not comprehend grade-level reading material); generating potential solutions (e.g., Ted might respond well to direct instruction in comprehension strategies); and implementing, monitoring, and evaluating the effectiveness of the selected intervention.

Problem-solving models have been implemented in many versions at local and state levels to reflect the unique features and needs of individual schools. However, all problem-solving models share the following components:

• Screening and assessment that is focused on student skills rather than classification
• Measuring response to instruction rather than relying on norm-referenced comparisons
• Using evidence-based strategies within general education classrooms
• Developing a collaborative partnership among general and special educators for consultation and team decision making.

Three-tiered model. One common problem-solving model is the three-tiered model. In this model, tier one includes problem-solving strategies directed by the teacher within the general education classrooms. Tier two includes problem-solving efforts at a team level in which grade-level staff members or a team of various school personnel collaborate to develop an intervention plan that is still within the general education curriculum. Tier three involves referral to a special education team for additional problem solving and, potentially, a special education assessment (Office of Special Education Programs, 2002).

Response to intervention. A growing body of research and public policy discussion has focused on problem-solving models that include evaluating a student’s RTI as an alternative to the IQ-achievement discrepancy approach to identifying learning disabilities (Gresham, 2002). RTI refers to specific procedures that align with the steps of problem solving:

• Implementing evidence-based interventions
• Frequently measuring a student’s progress to determine whether the intervention is effective
• Evaluating the quality of the instructional strategy
• Evaluating the fidelity of its implementation. (For example, did the intervention work? Was it scientifically based? Was it implemented as planned?)

Although there is considerable debate about replacing traditional eligibility procedures with RTI approaches (Vaughn & Fuchs, 2003), there is promising evidence that RTI can systematically improve the effectiveness of instruction for struggling students and provide school teams with evidence-based procedures that measures a student’s progress and his or her need for special services.

New roles for personnel. An important component of problem-solving models is the allocation (or realignment) of personnel who are knowledgeable about the applications of research to classroom practice. Whereas traditional models often limit the availability of certain personnel-for example, school psychologists-to prevention and early intervention activities (e.g., classroom consultation), problem-solving models generally enhance the roles of these service providers through a systemic process that is built upon general education consultation. Problem solving shifts the emphasis from identifying disabilities to implementing earlier interventions that have the potential to reduce referral and placement in special education.

Outcomes of Problem Solving and RTI

Anticipated benefits of problem-solving models, particularly those using RTI procedures, include emphasizing scientifically proven instructional methods, the early identification and remediation of achievement difficulties, more functional and frequent measurement of student progress, a reduction in inappropriate and disproportionate special education placements of students from diverse cultural and linguistic backgrounds, and a reallocation of instructional and behavior support personnel to better meet the needs of all students (Gresham, 2002; Ysseldyke & Marston, 1999). By using problem solving, some districts have reduced overall special education placements, increased individual and group performance on standards tests, and increased collaboration among special and general educators.

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The enhanced collaboration between general education teachers and support personnel is particularly important at the secondary level because staff members often have limited interaction with school personnel who are outside of their specialty area. Problem solving provides a vehicle to facilitate communication across disciplines to resolve student difficulties in the classroom. Secondary schools, however, face additional barriers to collaboration because each student may have five or more teachers. Special education is often even more separated from general education in secondary school settings. Secondary school teachers also have a greater tendency to see themselves as content specialists and may be less invested in addressing general learning problems, particularly when they teach five or six class periods (and 150 or more students) each day. The sheer size of the student body and the staff can create both funding and logistical difficulties for scheduling training and team meetings.

Is Problem Solving Worth the Effort?

Data from district-wide and state-level projects in rural, suburban, and urban communities around the country support the need to thoughtfully implement problem-solving models at all grade levels. There are several federally funded demonstration centers that systematically collect information about these approaches. Although national demonstration models may be a few years away, it seems likely that state and federal regulations under IDEA will include problem solving and RTI as accepted experimental options. Problem solving continues to offer much promise to secondary school administrators who are seeking to improve student performance through ongoing assessment and evidence-based instruction. PL

• Fletcher, J., Lyon, R., Barnes, M., Stuebing, K., Francis, D., Olson, R., Shaywitz, S., & Shaywitz, B. (2002). Classification of learning disabilities: An evidence-based evaluation. In R. Bradley, L. Donaldson, & D. Hallahan (Eds.), Identification of learning disabilities (pp. 185-250). Mahwah, NJ: Erlbaum.
• Gresham, F. (2002). Responsiveness to intervention: An alternative approach to the identification of learning disabilities. In R. Bradley, L. Donaldson, & D. Hallahan (Eds.), Identification of learning disabilities (pp. 467-519). Mahwah, NJ: Erlbaum.
• Marston, D. (2002). A functional and intervention-based assessment approach to establishing discrepancy for students with learning disabilities. In R. Bradley, L. Donaldson, & D. Hallahan (Eds.), Identification of learning disabilities (pp. 437-447). Mahwah, NJ: Erlbaum.
• National Reading Panel. (2000). Teaching children to read: An evidence-based assessment of the scientific literature on reading and its implications for reading instruction-Reports of the subgroups. Washington, DC: Author.
• Office of Special Education Programs, U.S. Department of Education. (2002). Specific learning disabilities: Finding common ground (Report of the Learning Disabilities Round Table). Washington, DC: Author.
• President’s Commission on Excellence in Special Education. (2002). A new era: Revitalizing special education for children and their families. Washington, DC: U.S. Department of Education.
• Reschly, D., & Tilly, W. D. III (1999). Reform trends and system design alternatives. In D. Reschly, W. D. Tilly III, & J. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 19-48). Longmont, CO: Sopris West.
• Vaughn, S., & Fuchs, L. (Eds.) (2003). Special issue: Response to intervention. Learning Disabilities Research & Practice, 18(3).
• Ysseldyke, J., & Marston, D. (1999). Origins of categorical special education services in schools and a rationale for changing them. In D. Reschly, W. D. Tilly III, & J. Grimes (Eds.), Special education in transition: Functional assessment and noncategorical programming (pp. 1-18). Longmont, CO: Sopris West.

Case Study: Optimizing Success Through Problem Solving

By Marcia Staum and Lourdes Ocampo

Milwaukee Public Schools, the largest school district in Wisconsin, is educating students with Optimizing Success Through Problem Solving (OSPS), a problem-solving initiative that uses a four-step, data-based, decision-making process to enhance school reform efforts. OSPS is patterned after best practices in the prevention literature and focuses on prevention, early intervention, and focused intervention levels.  Problem-solving facilitators provide staff members with the training, modeling, support, and tools they need to effectively use data to drive their instructional decision-making. The OSPS initiative began in the fall of 2000 with seven participating schools. Initially, elementary and middle level schools began to use OSPS, with an emphasis on problem solving for individual student issues. As the initiative matured, increased focus was placed on prevention and early intervention support in the schools. Today, 78 schools participate in the OSPS initiative and are serviced by a team of 18 problem-solving facilitators. 

OSPS in Action: Juneau High School

The administration of Juneau High School, a Milwaukee public charter school with 900 students, invited OSPS to become involved at Juneau for the 2003-2004 school year. Because at the time OSPS had limited involvement with high schools, two problem-solving facilitators were assigned to Juneau for one half-day each week. The problem-solving facilitators immediately joined the Juneau’s learning team, which is a small group of staff members and administrators who make educational decisions aimed at increasing student achievement.

When the problem-solving facilitators became involved with Juneau, the learning team was working to improve student participation on the Wisconsin Knowledge and Concepts Exam (WKCE). The previous year, Juneau’s 10th-grade participation on the exam had been very low. The learning team used OSPS’s four-step problem-solving process to develop and implement a plan that resulted in a 99% student participation rate on the WKCE. After this initial success, the problem-solving model was also used at Juneau to increase parent participation in parent-teacher conferences. According to Myron Cain, Juneau’s principal, “Problem solving has helped the learning team at Juneau go from dialogue into action. In addition, problem solving has supported the school within the Collaborative Support Team process and with teambuilding, which resulted in a better school climate.”

By starting at the prevention level, Juneau found that there was increased commitment from staff members. OSPS is now in the initial stages of working with Juneau to explore alternatives to suspension.  The goal is to create a working plan that will lead to creative ways of decreasing the number of suspensions at Juneau.

Marcia Staum is a school psychologist, and Lourdes Ocampo is a school social worker for Optimizing Success Through Problem Solving.

What Is Response to Intervention?

Many researchers have recommended that a student’s response to intervention or response to instruction (RTI) should be considered as an alternative or replacement to the traditional IQ-achievement discrepancy approach to identifying learning disabilities (Gresham, 2002; President’s Commission on Excellence in Special Education, 2002). Although there is considerable debate about replacing traditional eligibility procedures with RTI approaches (Vaughn & Fuchs, 2003), there is promising evidence that RTI can systematically improve the effectiveness of instruction for struggling students and provide school teams with evidence-based procedures to measure student progress and need for special services. In fact, Congress has proposed the use of research-based RTI methods (as part of a comprehensive evaluation process to reauthorize IDEA) as an allowable alternative to the use of an IQ-achievement discrepancy procedure in identifying learning disabilities.

RTI refers to specific procedures that align with the steps of problem solving. These steps include the implementation of evidence-based instructional strategies in the general education classroom and the frequent measurement of a student’s progress to determine if the intervention is effective. In settings where RTI is also a criteria for identification of disability, a student’s progress in response to intervention is an important determinant of the need and eligibility for special education services.

It is important for administrators to recognize that RTI can be implemented in various ways depending on a school’s overall service delivery model and state and federal mandates. An RTI approach benefits from the involvement of specially trained personnel, such as school psychologists and curriculum specialists, who have expertise in instructional consultation and evaluation.

• National Center on Student Progress Monitoring, www.studentprogress.org
• National Research Center on Learning Disabilities, www.nrcld.org

This article was adapted from a handout published in Helping Children at Home and School II: Handouts for Families and Educators (NASP, 2004). “Counseling 101” articles and related HCHS II handouts can be downloaded from www.naspcenter.org/principals .

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Jamaludin, A., & Hung, D. W. L. (2016). Digital "learning trails": Scaling technology-facilitated curricular innovation in schools with a rhizomatic lens. Journal of Educational Change , 17 (3), 355–377.

Kahneman, D. (2011). Thinking, fast and slow . New York: Farrar, Strauss, &amp; Giroux.

National Academy of Sciences. (2010). Rising above the gathering storm, revisited: Rapidly approaching category 5. Washington, DC: National Academies Press.

McNeill, K. L., González-Howard, M., Katsh-Singer, R., & Loper, S. (2017). Moving beyond pseudoargumentation: Teachers' enactments of an educative science curriculum focused on argumentation. Science Education , 101 (3), 426–457.

Ng, P. T. (2017). Learning from Singapore: The power of paradoxes . New York: Routledge.

OECD. (2012). PISA 2012 results: Creative problem solving. Paris: OECD.

Patchen, A. K., Zhang, L., & Barnett, M. (2017). Growing plants and scientists: Fostering positive attitudes toward science among all participants in an afterschool hydroponics program. Journal of Science and Educational Technology , 26 (3), 279–294.

Prensky, M. R. (2012). From digital natives to digital wisdom: Hopeful essays for 21st century learning. Thousand Oaks, CA: Corwin.

Shirley, D. (2016). The new imperatives of educational change: Achievement with integrity . New York: Routledge.

• 1 Read more about the Jurong Secondary School project .

He has conducted in-depth studies about school innovations in England, Germany, Canada, and South Korea. Shirley has been a visiting professor at Harvard University in the United States, Venice International University in Italy, the National Institute of Education in Singapore, the University of Barcelona in Spain, and the University of Stavanger in Norway. He is a fellow of the Royal Society of Arts. Shirley’s previous book is The New Imperatives of Educational Change: Achievement with Integrity .

Pak Tee Ng is Associate Dean, Leadership Learning at the National Institute of Education of Nanyang Technological University in Singapore and the author of Learning from Singapore: The Power of Paradoxes (Routledge, 2017).

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Top 8 modern education problems and ways to solve them.

| September 15, 2017 | 0 responses

In many ways, today’s system is better than the traditional one. Technology is the biggest change and the greatest advantage at the same time. Various devices, such as computers, projectors, tablets and smartphones, make the process of learning simpler and more fun. The Internet gives both students and teachers access to limitless knowledge.

However, this is not the perfect educational system. It has several problems, so we have to try to improve it.

•  Problem: The Individual Needs of Low-Achievers Are Not Being Addressed

Personalized learning is the most popular trend in education. The educators are doing their best to identify the learning style of each student and provide training that corresponds to their needs.

However, many students are at risk of falling behind, especially children who are learning mathematics and reading. In the USA, in particular, there are large gaps in science achievements by middle school.

Solution: Address the Needs of Low-Achievers

The educators must try harder to reduce the number of students who are getting low results on long-term trajectories. If we identify these students at an early age, we can provide additional training to help them improve the results.

• Problem: Overcrowded Classrooms

In 2016, there were over 17,000 state secondary school children in the UK being taught in classes of 36+ pupils.

Solution: Reduce the Number of Students in the Classroom

Only a smaller class can enable an active role for the student and improve the level of individual attention they get from the teacher.

• Problem: The Teachers Are Expected to Entertain

Today’s generations of students love technology, so the teachers started using technology just to keep them engaged. That imposes a serious issue: education is becoming an entertainment rather than a learning process.

Solution: Set Some Limits

We don’t have to see education as opposed to entertainment. However, we have to make the students aware of the purpose of technology and games in the classroom. It’s all about learning.

• Problem: Not Having Enough Time for Volunteering in University

The students are overwhelmed with projects and assignments. There is absolutely no space for internships and volunteering in college .

Solution: Make Internships and Volunteering Part of Education

When students graduate, a volunteering activity can make a great difference during the hiring process. In addition, these experiences help them develop into complete persons. If the students start getting credits for volunteering and internships, they will be willing to make the effort.

• Problem: The Parents Are Too Involved

Due to the fact that technology became part of the early educational process, it’s necessary for the parents to observe the way their children use the Internet at home. They have to help the students to complete assignments involving technology.

What about those parents who don’t have enough time for that? What if they have time, but want to use it in a different way?

Solution: Stop Expecting Parents to Act Like Teachers at Home

The parent should definitely support their child throughout the schooling process. However, we mustn’t turn this into a mandatory role. The teachers should stop assigning homework that demands parental assistance.

• Problem: Outdated Curriculum

Although we transformed the educational system, many features of the curriculum remained unchanged.

Solution: Eliminate Standardised Exams

This is a radical suggestion. However, standardised exams are a big problem. We want the students to learn at their own pace. We are personalizing the process of education. Then why do we expect them to compete with each other and meet the same standards as everyone else? The teacher should be the one responsible of grading.

• Problem: Not All Teachers Can Meet the Standards of the New Educational System

Can we really expect all teachers to use technology? Some of them are near the end of their teaching careers and they have never used tablets in the lecturing process before.

Solution: Provide Better Training for the Teachers

If we want all students to receive high-quality education based on the standards of the system, we have to prepare the teachers first. They need more training, preparation, and even tests that prove they can teach today’s generations of students.

• Problem: Graduates Are Not Ready for What Follows

A third of the employers in the UK are not happy with the performance of recent graduates. That means the system is not preparing them well for the challenges that follow.

Solution: More Internships, More Realistic Education

Practical education – that’s a challenge we still haven’t met. We have to get more practical.

The evolution of the educational system is an important process. Currently, we have a system that’s more suitable to the needs of generations when compared to the traditional system. However, it’s still not perfect. The evolution never stops.

Author Bio:   Chris Richardson is a journalist, editor, and a blogger. He loves to write, learn new things, and meet new outgoing people. Chris is also fond of traveling, sports, and playing the guitar. Follow him on Facebook and Google+ .

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The Algebra Problem: How Middle School Math Became a National Flashpoint

Top students can benefit greatly by being offered the subject early. But many districts offer few Black and Latino eighth graders a chance to study it.

By Troy Closson

From suburbs in the Northeast to major cities on the West Coast, a surprising subject is prompting ballot measures, lawsuits and bitter fights among parents: algebra.

Students have been required for decades to learn to solve for the variable x, and to find the slope of a line. Most complete the course in their first year of high school. But top-achievers are sometimes allowed to enroll earlier, typically in eighth grade.

The dual pathways inspire some of the most fiery debates over equity and academic opportunity in American education.

Do bias and inequality keep Black and Latino children off the fast track? Should middle schools eliminate algebra to level the playing field? What if standout pupils lose the chance to challenge themselves?

The questions are so fraught because algebra functions as a crucial crossroads in the education system. Students who fail it are far less likely to graduate. Those who take it early can take calculus by 12th grade, giving them a potential edge when applying to elite universities and lifting them toward society’s most high-status and lucrative professions.

But racial and economic gaps in math achievement are wide in the United States, and grew wider during the pandemic. In some states, nearly four in five poor children do not meet math standards.

To close those gaps, New York City’s previous mayor, Bill de Blasio, adopted a goal embraced by many districts elsewhere. Every middle school would offer algebra, and principals could opt to enroll all of their eighth graders in the class. San Francisco took an opposite approach: If some children could not reach algebra by middle school, no one would be allowed to take it.

The central mission in both cities was to help disadvantaged students. But solving the algebra dilemma can be more complex than solving the quadratic formula.

New York’s dream of “algebra for all” was never fully realized, and Mayor Eric Adams’s administration changed the goal to improving outcomes for ninth graders taking algebra. In San Francisco, dismantling middle-school algebra did little to end racial inequities among students in advanced math classes. After a huge public outcry, the district decided to reverse course.

“You wouldn’t think that there could be a more boring topic in the world,” said Thurston Domina, a professor at the University of North Carolina. “And yet, it’s this place of incredibly high passions.”

“Things run hot,” he said.

In some cities, disputes over algebra have been so intense that parents have sued school districts, protested outside mayors’ offices and campaigned for the ouster of school board members.

Teaching math in middle school is a challenge for educators in part because that is when the material becomes more complex, with students moving from multiplication tables to equations and abstract concepts. Students who have not mastered the basic skills can quickly become lost, and it can be difficult for them to catch up.

Many school districts have traditionally responded to divergent achievement levels by simply separating children into distinct pathways, placing some in general math classes while offering others algebra as an accelerated option. Such sorting, known as tracking, appeals to parents who want their children to reach advanced math as quickly as possible.

But tracking has cast an uncomfortable spotlight on inequality. Around a quarter of all students in the United States take algebra in middle school. But only about 12 percent of Black and Latino eighth graders do, compared with roughly 24 percent of white pupils, a federal report found .

“That’s why middle school math is this flashpoint,” said Joshua Goodman, an associate professor of education and economics at Boston University. “It’s the first moment where you potentially make it very obvious and explicit that there are knowledge gaps opening up.”

In the decades-long war over math, San Francisco has emerged as a prominent battleground.

California once required that all eighth graders take algebra. But lower-performing middle school students often struggle when forced to enroll in the class, research shows. San Francisco later stopped offering the class in eighth grade. But the ban did little to close achievement gaps in more advanced math classes, recent research has found.

As the pendulum swung, the only constant was anger. Leading Bay Area academics disparaged one another’s research . A group of parents even sued the district last spring. “Denying students the opportunity to skip ahead in math when their intellectual ability clearly allows for it greatly harms their potential for future achievement,” their lawsuit said.

The city is now back to where it began: Middle school algebra — for some, not necessarily for all — will return in August. The experience underscored how every approach carries risks.

“Schools really don’t know what to do,” said Jon R. Star, an educational psychologist at Harvard who has studied algebra education. “And it’s just leading to a lot of tension.”

In Cambridge, Mass., the school district phased out middle school algebra before the pandemic. But some argued that the move had backfired: Families who could afford to simply paid for their children to take accelerated math outside of school.

“It’s the worst of all possible worlds for equity,” Jacob Barandes, a Cambridge parent, said at a school board meeting.

Elsewhere, many students lack options to take the class early: One of Philadelphia’s most prestigious high schools requires students to pass algebra before enrolling, preventing many low-income children from applying because they attend middle schools that do not offer the class.

In New York, Mr. de Blasio sought to tackle the disparities when he announced a plan in 2015 to offer algebra — but not require it — in all of the city’s middle schools. More than 15,000 eighth graders did not have the class at their schools at the time.

Since then, the number of middle schools that offer algebra has risen to about 80 percent from 60 percent. But white and Asian American students still pass state algebra tests at higher rates than their peers.

The city’s current schools chancellor, David Banks, also shifted the system’s algebra focus to high schools, requiring the same ninth-grade curriculum at many schools in a move that has won both support and backlash from educators.

And some New York City families are still worried about middle school. A group of parent leaders in Manhattan recently asked the district to create more accelerated math options before high school, saying that many young students must seek out higher-level instruction outside the public school system.

In a vast district like New York — where some schools are filled with children from well-off families and others mainly educate homeless children — the challenge in math education can be that “incredible diversity,” said Pedro A. Noguera, the dean of the University of Southern California’s Rossier School of Education.

“You have some kids who are ready for algebra in fourth grade, and they should not be denied it,” Mr. Noguera said. “Others are still struggling with arithmetic in high school, and they need support.”

Many schools are unequipped to teach children with disparate math skills in a single classroom. Some educators lack the training they need to help students who have fallen behind, while also challenging those working at grade level or beyond.

Some schools have tried to find ways to tackle the issue on their own. KIPP charter schools in New York have added an additional half-hour of math time to many students’ schedules, to give children more time for practice and support so they can be ready for algebra by eighth grade.

At Middle School 50 in Brooklyn, where all eighth graders take algebra, teachers rewrote lesson plans for sixth- and seventh-grade students to lay the groundwork for the class.

The school’s principal, Ben Honoroff, said he expected that some students would have to retake the class in high school. But after starting a small algebra pilot program a few years ago, he came to believe that exposing children early could benefit everyone — as long as students came into it well prepared.

Looking around at the students who were not enrolling in the class, Mr. Honoroff said, “we asked, ‘Are there other kids that would excel in this?’”

“The answer was 100 percent, yes,” he added. “That was not something that I could live with.”

Troy Closson reports on K-12 schools in New York City for The Times. More about Troy Closson

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WHAT AI WILL DO — AND WHAT IT STILL CAN’T

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What the AI Pessimists Are Missing

The current debate about generative AI focuses disproportionately on the disruption it might unleash. While it is true technological advances always disrupt legacy industries and existing systems and processes, one must not ignore the opportunities they can create or the risks they can mitigate.

WASHINGTON, DC – Pessimism suffuses current discussions about generative artificial intelligence. A YouGov survey in March found that Americans primarily feel “cautious” or “concerned” about AI, whereas only one in five are “hopeful” or “excited.” Around four in ten are very or somewhat concerned that AI could put an end to the human race.

Such fears illustrate the human tendency to focus more on what could be lost than on what could be gained from technological change. Advances in AI will cause disruption. But creative destruction creates as well as destroys, and that process ultimately is beneficial. Often, the problems created by a new technology can also be solved by it. We are already seeing this with AI, and we will see more of it in the coming years.

Recall the panic that swept   through schools and universities when OpenAI first demonstrated that its ChatGPT tool can write in natural language. Many educators raised valid concerns that generative AI would help students cheat on assignments and exams, shortchanging their educations. But the same technology that enables this abuse also enables detection and prevention of it.

Moreover, generative AI can help to improve education quality. The longstanding classroom model of education faces serious challenges. Aptitude and preparation vary widely across students within a given classroom, as do styles of learning and levels of engagement, attention, and focus. In addition, the quality of teaching varies across classrooms.

AI could address these issues by acting as a private tutor for every student. If a particular student learns math best by playing math games, AI can play math games. If another student learns better by quietly working on problems and asking for help when needed, AI can accommodate that. If one student is falling behind while another in the same classroom has already mastered the material and grown bored, AI tutors can work on remediation with the former student and more challenging material with the latter. AI systems will also serve as customized teaching assistants, helping teachers develop lesson plans and shape classroom instruction.

The economic benefits of these applications would be substantial. When every child has a private AI tutor, educational outcomes will improve overall, with less-advantaged students and pupils in lower-quality schools likely benefiting disproportionately. These better-educated students will then grow into more productive workers who can command higher wages. They also will be wiser citizens, capable of brightening the outlook for democracy. Because democracy is a foundation for long-term prosperity, this, too, will have salutary economic effects.

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Many commentators worry that AI will undermine democracy by supercharging misinformation and disinformation. They ask us to imagine a “deep fake” of, say, President Joe Biden announcing that the United States is withdrawing from NATO, or perhaps of Donald Trump suffering a medical event. Such a viral video might be so convincing as to affect public opinion in the run-up to the November election.

But while deep fakes of political leaders and candidates for high office are a real threat, concerns about AI-driven risks to democracy are overblown. Again, the same technology that allows for deep fakes and other forms of information warfare can also be deployed to counter them. Such tools are already being introduced. For example, SynthID, a watermarking tool developed by Google DeepMind, imbues AI-generated content with a digital signature that is imperceptible to humans but detectable by software. Three months ago, OpenAI added watermarks to all images generated by ChatGPT.

Will AI weapons create a more dangerous world? It is too early to say. But as with the examples above, the same technology that can create better offensive weapons can also create better defenses. Many experts believe that AI will increase security by mitigating the “defender’s dilemma”: the asymmetry whereby bad actors need to succeed only once, whereas defensive systems must work every time.

In February, Google CEO Sundar Pichai reported that his firm had developed a large language model designed specifically for cyber defense and threat intelligence. “Some of our tools are already up to 70 per cent better at detecting malicious scripts and up to 300 per cent more effective at identifying files that exploit vulnerabilities,” he wrote .

The same logic applies to national-security threats. Military strategists worry that swarms of low-cost, easy-to-make drones could threaten large, expensive aircraft carriers, fighter jets, and tanks – all systems that the US military relies on – if they are controlled and coordinated by AI. But the same underlying technology is already being used to create defenses against such attacks.

Finally, many experts and citizens are concerned about AI displacing human workers. But, as I wrote a few months ago, this common fear reflects a zero-sum mentality that misunderstands how economies evolve. Though generative AI will displace many workers, it also will create new opportunities. Work in the future will look vastly different from work today because generative AI will create new goods and services whose production will require human labor. A similar process happened with previous technological advances. As the MIT economist David Autor and his colleagues have shown , the majority of today’s jobs are in occupations introduced after 1940.

The current debate around generative AI focuses disproportionately on the disruption it might unleash. But technological advances not only disrupt; they also create. There will always be bad actors seeking to wreak havoc with new technologies. Fortunately, there is an enormous financial incentive to counter such risks, as well as to preserve and generate profits.

The personal computer and the internet empowered thieves, facilitated the spread of false information, and led to substantial labor-market disruptions. Yet very few today would turn back the clock. History should inspire confidence – but not complacency – that generative AI will lead to a better world.

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10 of the highest-paying IT jobs right now

If you’re looking for a well-paying, in-demand job that rewards problem-solving skills, a career in information technology might be a good fit for you. The field of IT encompasses computer systems, programming languages, software, data, information processing, and storage to create, secure, and exchange electronic data. 

Even with recent layoffs in the tech sector, Gaurav Jetley, assistant professor of computer information systems in Colorado State University ’s College of Business, says not to worry.

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“IT jobs are still in demand,” Jetley says. “We will see more jobs open up later this year, hopefully.”

And it appears to be true: According to the U.S. Bureau of Labor Statistics, 377,500 job openings are projected each year, with a median annual wage for computer and information technology occupations of $104,420 in May 2023.

For those who are interested in pursuing IT jobs, here are 10 of the field’s top-paying roles.

10. Principal Software Engineer  

Top-paying companies: Microsoft, USAA, MITRE

Description: Principal Software Engineers lead teams of engineers to create high-quality, scalable software to achieve an organization’s goals. This role develops and tests software; they are also responsible for reviewing code written by other engineers, identifying the right technology to meet an organization’s needs, and creating architecture for complex software systems.

Average base salary: $111,822, according to Indeed .

Top-paying locations: New York, N.Y. ($165,480), Atlanta, Ga. ($157,432), Chicago, Ill. ($147,257), according to Indeed .

9. Information Security and Cybersecurity Engineers and Architects  

Top-paying companies: Capital One, MITRE, Honeywell

Description: Information Security and Cybersecurity Engineers and Architects are IT professionals who work alongside developers to make sure that software, systems, applications, and networks are secure. 

These roles may also respond to security risks faced by organizations, such as cyberattacks, security incidents, and data breaches. While architects are responsible for designing cybersecurity systems, engineers focus on building and maintaining cybersecurity infrastructure.

“These are folks who are at the forefront of technology,” Jetley says. “They have to be proactive. They have to be updated on what’s happening, what kind of new threats are emerging, and to take steps to mitigate these things.”

Average base salary: $112,619, according to Indeed .

Top-paying locations: Charlotte, N.C. ($162,158), Raleigh, N.C. ($146,450), Washington, D.C. ($122,770), according to Indeed .

8. DevOps Engineer  

Top-paying companies: Capital One, Boeing, Northrop Grumman

Description: DevOps Engineers manage an organization’s IT infrastructure. This role updates and maintains software processes with the aim of fixing bugs and improving user experience. DevOps engineers have a strong focus on automation and coordinate all teams involved with a product’s development.

“These are very technically savvy folks that basically manage the entire IT infrastructure,” Jetley says. 

Average base salary: $125,152, according to Indeed .

Top-paying locations: Palo Alto, Calif. ($157,688), San Francisco, Calif. ($153,008), Herndon, Va. ($148,683), according to Indeed .

7. Chief Information Officer  

Top-paying companies: Cisco, Walt Disney Company, Adobe

Description: Chief Information Officers (CIOs) are responsible for managing and implementing an organization’s information and computer technology systems. This executive position figures out which technologies will benefit an organization, improve business processes, and integrate systems that help an organization achieve their goals.

“This position is not about the nitty gritty but looking at the overall strategy for the entire company,” Jetley says. “They also take care of the implementation of systems.”

Average base s alary: $128,101, according to Indeed .

Top-paying locations: New York, N.Y. ($211,773), Austin, Texas ($180,626), Washington, D.C. ($163,990), according to Indeed .

6. Solutions Architect  

Top-paying companies: Cisco, IBM, Amazon.com

Description: Solutions Architects develop, build, and implement an organization’s systems architecture to meet customer and business needs. This role evaluates an organization’s existing system architecture and figures out solutions to change, improve, and modernize. 

“You usually have a solutions architect in companies that are employing a cloud solution. They design these solutions,” Jetley says. “These days we’re seeing an uptick in cloud solutions architects because of AI. Most AI is running in the cloud these days.”

Average base salary: $128,106, according to Payscale .

Top-paying locations: San Francisco, Calif. ($148,014), New York, N.Y. ($135,266), Chicago, Ill. ($132,515), according to Payscale .

5. Director of Information Technology  

Top-paying companies: Oracle, Bristol Myers Squibb, USAA

Description: IT Directors manage the information technology and computer systems of an organization under the CIO. This position makes sure that an organization’s tech solutions adequately manage the security, accessibility, and functionality of their IT framework. They also ensure proper communication between chief executives and the IT department.

Average base salary: $130,896, according to Indeed .

Top-paying locations: San Jose, Calif. ($193,636), St. Louis, Mo. ($176,150), New York, N.Y. ($159,317), according to Indeed .

4. Data Architect  

Top-paying companies: Amazon.com, Accenture, IBM

Description: Data Architects design, deploy, and manage the data infrastructure of an organization. This role formulates an organization’s entire data strategy, including analyzing existing databases, planning future ones, and implementing data storage and management solutions. As practically every company employs data, this role is useful in every industry.

“They define how the data will be stored in the company, how it will be consumed,” Jetley explains.

Average base salary: $132,442, according to Payscale .

Top-paying locations: Washington, D.C. ($153,480), New York, N.Y. ($149,160), Minneapolis, Minn. ($122,717), according to Payscale .

3. Application Architect  

Description: Application Architects manage the development and troubleshooting of applications. Whether overseeing a team of developers or working with clients to plan and design applications, this role addresses programming and coding issues to improve products. This position requires someone to be both a master developer and an experienced leader.

Average base salary: $138,429, according to Indeed .

Top-paying locations: San Jose, Calif. ($173,364), San Francisco, Calif. ($161,567), Washington, D.C. ($153,720), according to Indeed .

2. Vice President of Information Technology

Top-paying companies: Oracle, Centene, USAA

Description: Vice Presidents (VPs) of Information Technology are tasked with overseeing the IT operations of an organization, including its infrastructure, security, data management, and software applications. VPs of IT direct and manage schedules, IT plans, programs, and policies related to an organization’s management of information systems, computer services, data processing, network communications, and business operations.

Average base salary: $167,619, according to Indeed .

Top-paying locations: Arlington Heights, Ill. ($228,699), San Diego, Calif. ($213,387), Dallas, Texas ($211,544), according to Indeed .

1. Chief Technology Officer  

Top-paying companies: Capital One, Bloomberg, AFL-CIO

Description: Chief Technology Officers (CTOs) manage an organization’s technological needs and oversee its research and development efforts. CTOs consider the needs of an organization and make investments to help them reach their goals. They also use technology to improve products that serve customers.

Average base salary: $186,703, according to Indeed .

Top-paying locations: San Diego, Calif. ($298,291), Seattle, Wash. ($255,930), New York, N.Y. ($224,111), according to Indeed .

The takeaway  

If you’re willing to put in the time and effort, the field of IT is a rewarding one for continuous learners who love to problem solve. For those who are just getting started, it’s a good idea to pursue certifications or a bachelor’s degree related to IT. Jetley recommends concentrating on a specialty.

“Have a general understanding of many specialties, but digging deep into one specialty is key,” Jetley says. “For that, you have to spend a considerable amount of time learning these systems.”

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