what is problem solving in educational psychology

Chapter 9: Facilitating Complex Thinking

Problem-solving.

Somewhat less open-ended than creative thinking is problem solving , the analysis and solution of tasks or situations that are complex or ambiguous and that pose difficulties or obstacles of some kind (Mayer & Wittrock, 2006). Problem solving is needed, for example, when a physician analyzes a chest X-ray: a photograph of the chest is far from clear and requires skill, experience, and resourcefulness to decide which foggy-looking blobs to ignore, and which to interpret as real physical structures (and therefore real medical concerns). Problem solving is also needed when a grocery store manager has to decide how to improve the sales of a product: should she put it on sale at a lower price, or increase publicity for it, or both? Will these actions actually increase sales enough to pay for their costs?

Example 1: Problem Solving in the Classroom

Problem solving happens in classrooms when teachers present tasks or challenges that are deliberately complex and for which finding a solution is not straightforward or obvious. The responses of students to such problems, as well as the strategies for assisting them, show the key features of problem solving. Consider this example, and students’ responses to it. We have numbered and named the paragraphs to make it easier to comment about them individually:

Scene #1: A problem to be solved

A teacher gave these instructions: “Can you connect all of the dots below using only four straight lines?” She drew the following display on the chalkboard:

The problem itself and the procedure for solving it seemed very clear: simply experiment with different arrangements of four lines. But two volunteers tried doing it at the board, but were unsuccessful. Several others worked at it at their seats, but also without success.

Scene #2: Coaxing students to re-frame the problem

When no one seemed to be getting it, the teacher asked, “Think about how you’ve set up the problem in your mind—about what you believe the problem is about. For instance, have you made any assumptions about how long the lines ought to be? Don’t stay stuck on one approach if it’s not working!”

Scene #3: Alicia abandons a fixed response

After the teacher said this, Alicia indeed continued to think about how she saw the problem. “The lines need to be no longer than the distance across the square,” she said to herself. So she tried several more solutions, but none of them worked either.

The teacher walked by Alicia’s desk and saw what Alicia was doing. She repeated her earlier comment: “Have you assumed anything about how long the lines ought to be?”

Alicia stared at the teacher blankly, but then smiled and said, “Hmm! You didn’t actually say that the lines could be no longer than the matrix! Why not make them longer?” So she experimented again using oversized lines and soon discovered a solution:

Scene #4: Willem’s and Rachel’s alternative strategies

Meanwhile, Willem worked on the problem. As it happened, Willem loved puzzles of all kinds, and had ample experience with them. He had not, however, seen this particular problem. “It must be a trick,” he said to himself, because he knew from experience that problems posed in this way often were not what they first appeared to be. He mused to himself: “Think outside the box, they always tell you. . .” And that was just the hint he needed: he drew lines outside the box by making them longer than the matrix and soon came up with this solution:

When Rachel went to work, she took one look at the problem and knew the answer immediately: she had seen this problem before, though she could not remember where. She had also seen other drawing-related puzzles, and knew that their solution always depended on making the lines longer, shorter, or differently angled than first expected. After staring at the dots briefly, she drew a solution faster than Alicia or even Willem. Her solution looked exactly like Willem’s.

This story illustrates two common features of problem solving: the effect of degree of structure or constraint on problem solving, and the effect of mental obstacles to solving problems. The next sections discuss each of these features, and then looks at common techniques for solving problems.

The effect of constraints: well-structured versus ill-structured problems

Problems vary in how much information they provide for solving a problem, as well as in how many rules or procedures are needed for a solution. A well-structured problem provides much of the information needed and can in principle be solved using relatively few clearly understood rules. Classic examples are the word problems often taught in math lessons or classes: everything you need to know is contained within the stated problem and the solution procedures are relatively clear and precise. An ill-structured problem has the converse qualities: the information is not necessarily within the problem, solution procedures are potentially quite numerous, and a multiple solutions are likely (Voss, 2006). Extreme examples are problems like “How can the world achieve lasting peace?” or “How can teachers insure that students learn?”

By these definitions, the nine-dot problem is relatively well-structured—though not completely. Most of the information needed for a solution is provided in Scene #1: there are nine dots shown and instructions given to draw four lines. But not all necessary information was given: students needed to consider lines that were longer than implied in the original statement of the problem. Students had to “think outside the box,” as Willem said—in this case, literally.

When a problem is well-structured, so are its solution procedures likely to be as well. A well-defined procedure for solving a particular kind of problem is often called an algorithm ; examples are the procedures for multiplying or dividing two numbers or the instructions for using a computer (Leiserson, et al., 2001). Algorithms are only effective when a problem is very well-structured and there is no question about whether the algorithm is an appropriate choice for the problem. In that situation it pretty much guarantees a correct solution. They do not work well, however, with ill-structured problems, where they are ambiguities and questions about how to proceed or even about precisely what the problem is about. In those cases it is more effective to use heuristics , which are general strategies—“rules of thumb,” so to speak—that do not always work, but often do, or that provide at least partial solutions. When beginning research for a term paper, for example, a useful heuristic is to scan the library catalogue for titles that look relevant. There is no guarantee that this strategy will yield the books most needed for the paper, but the strategy works enough of the time to make it worth trying.

In the nine-dot problem, most students began in Scene #1 with a simple algorithm that can be stated like this: “Draw one line, then draw another, and another, and another.” Unfortunately this simple procedure did not produce a solution, so they had to find other strategies for a solution. Three alternatives are described in Scenes #3 (for Alicia) and 4 (for Willem and Rachel). Of these, Willem’s response resembled a heuristic the most: he knew from experience that a good general strategy that often worked for such problems was to suspect a deception or trick in how the problem was originally stated. So he set out to question what the teacher had meant by the word line , and came up with an acceptable solution as a result.

Common obstacles to solving problems

The example also illustrates two common problems that sometimes happen during problem solving. One of these is functional fixedness : a tendency to regard the functions of objects and ideas as fixed (German & Barrett, 2005). Over time, we get so used to one particular purpose for an object that we overlook other uses. We may think of a dictionary, for example, as necessarily something to verify spellings and definitions, but it also can function as a gift, a doorstop, or a footstool. For students working on the nine-dot matrix described in the last section, the notion of “drawing” a line was also initially fixed; they assumed it to be connecting dots but not extending lines beyond the dots. Functional fixedness sometimes is also called response set , the tendency for a person to frame or think about each problem in a series in the same way as the previous problem, even when doing so is not appropriate to later problems. In the example of the nine-dot matrix described above, students often tried one solution after another, but each solution was constrained by a set response not to extend any line beyond the matrix.

Functional fixedness and the response set are obstacles in problem representation , the way that a person understands and organizes information provided in a problem. If information is misunderstood or used inappropriately, then mistakes are likely—if indeed the problem can be solved at all. With the nine-dot matrix problem, for example, construing the instruction to draw four lines as meaning “draw four lines entirely within the matrix” means that the problem simply could not be solved. For another, consider this problem: “The number of water lilies on a lake doubles each day. Each water lily covers exactly one square foot. If it takes 100 days for the lilies to cover the lake exactly, how many days does it take for the lilies to cover exactly half of the lake?” If you think that the size of the lilies affects the solution to this problem, you have not represented the problem correctly. Information about lily size is not relevant to the solution, and only serves to distract from the truly crucial information, the fact that the lilies double their coverage each day. (The answer, incidentally, is that the lake is half covered in 99 days; can you think why?)

Strategies to assist problem solving

Just as there are cognitive obstacles to problem solving, there are also general strategies that help the process be successful, regardless of the specific content of a problem (Thagard, 2005). One helpful strategy is problem analysis —identifying the parts of the problem and working on each part separately. Analysis is especially useful when a problem is ill-structured. Consider this problem, for example: “Devise a plan to improve bicycle transportation in the city.” Solving this problem is easier if you identify its parts or component subproblems, such as (1) installing bicycle lanes on busy streets, (2) educating cyclists and motorists to ride safely, (3) fixing potholes on streets used by cyclists, and (4) revising traffic laws that interfere with cycling. Each separate subproblem is more manageable than the original, general problem. The solution of each subproblem contributes the solution of the whole, though of course is not equivalent to a whole solution.

Another helpful strategy is working backward from a final solution to the originally stated problem. This approach is especially helpful when a problem is well-structured but also has elements that are distracting or misleading when approached in a forward, normal direction. The water lily problem described above is a good example: starting with the day when all the lake is covered (Day 100), ask what day would it therefore be half covered (by the terms of the problem, it would have to be the day before, or Day 99). Working backward in this case encourages reframing the extra information in the problem (i. e. the size of each water lily) as merely distracting, not as crucial to a solution.

A third helpful strategy is analogical thinking —using knowledge or experiences with similar features or structures to help solve the problem at hand (Bassok, 2003). In devising a plan to improve bicycling in the city, for example, an analogy of cars with bicycles is helpful in thinking of solutions: improving conditions for both vehicles requires many of the same measures (improving the roadways, educating drivers). Even solving simpler, more basic problems is helped by considering analogies. A first grade student can partially decode unfamiliar printed words by analogy to words he or she has learned already. If the child cannot yet read the word screen , for example, he can note that part of this word looks similar to words he may already know, such as seen or green , and from this observation derive a clue about how to read the word screen . Teachers can assist this process, as you might expect, by suggesting reasonable, helpful analogies for students to consider.

Bassok, J. (2003). Analogical transfer in problem solving. In Davidson, J. & Sternberg, R. (Eds.). The psychology of problem solving. New York: Cambridge University Press.

German, T. & Barrett, H. (2005). Functional fixedness in a technologically sparse culture. Psychological Science, 16 (1), 1–5.

Leiserson, C., Rivest, R., Cormen, T., & Stein, C. (2001). Introduction to algorithms. Cambridge, MA: MIT Press.

Luchins, A. & Luchins, E. (1994). The water-jar experiment and Einstellung effects. Gestalt Theory: An International Interdisciplinary Journal, 16 (2), 101–121.

Mayer, R. & Wittrock, M. (2006). Problem-solving transfer. In D. Berliner & R. Calfee (Eds.), Handbook of Educational Psychology, pp. 47–62. Mahwah, NJ: Erlbaum.

Thagard, R. (2005). Mind: Introduction to Cognitive Science, 2nd edition. Cambridge, MA: MIT Press.

Voss, J. (2006). Toulmin’s model and the solving of ill-structured problems. Argumentation, 19 (3), 321–329.

• Educational Psychology. Authored by : Kelvin Seifert and Rosemary Sutton. Located at : https://open.umn.edu/opentextbooks/BookDetail.aspx?bookId=153 . License : CC BY: Attribution

Facilitating Complex Thinking

Problem-Solving

Somewhat less open-ended than creative thinking is  problem-solving , the analysis and solution of tasks or situations that are complex or ambiguous and that pose difficulties or obstacles of some kind (Mayer & Wittrock, 2006). Problem-solving is needed, for example, when a physician analyzes a chest X-ray: a photograph of the chest is far from clear and requires skill, experience, and resourcefulness to decide which foggy-looking blobs to ignore, and which to interpret as real physical structures (and therefore real medical concerns). Problem-solving is also needed when a grocery store manager has to decide how to improve the sales of a product: should she put it on sale at a lower price, or increase publicity for it, or both? Will these actions actually increase sales enough to pay for their costs?

PROBLEM-SOLVING IN THE CLASSROOM

Problem-solving happens in classrooms when teachers present tasks or challenges that are deliberately complex and for which finding a solution is not straightforward or obvious. The responses of students to such problems, as well as the strategies for assisting them, show the key features of problem-solving. Consider this example and students’ responses to it. We have numbered and named the paragraphs to make it easier to comment about them individually:

Scene #1: A problem to be solved

A teacher gave these instructions: “Can you connect all of the dots below using only  four  straight lines?” She drew the following display on the chalkboard:

The problem itself and the procedure for solving it seemed very clear: simply experiment with different arrangements of four lines. But two volunteers tried doing it at the board, but were unsuccessful. Several others worked at it at their seats, but also without success.

Scene #2: Coaxing students to re-frame the problem

When no one seemed to be getting it, the teacher asked, “Think about how you’ve set up the problem in your mind—about what you believe the problem is about. For instance, have you made any assumptions about how long the lines ought to be? Don’t stay stuck on one approach if it’s not working!”

Scene #3: Alicia abandons a fixed response

After the teacher said this, Alicia indeed continued to think about how she saw the problem. “The lines need to be no longer than the distance across the square,” she said to herself. So she tried several more solutions, but none of them worked either.

The teacher walked by Alicia’s desk and saw what Alicia was doing. She repeated her earlier comment: “Have you assumed anything about how long the lines ought to be?”

Alicia stared at the teacher blankly, but then smiled and said, “Hmm! You didn’t actually  say  that the lines could be no longer than the matrix! Why not make them longer?” So she experimented again using oversized lines and soon discovered a solution:

Scene #4: Willem’s and Rachel’s alternative strategies

Meanwhile, Willem worked on the problem. As it happened, Willem loved puzzles of all kinds and had ample experience with them. He had not, however, seen this particular problem. “It  must  be a trick,” he said to himself because he knew from experience that problems posed in this way often were not what they first appeared to be. He mused to himself: “Think outside the box, they always tell you. . .” And  that  was just the hint he needed: he drew lines outside the box by making them longer than the matrix and soon came up with this solution:

When Rachel went to work, she took one look at the problem and knew the answer immediately: she had seen this problem before, though she could not remember where. She had also seen other drawing-related puzzles and knew that their solution always depended on making the lines longer, shorter, or differently angled than first expected. After staring at the dots briefly, she drew a solution faster than Alicia or even Willem. Her solution looked exactly like Willem’s.

This story illustrates two common features of problem-solving: the effect of degree of structure or constraint on problem-solving, and the effect of mental obstacles to solving problems. The next sections discuss each of these features and then look at common techniques for solving problems.

The Effect of Constraints: Well-Structured Versus Ill-Structured Problems

Problems vary in how much information they provide for solving a problem, as well as in how many rules or procedures are needed for a solution. A  well-structured problem  provides much of the information needed and can in principle be solved using relatively few clearly understood rules. Classic examples are the word problems often taught in math lessons or classes: everything you need to know is contained within the stated problem and the solution procedures are relatively clear and precise. An  ill-structured problem  has the converse qualities: the information is not necessarily within the problem, solution procedures are potentially quite numerous, and multiple solutions are likely (Voss, 2006). Extreme examples are problems like “How can the world achieve lasting peace?” or “How can teachers ensure that students learn?”

By these definitions, the nine-dot problem is relatively well-structured—though not completely. Most of the information needed for a solution is provided in Scene #1: there are nine dots shown and instructions given to draw four lines. But not  all  necessary information was given: students needed to consider lines that were longer than implied in the original statement of the problem. Students had to “think outside the box,” as Willem said—in this case, literally.

When a problem is well-structured, so are its solution procedures likely to be as well. A well-defined procedure for solving a particular kind of problem is often called an  algorithm ; examples are the procedures for multiplying or dividing two numbers or the instructions for using a computer (Leiserson, et al., 2001). Algorithms are only effective when a problem is very well-structured and there is no question about whether the algorithm is an appropriate choice for the problem. In that situation, it pretty much guarantees a correct solution. They do not work well, however, with ill-structured problems, where they are ambiguities and questions about how to proceed or even about precisely  what  the problem is about. In those cases, it is more effective to use  heuristics , which are general strategies—“rules of thumb,” so to speak—that do not always work but often do, or that provide at least partial solutions. When beginning research for a term paper, for example, a useful heuristic is to scan the library catalog for titles that look relevant. There is no guarantee that this strategy will yield the books most needed for the paper, but the strategy works enough of the time to make it worth trying.

In the nine-dot problem, most students began in Scene #1 with a simple algorithm that can be stated like this: “Draw one line, then draw another, and another, and another.” Unfortunately, this simple procedure did not produce a solution, so they had to find other strategies for a solution. Three alternatives are described in Scenes #3 (for Alicia) and 4 (for Willem and Rachel). Of these, Willem’s response resembled a heuristic the most: he knew from experience that a good  general  strategy that  often  worked for such problems was to suspect deception or trick in how the problem was originally stated. So he set out to question what the teacher had meant by the word  line  and came up with an acceptable solution as a result.

Common Obstacles to Solving Problems

The example also illustrates two common problems that sometimes happen during problem-solving. One of these is  functional fixedness : a tendency to regard the  functions  of objects and ideas as  fixed  (German & Barrett, 2005). Over time, we get so used to one particular purpose for an object that we overlook other uses. We may think of a dictionary, for example, as necessarily something to verify spellings and definitions, but it also can function as a gift, a doorstop, or a footstool. For students working on the nine-dot matrix described in the last section, the notion of “drawing” a line was also initially fixed; they assumed it to be connecting dots but not extending lines beyond the dots. Functional fixedness sometimes is also called  response set , the tendency for a person to frame or think about each problem in a series in the same way as the previous problem, even when doing so is not appropriate for later problems. In the example of the nine-dot matrix described above, students often tried one solution after another, but each solution was constrained by a set response not  to extend any line beyond the matrix.

Functional fixedness and the response set are obstacles in  problem representation , the way that a person understands and organizes information provided in a problem. If information is misunderstood or used inappropriately, then mistakes are likely—if indeed the problem can be solved at all. With the nine-dot matrix problem, for example, construing the instruction to draw four lines as meaning “draw four lines entirely within the matrix” means that the problem simply could not be solved. For another, consider this problem: “The number of water lilies on a lake doubles each day. Each water lily covers exactly one square foot. If it takes 100 days for the lilies to cover the lake exactly, how many days does it take for the lilies to cover exactly half of the lake?” If you think that the size of the lilies affects the solution to this problem, you have not represented the problem correctly. Information about lily size is  not  relevant to the solution and only serves to distract from the truly crucial information, the fact that the lilies  double  their coverage each day. (The answer, incidentally, is that the lake is half covered in 99 days; can you think why?)

Strategies to Assist Problem-Solving

Just as there are cognitive obstacles to problem-solving, there are also general strategies that help the process be successful, regardless of the specific content of a problem (Thagard, 2005). One helpful strategy is  problem analysis —identifying the parts of the problem and working on each part separately. Analysis is especially useful when a problem is ill-structured. Consider this problem, for example: “Devise a plan to improve bicycle transportation in the city.” Solving this problem is easier if you identify its parts or component subproblems, such as (1) installing bicycle lanes on busy streets, (2) educating cyclists and motorists to ride safely, (3) fixing potholes on streets used by cyclists, and (4) revising traffic laws that interfere with cycling. Each separate subproblem is more manageable than the original, general problem. The solution of each subproblem contributes to the solution of the whole, though of course is not equivalent to a whole solution.

Another helpful strategy is  working backward   from  a final solution to the originally stated problem. This approach is especially helpful when a problem is well-structured but also has elements that are distracting or misleading when approached in a forward, normal direction. The water lily problem described above is a good example: starting with the day when  all  the lake is covered (Day 100), ask what day would it, therefore, be half-covered (by the terms of the problem, it would have to be the day before, or Day 99). Working backward, in this case, encourages reframing the extra information in the problem (i. e. the size of each water lily) as merely distracting, not as crucial to a solution.

A third helpful strategy is  analogical thinking —using knowledge or experiences with similar features or structures to help solve the problem at hand (Bassok, 2003). In devising a plan to improve bicycling in the city, for example, an analogy of cars with bicycles is helpful in thinking of solutions: improving conditions for both vehicles requires many of the same measures (improving the roadways, educating drivers). Even solving simpler, more basic problems is helped by considering analogies. A first-grade student can partially decode unfamiliar printed words by analogy to words he or she has learned already. If the child cannot yet read the word screen , for example, he can note that part of this word looks similar to words he may already know, such as  seen  or  green,  and from this observation derive a clue about how to read the word  screen . Teachers can assist this process, as you might expect, by suggesting reasonable, helpful analogies for students to consider.

Video 5.4.1. Problem Solving explains strategies used for solving problems.

Many systems for problem-solving can be taught to learners (Pressley, 1995). There are problem-solving strategies to improve general problem solving (Burkell, Schneider, & Pressley, 1990; Mayer, 1987; Sternberg, 1988), scientific thinking (Kuhn, 1989), mathematical problem solving (Schoenfeld, 1989), and writing during the elementary years (Harris & Graham, 1992a) and during adolescence (Applebee, 1984; Langer & Applebee, 1987).

A problem-solving system that can be used in a variety of curriculum areas and with a variety of problems is called IDEAL (Bransford & Steen, 1984). IDEAL involves five stages of problem-solving:

• Identify the problem. Learners must know what the problem is before they can solve it. During this stage of problem-solving, learners ask themselves whether they understand what the problem is and whether they have stated it clearly.
• Define terms. During this stage, learners check whether they understand what each word in the problem statement means.
• Explore strategies. At this stage, learners compile relevant information and try out strategies to solve the problem. This can involve drawing diagrams, working backward to solve a mathematical or reading comprehension problem, or breaking complex problems into manageable units.
• Act on the strategy. Once learners have explored a variety of strategies, they select one and now use it.
• Look at the effects. During the final stage of the IDEAL method, learners ask themselves whether they have come up with an acceptable solution.

Video 5.4.2. The Problem Solving Model explains the process involved in solving problems. These steps can be explicitly taught to enhance problem-solving skills.

Candela Citations

• Problem-Solving. Authored by : Nicole Arduini-Van Hoose. Provided by : Hudson Valley Community College. Retrieved from : https://courses.lumenlearning.com/edpsy/chapter/problemsolving. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• Educational Psychology. Authored by : Kelvin Seifert and Rosemary Sutton. Provided by : The Saylor Foundation. Retrieved from : https://courses.lumenlearning.com/educationalpsychology. License : CC BY: Attribution
• Educational Psychology. Authored by : Bohlin. License : CC BY: Attribution
• Problem Solving. Authored by : Carole Yue. Provided by : Khan Academy. Retrieved from : https://youtu.be/J3GGx9wy07w. License : CC BY-NC-SA: Attribution-NonCommercial-ShareAlike
• The Problem Solving Model. Provided by : Gregg Learning. Retrieved from : https://youtu.be/CDk_BD1LXiI. License : All Rights Reserved

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Problem Solving

Problem solving, a fundamental cognitive process deeply rooted in psychology, plays a pivotal role in various aspects of human existence, especially within educational contexts. This article delves into the nature of problem solving, exploring its theoretical underpinnings, the cognitive and psychological processes that underlie it, and the application of problem-solving skills within educational settings and the broader real world. With a focus on both theory and practice, this article underscores the significance of cultivating problem-solving abilities as a cornerstone of cognitive development and innovation, shedding light on its applications in fields ranging from education to clinical psychology and beyond, thereby paving the way for future research and intervention in this critical domain of human cognition.

Introduction

Problem solving, a quintessential cognitive process deeply embedded in the domains of psychology and education, serves as a linchpin for human intellectual development and adaptation to the ever-evolving challenges of the world. The fundamental capacity to identify, analyze, and surmount obstacles is intrinsic to human nature and has been a subject of profound interest for psychologists, educators, and researchers alike. This article aims to provide a comprehensive exploration of problem solving, investigating its theoretical foundations, cognitive intricacies, and practical applications in educational contexts. With a clear understanding of its multifaceted nature, we will elucidate the pivotal role that problem solving plays in enhancing learning, fostering creativity, and promoting cognitive growth, setting the stage for a detailed examination of its significance in both psychology and education. In the continuum of psychological research and educational practice, problem solving stands as a cornerstone, enabling individuals to navigate the complexities of their world. This article’s thesis asserts that problem solving is not merely a cognitive skill but a dynamic process with profound implications for intellectual growth and application in diverse real-world contexts.

Academic Writing, Editing, Proofreading, And Problem Solving Services

Get 10% off with 24start discount code, the nature of problem solving.

Problem solving, within the realm of psychology, refers to the cognitive process through which individuals identify, analyze, and resolve challenges or obstacles to achieve a desired goal. It encompasses a range of mental activities, such as perception, memory, reasoning, and decision-making, aimed at devising effective solutions in the face of uncertainty or complexity.

Problem solving as a subject of inquiry has drawn from various theoretical perspectives, each offering unique insights into its nature. Among the seminal theories, Gestalt psychology has highlighted the role of insight and restructuring in problem solving, emphasizing that individuals often reorganize their mental representations to attain solutions. Information processing theories, inspired by computer models, emphasize the systematic and step-by-step nature of problem solving, likening it to information retrieval and manipulation. Furthermore, cognitive psychology has provided a comprehensive framework for understanding problem solving by examining the underlying cognitive processes involved, such as attention, memory, and decision-making. These theoretical foundations collectively offer a richer comprehension of how humans engage in and approach problem-solving tasks.

Problem solving is not a monolithic process but a series of interrelated stages that individuals progress through. These stages are integral to the overall problem-solving process, and they include:

• Problem Representation: At the outset, individuals must clearly define and represent the problem they face. This involves grasping the nature of the problem, identifying its constraints, and understanding the relationships between various elements.
• Goal Setting: Setting a clear and attainable goal is essential for effective problem solving. This step involves specifying the desired outcome or solution and establishing criteria for success.
• Solution Generation: In this stage, individuals generate potential solutions to the problem. This often involves brainstorming, creative thinking, and the exploration of different strategies to overcome the obstacles presented by the problem.
• Solution Evaluation: After generating potential solutions, individuals must evaluate these alternatives to determine their feasibility and effectiveness. This involves comparing solutions, considering potential consequences, and making choices based on the criteria established in the goal-setting phase.

These components collectively form the roadmap for navigating the terrain of problem solving and provide a structured approach to addressing challenges effectively. Understanding these stages is crucial for both researchers studying problem solving and educators aiming to foster problem-solving skills in learners.

Cognitive and Psychological Aspects of Problem Solving

Problem solving is intricately tied to a range of cognitive processes, each contributing to the effectiveness of the problem-solving endeavor.

• Perception: Perception serves as the initial gateway in problem solving. It involves the gathering and interpretation of sensory information from the environment. Effective perception allows individuals to identify relevant cues and patterns within a problem, aiding in problem representation and understanding.
• Memory: Memory is crucial in problem solving as it enables the retrieval of relevant information from past experiences, learned strategies, and knowledge. Working memory, in particular, helps individuals maintain and manipulate information while navigating through the various stages of problem solving.
• Reasoning: Reasoning encompasses logical and critical thinking processes that guide the generation and evaluation of potential solutions. Deductive and inductive reasoning, as well as analogical reasoning, play vital roles in identifying relationships and formulating hypotheses.

While problem solving is a universal cognitive function, individuals differ in their problem-solving skills due to various factors.

• Intelligence: Intelligence, as measured by IQ or related assessments, significantly influences problem-solving abilities. Higher levels of intelligence are often associated with better problem-solving performance, as individuals with greater cognitive resources can process information more efficiently and effectively.
• Creativity: Creativity is a crucial factor in problem solving, especially in situations that require innovative solutions. Creative individuals tend to approach problems with fresh perspectives, making novel connections and generating unconventional solutions.
• Expertise: Expertise in a specific domain enhances problem-solving abilities within that domain. Experts possess a wealth of knowledge and experience, allowing them to recognize patterns and solutions more readily. However, expertise can sometimes lead to domain-specific biases or difficulties in adapting to new problem types.

Despite the cognitive processes and individual differences that contribute to effective problem solving, individuals often encounter barriers that impede their progress. Recognizing and overcoming these barriers is crucial for successful problem solving.

• Functional Fixedness: Functional fixedness is a cognitive bias that limits problem solving by causing individuals to perceive objects or concepts only in their traditional or “fixed” roles. Overcoming functional fixedness requires the ability to see alternative uses and functions for objects or ideas.
• Confirmation Bias: Confirmation bias is the tendency to seek, interpret, and remember information that confirms preexisting beliefs or hypotheses. This bias can hinder objective evaluation of potential solutions, as individuals may favor information that aligns with their initial perspectives.
• Mental Sets: Mental sets are cognitive frameworks or problem-solving strategies that individuals habitually use. While mental sets can be helpful in certain contexts, they can also limit creativity and flexibility when faced with new problems. Recognizing and breaking out of mental sets is essential for overcoming this barrier.

Understanding these cognitive processes, individual differences, and common obstacles provides valuable insights into the intricacies of problem solving and offers a foundation for improving problem-solving skills and strategies in both educational and practical settings.

Problem Solving in Educational Settings

Problem solving holds a central position in educational psychology, as it is a fundamental skill that empowers students to navigate the complexities of the learning process and prepares them for real-world challenges. It goes beyond rote memorization and standardized testing, allowing students to apply critical thinking, creativity, and analytical skills to authentic problems. Problem-solving tasks in educational settings range from solving mathematical equations to tackling complex issues in subjects like science, history, and literature. These tasks not only bolster subject-specific knowledge but also cultivate transferable skills that extend beyond the classroom.

Problem-solving skills offer numerous advantages to both educators and students. For teachers, integrating problem-solving tasks into the curriculum allows for more engaging and dynamic instruction, fostering a deeper understanding of the subject matter. Additionally, it provides educators with insights into students’ thought processes and areas where additional support may be needed. Students, on the other hand, benefit from the development of critical thinking, analytical reasoning, and creativity. These skills are transferable to various life situations, enhancing students’ abilities to solve complex real-world problems and adapt to a rapidly changing society.

Teaching problem-solving skills is a dynamic process that requires effective pedagogical approaches. In K-12 education, educators often use methods such as the problem-based learning (PBL) approach, where students work on open-ended, real-world problems, fostering self-directed learning and collaboration. Higher education institutions, on the other hand, employ strategies like case-based learning, simulations, and design thinking to promote problem solving within specialized disciplines. Additionally, educators use scaffolding techniques to provide support and guidance as students develop their problem-solving abilities. In both K-12 and higher education, a key component is metacognition, which helps students become aware of their thought processes and adapt their problem-solving strategies as needed.

Assessing problem-solving abilities in educational settings involves a combination of formative and summative assessments. Formative assessments, including classroom discussions, peer evaluations, and self-assessments, provide ongoing feedback and opportunities for improvement. Summative assessments may include standardized tests designed to evaluate problem-solving skills within a particular subject area. Performance-based assessments, such as essays, projects, and presentations, offer a holistic view of students’ problem-solving capabilities. Rubrics and scoring guides are often used to ensure consistency in assessment, allowing educators to measure not only the correctness of answers but also the quality of the problem-solving process. The evolving field of educational technology has also introduced computer-based simulations and adaptive learning platforms, enabling precise measurement and tailored feedback on students’ problem-solving performance.

Understanding the pivotal role of problem solving in educational psychology, the diverse pedagogical strategies for teaching it, and the methods for assessing and measuring problem-solving abilities equips educators and students with the tools necessary to thrive in educational environments and beyond. Problem solving remains a cornerstone of 21st-century education, preparing students to meet the complex challenges of a rapidly changing world.

Applications and Practical Implications

Problem solving is not confined to the classroom; it extends its influence to various real-world contexts, showcasing its relevance and impact. In business, problem solving is the driving force behind product development, process improvement, and conflict resolution. For instance, companies often use problem-solving methodologies like Six Sigma to identify and rectify issues in manufacturing. In healthcare, medical professionals employ problem-solving skills to diagnose complex illnesses and devise treatment plans. Additionally, technology advancements frequently stem from creative problem solving, as engineers and developers tackle challenges in software, hardware, and systems design. Real-world problem solving transcends specific domains, as individuals in diverse fields address multifaceted issues by drawing upon their cognitive abilities and creative problem-solving strategies.

Clinical psychology recognizes the profound therapeutic potential of problem-solving techniques. Problem-solving therapy (PST) is an evidence-based approach that focuses on helping individuals develop effective strategies for coping with emotional and interpersonal challenges. PST equips individuals with the skills to define problems, set realistic goals, generate solutions, and evaluate their effectiveness. This approach has shown efficacy in treating conditions like depression, anxiety, and stress, emphasizing the role of problem-solving abilities in enhancing emotional well-being. Furthermore, cognitive-behavioral therapy (CBT) incorporates problem-solving elements to help individuals challenge and modify dysfunctional thought patterns, reinforcing the importance of cognitive processes in addressing psychological distress.

Problem solving is the bedrock of innovation and creativity in various fields. Innovators and creative thinkers use problem-solving skills to identify unmet needs, devise novel solutions, and overcome obstacles. Design thinking, a problem-solving approach, is instrumental in product design, architecture, and user experience design, fostering innovative solutions grounded in human needs. Moreover, creative industries like art, literature, and music rely on problem-solving abilities to transcend conventional boundaries and produce groundbreaking works. By exploring alternative perspectives, making connections, and persistently seeking solutions, creative individuals harness problem-solving processes to ignite innovation and drive progress in all facets of human endeavor.

Understanding the practical applications of problem solving in business, healthcare, technology, and its therapeutic significance in clinical psychology, as well as its indispensable role in nurturing innovation and creativity, underscores its universal value. Problem solving is not only a cognitive skill but also a dynamic force that shapes and improves the world we inhabit, enhancing the quality of life and promoting progress and discovery.

In summary, problem solving stands as an indispensable cornerstone within the domains of psychology and education. This article has explored the multifaceted nature of problem solving, from its theoretical foundations rooted in Gestalt psychology, information processing theories, and cognitive psychology to its integral components of problem representation, goal setting, solution generation, and solution evaluation. It has delved into the cognitive processes underpinning effective problem solving, including perception, memory, and reasoning, as well as the impact of individual differences such as intelligence, creativity, and expertise. Common barriers to problem solving, including functional fixedness, confirmation bias, and mental sets, have been examined in-depth.

The significance of problem solving in educational settings was elucidated, underscoring its pivotal role in fostering critical thinking, creativity, and adaptability. Pedagogical approaches and assessment methods were discussed, providing educators with insights into effective strategies for teaching and evaluating problem-solving skills in K-12 and higher education.

Furthermore, the practical implications of problem solving were demonstrated in the real world, where it serves as the driving force behind advancements in business, healthcare, and technology. In clinical psychology, problem-solving therapies offer effective interventions for emotional and psychological well-being. The symbiotic relationship between problem solving and innovation and creativity was explored, highlighting the role of this cognitive process in pushing the boundaries of human accomplishment.

As we conclude, it is evident that problem solving is not merely a skill but a dynamic process with profound implications. It enables individuals to navigate the complexities of their environment, fostering intellectual growth, adaptability, and innovation. Future research in the field of problem solving should continue to explore the intricate cognitive processes involved, individual differences that influence problem-solving abilities, and innovative teaching methods in educational settings. In practice, educators and clinicians should continue to incorporate problem-solving strategies to empower individuals with the tools necessary for success in education, personal development, and the ever-evolving challenges of the real world. Problem solving remains a steadfast ally in the pursuit of knowledge, progress, and the enhancement of human potential.

References:

• Anderson, J. R. (1995). Cognitive psychology and its implications. W. H. Freeman.
• Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In The psychology of learning and motivation (Vol. 2, pp. 89-195). Academic Press.
• Duncker, K. (1945). On problem-solving. Psychological Monographs, 58(5), i-113.
• Gick, M. L., & Holyoak, K. J. (1980). Analogical problem solving. Cognitive Psychology, 12(3), 306-355.
• Jonassen, D. H., & Hung, W. (2008). All problems are not equal: Implications for problem-based learning. Interdisciplinary Journal of Problem-Based Learning, 2(2), 6.
• Kitchener, K. S., & King, P. M. (1981). Reflective judgment: Concepts of justification and their relation to age and education. Journal of Applied Developmental Psychology, 2(2), 89-116.
• Luchins, A. S. (1942). Mechanization in problem solving: The effect of Einstellung. Psychological Monographs, 54(6), i-95.
• Mayer, R. E. (1992). Thinking, problem solving, cognition. W. H. Freeman.
• Newell, A., & Simon, H. A. (1972). Human problem solving (Vol. 104). Prentice-Hall Englewood Cliffs, NJ.
• Osborn, A. F. (1953). Applied imagination: Principles and procedures of creative problem solving (3rd ed.). Charles Scribner’s Sons.
• Polya, G. (1945). How to solve it: A new aspect of mathematical method. Princeton University Press.
• Sternberg, R. J. (2003). Wisdom, intelligence, and creativity synthesized. Cambridge University Press.

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48 Problem Solving

Department of Psychological and Brain Sciences, University of California, Santa Barbara

• Published: 03 June 2013
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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 nonroutine, 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. Classic theoretical approaches to the study of problem solving are associationism, Gestalt, and information processing. Current issues and suggested future issues 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 themes concern the domain specificity of problem solving and a focus on problem solving in authentic contexts.

The study of problem solving begins with defining problem solving, problem, and problem types. This introduction to problem solving is rounded out with an examination of cognitive processes in problem solving, the role of knowledge in problem solving, and historical approaches to the study of problem solving.

Definition of Problem Solving

Problem solving refers to cognitive processing directed at achieving a goal for which the problem solver does not initially know a solution method. This definition consists of four major elements (Mayer, 1992 ; Mayer & Wittrock, 2006 ):

Cognitive —Problem solving occurs within the problem solver’s cognitive system and can only be inferred indirectly from the problem solver’s behavior (including biological changes, introspections, and actions during problem solving). Process —Problem solving involves mental computations in which some operation is applied to a mental representation, sometimes resulting in the creation of a new mental representation. Directed —Problem solving is aimed at achieving a goal. Personal —Problem solving depends on the existing knowledge of the problem solver so that what is a problem for one problem solver may not be a problem for someone who already knows a solution method.

The definition is broad enough to include a wide array of cognitive activities such as deciding which apartment to rent, figuring out how to use a cell phone interface, playing a game of chess, making a medical diagnosis, finding the answer to an arithmetic word problem, or writing a chapter for a handbook. Problem solving is pervasive in human life and is crucial for human survival. Although this chapter focuses on problem solving in humans, problem solving also occurs in nonhuman animals and in intelligent machines.

How is problem solving related to other forms of high-level cognition processing, such as thinking and reasoning? Thinking refers to cognitive processing in individuals but includes both directed thinking (which corresponds to the definition of problem solving) and undirected thinking such as daydreaming (which does not correspond to the definition of problem solving). Thus, problem solving is a type of thinking (i.e., directed thinking).

Reasoning refers to problem solving within specific classes of problems, such as deductive reasoning or inductive reasoning. In deductive reasoning, the reasoner is given premises and must derive a conclusion by applying the rules of logic. For example, given that “A is greater than B” and “B is greater than C,” a reasoner can conclude that “A is greater than C.” In inductive reasoning, the reasoner is given (or has experienced) a collection of examples or instances and must infer a rule. For example, given that X, C, and V are in the “yes” group and x, c, and v are in the “no” group, the reasoning may conclude that B is in “yes” group because it is in uppercase format. Thus, reasoning is a type of problem solving.

Definition of Problem

A problem occurs when someone has a goal but does not know to achieve it. This definition is consistent with how the Gestalt psychologist Karl Duncker ( 1945 , p. 1) defined a problem in his classic monograph, On Problem Solving : “A problem arises when a living creature has a goal but does not know how this goal is to be reached.” However, today researchers recognize that the definition should be extended to include problem solving by intelligent machines. This definition can be clarified using an information processing approach by noting that a problem occurs when a situation is in the given state, the problem solver wants the situation to be in the goal state, and there is no obvious way to move from the given state to the goal state (Newell & Simon, 1972 ). Accordingly, the three main elements in describing a problem are the given state (i.e., the current state of the situation), the goal state (i.e., the desired state of the situation), and the set of allowable operators (i.e., the actions the problem solver is allowed to take). The definition of “problem” is broad enough to include the situation confronting a physician who wishes to make a diagnosis on the basis of preliminary tests and a patient examination, as well as a beginning physics student trying to solve a complex physics problem.

Types of Problems

It is customary in the problem-solving literature to make a distinction between routine and nonroutine problems. Routine problems are problems that are so familiar to the problem solver that the problem solver knows a solution method. For example, for most adults, “What is 365 divided by 12?” is a routine problem because they already know the procedure for long division. Nonroutine problems are so unfamiliar to the problem solver that the problem solver does not know a solution method. For example, figuring out the best way to set up a funding campaign for a nonprofit charity is a nonroutine problem for most volunteers. Technically, routine problems do not meet the definition of problem because the problem solver has a goal but knows how to achieve it. Much research on problem solving has focused on routine problems, although most interesting problems in life are nonroutine.

Another customary distinction is between well-defined and ill-defined problems. Well-defined problems have a clearly specified given state, goal state, and legal operators. Examples include arithmetic computation problems or games such as checkers or tic-tac-toe. Ill-defined problems have a poorly specified given state, goal state, or legal operators, or a combination of poorly defined features. Examples include solving the problem of global warming or finding a life partner. Although, ill-defined problems are more challenging, much research in problem solving has focused on well-defined problems.

Cognitive Processes in Problem Solving

The process of problem solving can be broken down into two main phases: problem representation , in which the problem solver builds a mental representation of the problem situation, and problem solution , in which the problem solver works to produce a solution. The major subprocess in problem representation is representing , which involves building a situation model —that is, a mental representation of the situation described in the problem. The major subprocesses in problem solution are planning , which involves devising a plan for how to solve the problem; executing , which involves carrying out the plan; and monitoring , which involves evaluating and adjusting one’s problem solving.

For example, given an arithmetic word problem such as “Alice has three marbles. Sarah has two more marbles than Alice. How many marbles does Sarah have?” the process of representing involves building a situation model in which Alice has a set of marbles, there is set of marbles for the difference between the two girls, and Sarah has a set of marbles that consists of Alice’s marbles and the difference set. In the planning process, the problem solver sets a goal of adding 3 and 2. In the executing process, the problem solver carries out the computation, yielding an answer of 5. In the monitoring process, the problem solver looks over what was done and concludes that 5 is a reasonable answer. In most complex problem-solving episodes, the four cognitive processes may not occur in linear order, but rather may interact with one another. Although some research focuses mainly on the execution process, problem solvers may tend to have more difficulty with the processes of representing, planning, and monitoring.

Knowledge for Problem Solving

An important theme in problem-solving research is that problem-solving proficiency on any task depends on the learner’s knowledge (Anderson et al., 2001 ; Mayer, 1992 ). Five kinds of knowledge are as follows:

Facts —factual knowledge about the characteristics of elements in the world, such as “Sacramento is the capital of California” Concepts —conceptual knowledge, including categories, schemas, or models, such as knowing the difference between plants and animals or knowing how a battery works Procedures —procedural knowledge of step-by-step processes, such as how to carry out long-division computations Strategies —strategic knowledge of general methods such as breaking a problem into parts or thinking of a related problem Beliefs —attitudinal knowledge about how one’s cognitive processing works such as thinking, “I’m good at this”

Although some research focuses mainly on the role of facts and procedures in problem solving, complex problem solving also depends on the problem solver’s concepts, strategies, and beliefs (Mayer, 1992 ).

Historical Approaches to Problem Solving

Psychological research on problem solving began in the early 1900s, as an outgrowth of mental philosophy (Humphrey, 1963 ; Mandler & Mandler, 1964 ). Throughout the 20th century four theoretical approaches developed: early conceptions, associationism, Gestalt psychology, and information processing.

Early Conceptions

The start of psychology as a science can be set at 1879—the year Wilhelm Wundt opened the first world’s psychology laboratory in Leipzig, Germany, and sought to train the world’s first cohort of experimental psychologists. Instead of relying solely on philosophical speculations about how the human mind works, Wundt sought to apply the methods of experimental science to issues addressed in mental philosophy. His theoretical approach became structuralism —the analysis of consciousness into its basic elements.

Wundt’s main contribution to the study of problem solving, however, was to call for its banishment. According to Wundt, complex cognitive processing was too complicated to be studied by experimental methods, so “nothing can be discovered in such experiments” (Wundt, 1911/1973 ). Despite his admonishments, however, a group of his former students began studying thinking mainly in Wurzburg, Germany. Using the method of introspection, subjects were asked to describe their thought process as they solved word association problems, such as finding the superordinate of “newspaper” (e.g., an answer is “publication”). Although the Wurzburg group—as they came to be called—did not produce a new theoretical approach, they found empirical evidence that challenged some of the key assumptions of mental philosophy. For example, Aristotle had proclaimed that all thinking involves mental imagery, but the Wurzburg group was able to find empirical evidence for imageless thought .

Associationism

The first major theoretical approach to take hold in the scientific study of problem solving was associationism —the idea that the cognitive representations in the mind consist of ideas and links between them and that cognitive processing in the mind involves following a chain of associations from one idea to the next (Mandler & Mandler, 1964 ; Mayer, 1992 ). For example, in a classic study, E. L. Thorndike ( 1911 ) placed a hungry cat in what he called a puzzle box—a wooden crate in which pulling a loop of string that hung from overhead would open a trap door to allow the cat to escape to a bowl of food outside the crate. Thorndike placed the cat in the puzzle box once a day for several weeks. On the first day, the cat engaged in many extraneous behaviors such as pouncing against the wall, pushing its paws through the slats, and meowing, but on successive days the number of extraneous behaviors tended to decrease. Overall, the time required to get out of the puzzle box decreased over the course of the experiment, indicating the cat was learning how to escape.

Thorndike’s explanation for how the cat learned to solve the puzzle box problem is based on an associationist view: The cat begins with a habit family hierarchy —a set of potential responses (e.g., pouncing, thrusting, meowing, etc.) all associated with the same stimulus (i.e., being hungry and confined) and ordered in terms of strength of association. When placed in the puzzle box, the cat executes its strongest response (e.g., perhaps pouncing against the wall), but when it fails, the strength of the association is weakened, and so on for each unsuccessful action. Eventually, the cat gets down to what was initially a weak response—waving its paw in the air—but when that response leads to accidentally pulling the string and getting out, it is strengthened. Over the course of many trials, the ineffective responses become weak and the successful response becomes strong. Thorndike refers to this process as the law of effect : Responses that lead to dissatisfaction become less associated with the situation and responses that lead to satisfaction become more associated with the situation. According to Thorndike’s associationist view, solving a problem is simply a matter of trial and error and accidental success. A major challenge to assocationist theory concerns the nature of transfer—that is, where does a problem solver find a creative solution that has never been performed before? Associationist conceptions of cognition can be seen in current research, including neural networks, connectionist models, and parallel distributed processing models (Rogers & McClelland, 2004 ).

Gestalt Psychology

The Gestalt approach to problem solving developed in the 1930s and 1940s as a counterbalance to the associationist approach. According to the Gestalt approach, cognitive representations consist of coherent structures (rather than individual associations) and the cognitive process of problem solving involves building a coherent structure (rather than strengthening and weakening of associations). For example, in a classic study, Kohler ( 1925 ) placed a hungry ape in a play yard that contained several empty shipping crates and a banana attached overhead but out of reach. Based on observing the ape in this situation, Kohler noted that the ape did not randomly try responses until one worked—as suggested by Thorndike’s associationist view. Instead, the ape stood under the banana, looked up at it, looked at the crates, and then in a flash of insight stacked the crates under the bananas as a ladder, and walked up the steps in order to reach the banana.

According to Kohler, the ape experienced a sudden visual reorganization in which the elements in the situation fit together in a way to solve the problem; that is, the crates could become a ladder that reduces the distance to the banana. Kohler referred to the underlying mechanism as insight —literally seeing into the structure of the situation. A major challenge of Gestalt theory is its lack of precision; for example, naming a process (i.e., insight) is not the same as explaining how it works. Gestalt conceptions can be seen in modern research on mental models and schemas (Gentner & Stevens, 1983 ).

Information Processing

The information processing approach to problem solving developed in the 1960s and 1970s and was based on the influence of the computer metaphor—the idea that humans are processors of information (Mayer, 2009 ). According to the information processing approach, problem solving involves a series of mental computations—each of which consists of applying a process to a mental representation (such as comparing two elements to determine whether they differ).

In their classic book, Human Problem Solving , Newell and Simon ( 1972 ) proposed that problem solving involved a problem space and search heuristics . A problem space is a mental representation of the initial state of the problem, the goal state of the problem, and all possible intervening states (based on applying allowable operators). Search heuristics are strategies for moving through the problem space from the given to the goal state. Newell and Simon focused on means-ends analysis , in which the problem solver continually sets goals and finds moves to accomplish goals.

Newell and Simon used computer simulation as a research method to test their conception of human problem solving. First, they asked human problem solvers to think aloud as they solved various problems such as logic problems, chess, and cryptarithmetic problems. Then, based on an information processing analysis, Newell and Simon created computer programs that solved these problems. In comparing the solution behavior of humans and computers, they found high similarity, suggesting that the computer programs were solving problems using the same thought processes as humans.

An important advantage of the information processing approach is that problem solving can be described with great clarity—as a computer program. An important limitation of the information processing approach is that it is most useful for describing problem solving for well-defined problems rather than ill-defined problems. The information processing conception of cognition lives on as a keystone of today’s cognitive science (Mayer, 2009 ).

Classic Issues in Problem Solving

Three classic issues in research on problem solving concern the nature of transfer (suggested by the associationist approach), the nature of insight (suggested by the Gestalt approach), and the role of problem-solving heuristics (suggested by the information processing approach).

Transfer refers to the effects of prior learning on new learning (or new problem solving). Positive transfer occurs when learning A helps someone learn B. Negative transfer occurs when learning A hinders someone from learning B. Neutral transfer occurs when learning A has no effect on learning B. Positive transfer is a central goal of education, but research shows that people often do not transfer what they learned to solving problems in new contexts (Mayer, 1992 ; Singley & Anderson, 1989 ).

Three conceptions of the mechanisms underlying transfer are specific transfer , general transfer , and specific transfer of general principles . Specific transfer refers to the idea that learning A will help someone learn B only if A and B have specific elements in common. For example, learning Spanish may help someone learn Latin because some of the vocabulary words are similar and the verb conjugation rules are similar. General transfer refers to the idea that learning A can help someone learn B even they have nothing specifically in common but A helps improve the learner’s mind in general. For example, learning Latin may help people learn “proper habits of mind” so they are better able to learn completely unrelated subjects as well. Specific transfer of general principles is the idea that learning A will help someone learn B if the same general principle or solution method is required for both even if the specific elements are different.

In a classic study, Thorndike and Woodworth ( 1901 ) found that students who learned Latin did not subsequently learn bookkeeping any better than students who had not learned Latin. They interpreted this finding as evidence for specific transfer—learning A did not transfer to learning B because A and B did not have specific elements in common. Modern research on problem-solving transfer continues to show that people often do not demonstrate general transfer (Mayer, 1992 ). However, it is possible to teach people a general strategy for solving a problem, so that when they see a new problem in a different context they are able to apply the strategy to the new problem (Judd, 1908 ; Mayer, 2008 )—so there is also research support for the idea of specific transfer of general principles.

Insight refers to a change in a problem solver’s mind from not knowing how to solve a problem to knowing how to solve it (Mayer, 1995 ; Metcalfe & Wiebe, 1987 ). In short, where does the idea for a creative solution come from? A central goal of problem-solving research is to determine the mechanisms underlying insight.

The search for insight has led to five major (but not mutually exclusive) explanatory mechanisms—insight as completing a schema, insight as suddenly reorganizing visual information, insight as reformulation of a problem, insight as removing mental blocks, and insight as finding a problem analog (Mayer, 1995 ). Completing a schema is exemplified in a study by Selz (Fridja & de Groot, 1982 ), in which people were asked to think aloud as they solved word association problems such as “What is the superordinate for newspaper?” To solve the problem, people sometimes thought of a coordinate, such as “magazine,” and then searched for a superordinate category that subsumed both terms, such as “publication.” According to Selz, finding a solution involved building a schema that consisted of a superordinate and two subordinate categories.

Reorganizing visual information is reflected in Kohler’s ( 1925 ) study described in a previous section in which a hungry ape figured out how to stack boxes as a ladder to reach a banana hanging above. According to Kohler, the ape looked around the yard and found the solution in a flash of insight by mentally seeing how the parts could be rearranged to accomplish the goal.

Reformulating a problem is reflected in a classic study by Duncker ( 1945 ) in which people are asked to think aloud as they solve the tumor problem—how can you destroy a tumor in a patient without destroying surrounding healthy tissue by using rays that at sufficient intensity will destroy any tissue in their path? In analyzing the thinking-aloud protocols—that is, transcripts of what the problem solvers said—Duncker concluded that people reformulated the goal in various ways (e.g., avoid contact with healthy tissue, immunize healthy tissue, have ray be weak in healthy tissue) until they hit upon a productive formulation that led to the solution (i.e., concentrating many weak rays on the tumor).

Removing mental blocks is reflected in classic studies by Duncker ( 1945 ) in which solving a problem involved thinking of a novel use for an object, and by Luchins ( 1942 ) in which solving a problem involved not using a procedure that had worked well on previous problems. Finding a problem analog is reflected in classic research by Wertheimer ( 1959 ) in which learning to find the area of a parallelogram is supported by the insight that one could cut off the triangle on one side and place it on the other side to form a rectangle—so a parallelogram is really a rectangle in disguise. The search for insight along each of these five lines continues in current problem-solving research.

Heuristics are problem-solving strategies, that is, general approaches to how to solve problems. Newell and Simon ( 1972 ) suggested three general problem-solving heuristics for moving from a given state to a goal state: random trial and error , hill climbing , and means-ends analysis . Random trial and error involves randomly selecting a legal move and applying it to create a new problem state, and repeating that process until the goal state is reached. Random trial and error may work for simple problems but is not efficient for complex ones. Hill climbing involves selecting the legal move that moves the problem solver closer to the goal state. Hill climbing will not work for problems in which the problem solver must take a move that temporarily moves away from the goal as is required in many problems.

Means-ends analysis involves creating goals and seeking moves that can accomplish the goal. If a goal cannot be directly accomplished, a subgoal is created to remove one or more obstacles. Newell and Simon ( 1972 ) successfully used means-ends analysis as the search heuristic in a computer program aimed at general problem solving, that is, solving a diverse collection of problems. However, people may also use specific heuristics that are designed to work for specific problem-solving situations (Gigerenzer, Todd, & ABC Research Group, 1999 ; Kahneman & Tversky, 1984 ).

Current and Future Issues in Problem Solving

Eight current issues in problem solving involve decision making, intelligence and creativity, teaching of thinking skills, expert problem solving, analogical reasoning, mathematical and scientific problem solving, everyday thinking, and the cognitive neuroscience of problem solving.

Decision Making

Decision making refers to the cognitive processing involved in choosing between two or more alternatives (Baron, 2000 ; Markman & Medin, 2002 ). For example, a decision-making task may involve choosing between getting $240 for sure or having a 25% change of getting $1000. According to economic theories such as expected value theory, people should chose the second option, which is worth $250 (i.e., .25 x $1000) rather than the first option, which is worth $240 (1.00 x $240), but psychological research shows that most people prefer the first option (Kahneman & Tversky, 1984 ).

Research on decision making has generated three classes of theories (Markman & Medin, 2002 ): descriptive theories, such as prospect theory (Kahneman & Tversky), which are based on the ideas that people prefer to overweight the cost of a loss and tend to overestimate small probabilities; heuristic theories, which are based on the idea that people use a collection of short-cut strategies such as the availability heuristic (Gigerenzer et al., 1999 ; Kahneman & Tversky, 2000 ); and constructive theories, such as mental accounting (Kahneman & Tversky, 2000 ), in which people build a narrative to justify their choices to themselves. Future research is needed to examine decision making in more realistic settings.

Intelligence and Creativity

Although researchers do not have complete consensus on the definition of intelligence (Sternberg, 1990 ), it is reasonable to view intelligence as the ability to learn or adapt to new situations. Fluid intelligence refers to the potential to solve problems without any relevant knowledge, whereas crystallized intelligence refers to the potential to solve problems based on relevant prior knowledge (Sternberg & Gregorenko, 2003 ). As people gain more experience in a field, their problem-solving performance depends more on crystallized intelligence (i.e., domain knowledge) than on fluid intelligence (i.e., general ability) (Sternberg & Gregorenko, 2003 ). The ability to monitor and manage one’s cognitive processing during problem solving—which can be called metacognition —is an important aspect of intelligence (Sternberg, 1990 ). Research is needed to pinpoint the knowledge that is needed to support intelligent performance on problem-solving tasks.

Creativity refers to the ability to generate ideas that are original (i.e., other people do not think of the same idea) and functional (i.e., the idea works; Sternberg, 1999 ). Creativity is often measured using tests of divergent thinking —that is, generating as many solutions as possible for a problem (Guilford, 1967 ). For example, the uses test asks people to list as many uses as they can think of for a brick. Creativity is different from intelligence, and it is at the heart of creative problem solving—generating a novel solution to a problem that the problem solver has never seen before. An important research question concerns whether creative problem solving depends on specific knowledge or creativity ability in general.

Teaching of Thinking Skills

How can people learn to be better problem solvers? Mayer ( 2008 ) proposes four questions concerning teaching of thinking skills:

What to teach —Successful programs attempt to teach small component skills (such as how to generate and evaluate hypotheses) rather than improve the mind as a single monolithic skill (Covington, Crutchfield, Davies, & Olton, 1974 ). How to teach —Successful programs focus on modeling the process of problem solving rather than solely reinforcing the product of problem solving (Bloom & Broder, 1950 ). Where to teach —Successful programs teach problem-solving skills within the specific context they will be used rather than within a general course on how to solve problems (Nickerson, 1999 ). When to teach —Successful programs teaching higher order skills early rather than waiting until lower order skills are completely mastered (Tharp & Gallimore, 1988 ).

Overall, research on teaching of thinking skills points to the domain specificity of problem solving; that is, successful problem solving depends on the problem solver having domain knowledge that is relevant to the problem-solving task.

Expert Problem Solving

Research on expertise is concerned with differences between how experts and novices solve problems (Ericsson, Feltovich, & Hoffman, 2006 ). Expertise can be defined in terms of time (e.g., 10 years of concentrated experience in a field), performance (e.g., earning a perfect score on an assessment), or recognition (e.g., receiving a Nobel Prize or becoming Grand Master in chess). For example, in classic research conducted in the 1940s, de Groot ( 1965 ) found that chess experts did not have better general memory than chess novices, but they did have better domain-specific memory for the arrangement of chess pieces on the board. Chase and Simon ( 1973 ) replicated this result in a better controlled experiment. An explanation is that experts have developed schemas that allow them to chunk collections of pieces into a single configuration.

In another landmark study, Larkin et al. ( 1980 ) compared how experts (e.g., physics professors) and novices (e.g., first-year physics students) solved textbook physics problems about motion. Experts tended to work forward from the given information to the goal, whereas novices tended to work backward from the goal to the givens using a means-ends analysis strategy. Experts tended to store their knowledge in an integrated way, whereas novices tended to store their knowledge in isolated fragments. In another study, Chi, Feltovich, and Glaser ( 1981 ) found that experts tended to focus on the underlying physics concepts (such as conservation of energy), whereas novices tended to focus on the surface features of the problem (such as inclined planes or springs). Overall, research on expertise is useful in pinpointing what experts know that is different from what novices know. An important theme is that experts rely on domain-specific knowledge rather than solely general cognitive ability.

Analogical Reasoning

Analogical reasoning occurs when people solve one problem by using their knowledge about another problem (Holyoak, 2005 ). For example, suppose a problem solver learns how to solve a problem in one context using one solution method and then is given a problem in another context that requires the same solution method. In this case, the problem solver must recognize that the new problem has structural similarity to the old problem (i.e., it may be solved by the same method), even though they do not have surface similarity (i.e., the cover stories are different). Three steps in analogical reasoning are recognizing —seeing that a new problem is similar to a previously solved problem; abstracting —finding the general method used to solve the old problem; and mapping —using that general method to solve the new problem.

Research on analogical reasoning shows that people often do not recognize that a new problem can be solved by the same method as a previously solved problem (Holyoak, 2005 ). However, research also shows that successful analogical transfer to a new problem is more likely when the problem solver has experience with two old problems that have the same underlying structural features (i.e., they are solved by the same principle) but different surface features (i.e., they have different cover stories) (Holyoak, 2005 ). This finding is consistent with the idea of specific transfer of general principles as described in the section on “Transfer.”

Mathematical and Scientific Problem Solving

Research on mathematical problem solving suggests that five kinds of knowledge are needed to solve arithmetic word problems (Mayer, 2008 ):

Factual knowledge —knowledge about the characteristics of problem elements, such as knowing that there are 100 cents in a dollar Schematic knowledge —knowledge of problem types, such as being able to recognize time-rate-distance problems Strategic knowledge —knowledge of general methods, such as how to break a problem into parts Procedural knowledge —knowledge of processes, such as how to carry our arithmetic operations Attitudinal knowledge —beliefs about one’s mathematical problem-solving ability, such as thinking, “I am good at this”

People generally possess adequate procedural knowledge but may have difficulty in solving mathematics problems because they lack factual, schematic, strategic, or attitudinal knowledge (Mayer, 2008 ). Research is needed to pinpoint the role of domain knowledge in mathematical problem solving.

Research on scientific problem solving shows that people harbor misconceptions, such as believing that a force is needed to keep an object in motion (McCloskey, 1983 ). Learning to solve science problems involves conceptual change, in which the problem solver comes to recognize that previous conceptions are wrong (Mayer, 2008 ). Students can be taught to engage in scientific reasoning such as hypothesis testing through direct instruction in how to control for variables (Chen & Klahr, 1999 ). A central theme of research on scientific problem solving concerns the role of domain knowledge.

Everyday Thinking

Everyday thinking refers to problem solving in the context of one’s life outside of school. For example, children who are street vendors tend to use different procedures for solving arithmetic problems when they are working on the streets than when they are in school (Nunes, Schlieman, & Carraher, 1993 ). This line of research highlights the role of situated cognition —the idea that thinking always is shaped by the physical and social context in which it occurs (Robbins & Aydede, 2009 ). Research is needed to determine how people solve problems in authentic contexts.

Cognitive Neuroscience of Problem Solving

The cognitive neuroscience of problem solving is concerned with the brain activity that occurs during problem solving. For example, using fMRI brain imaging methodology, Goel ( 2005 ) found that people used the language areas of the brain to solve logical reasoning problems presented in sentences (e.g., “All dogs are pets…”) and used the spatial areas of the brain to solve logical reasoning problems presented in abstract letters (e.g., “All D are P…”). Cognitive neuroscience holds the potential to make unique contributions to the study of problem solving.

Problem solving has always been a topic at the fringe of cognitive psychology—too complicated to study intensively but too important to completely ignore. Problem solving—especially in realistic environments—is messy in comparison to studying elementary processes in cognition. The field remains fragmented in the sense that topics such as decision making, reasoning, intelligence, expertise, mathematical problem solving, everyday thinking, and the like are considered to be separate topics, each with its own separate literature. Yet some recurring themes are the role of domain-specific knowledge in problem solving and the advantages of studying problem solving in authentic contexts.

Future Directions

Some important issues for future research include the three classic issues examined in this chapter—the nature of problem-solving transfer (i.e., How are people able to use what they know about previous problem solving to help them in new problem solving?), the nature of insight (e.g., What is the mechanism by which a creative solution is constructed?), and heuristics (e.g., What are some teachable strategies for problem solving?). In addition, future research in problem solving should continue to pinpoint the role of domain-specific knowledge in problem solving, the nature of cognitive ability in problem solving, how to help people develop proficiency in solving problems, and how to provide aids for problem solving.

Anderson L. W. , Krathwohl D. R. , Airasian P. W. , Cruikshank K. A. , Mayer R. E. , Pintrich P. R. , Raths, J., & Wittrock M. C. ( 2001 ). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. New York : Longman.

Baron J. ( 2000 ). Thinking and deciding (3rd ed.). New York : Cambridge University Press.

Google Scholar

Google Preview

Bloom B. S. , & Broder B. J. ( 1950 ). Problem-solving processes of college students: An exploratory investigation. Chicago : University of Chicago Press.

Chase W. G. , & Simon H. A. ( 1973 ). Perception in chess.   Cognitive Psychology, 4, 55–81.

Chen Z. , & Klahr D. ( 1999 ). All other things being equal: Acquisition and transfer of the control of variable strategy . Child Development, 70, 1098–1120.

Chi M. T. H. , Feltovich P. J. , & Glaser R. ( 1981 ). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5, 121–152.

Covington M. V. , Crutchfield R. S. , Davies L. B. , & Olton R. M. ( 1974 ). The productive thinking program. Columbus, OH : Merrill.

de Groot A. D. ( 1965 ). Thought and choice in chess. The Hague, The Netherlands : Mouton.

Duncker K. ( 1945 ). On problem solving.   Psychological Monographs, 58 (3) (Whole No. 270).

Ericsson K. A. , Feltovich P. J. , & Hoffman R. R. (Eds.). ( 2006 ). The Cambridge handbook of expertise and expert performance. New York : Cambridge University Press.

Fridja N. H. , & de Groot A. D. ( 1982 ). Otto Selz: His contribution to psychology. The Hague, The Netherlands : Mouton.

Gentner D. , & Stevens A. L. (Eds.). ( 1983 ). Mental models. Hillsdale, NJ : Erlbaum.

Gigerenzer G. , Todd P. M. , & ABC Research Group (Eds.). ( 1999 ). Simple heuristics that make us smart. Oxford, England : Oxford University Press.

Goel V. ( 2005 ). Cognitive neuroscience of deductive reasoning. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 475–492). New York : Cambridge University Press.

Guilford J. P. ( 1967 ). The nature of human intelligence. New York : McGraw-Hill.

Holyoak K. J. ( 2005 ). Analogy. In K. J. Holyoak & R. G. Morrison (Eds.), The Cambridge handbook of thinking and reasoning (pp. 117–142). New York : Cambridge University Press.

Humphrey G. ( 1963 ). Thinking: An introduction to experimental psychology. New York : Wiley.

Judd C. H. ( 1908 ). The relation of special training and general intelligence. Educational Review, 36, 28–42.

Kahneman D. , & Tversky A. ( 1984 ). Choices, values, and frames. American Psychologist, 39, 341–350.

Kahneman D. , & Tversky A. (Eds.). ( 2000 ). Choices, values, and frames. New York : Cambridge University Press.

Kohler W. ( 1925 ). The mentality of apes. New York : Liveright.

Larkin J. H. , McDermott J. , Simon D. P. , & Simon H. A. ( 1980 ). Expert and novice performance in solving physics problems. Science, 208, 1335–1342.

Luchins A. ( 1942 ). Mechanization in problem solving.   Psychological Monographs, 54 (6) (Whole No. 248).

Mandler J. M. , & Mandler G. ( 1964 ). Thinking from associationism to Gestalt. New York : Wiley.

Markman A. B. , & Medin D. L. ( 2002 ). Decision making. In D. Medin (Ed.), Stevens’ handbook of experimental psychology, Vol. 2. Memory and cognitive processes (2nd ed., pp. 413–466). New York : Wiley.

Mayer R. E. ( 1992 ). Thinking, problem solving, cognition (2nd ed). New York : Freeman.

Mayer R. E. ( 1995 ). The search for insight: Grappling with Gestalt psychology’s unanswered questions. In R. J. Sternberg & J. E. Davidson (Eds.), The nature of insight (pp. 3–32). Cambridge, MA : MIT Press.

Mayer R. E. ( 2008 ). Learning and instruction. Upper Saddle River, NJ : Merrill Prentice Hall.

Mayer R. E. ( 2009 ). Information processing. In T. L. Good (Ed.), 21st century education: A reference handbook (pp. 168–174). Thousand Oaks, CA : Sage.

Mayer R. E. , & Wittrock M. C. ( 2006 ). Problem solving. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 287–304). Mahwah, NJ : Erlbaum.

McCloskey M. ( 1983 ). Intuitive physics.   Scientific American, 248 (4), 122–130.

Metcalfe J. , & Wiebe D. ( 1987 ). Intuition in insight and non-insight problem solving. Memory and Cognition, 15, 238–246.

Newell A. , & Simon H. A. ( 1972 ). Human problem solving. Englewood Cliffs, NJ : Prentice-Hall.

Nickerson R. S. ( 1999 ). Enhancing creativity. In R. J. Sternberg (Ed.), Handbook of creativity (pp. 392–430). New York : Cambridge University Press.

Nunes T. , Schliemann A. D. , & Carraher D. W , ( 1993 ). Street mathematics and school mathematics. Cambridge, England : Cambridge University Press.

Robbins P. , & Aydede M. (Eds.). ( 2009 ). The Cambridge handbook of situated cognition. New York : Cambridge University Press.

Rogers T. T. , & McClelland J. L. ( 2004 ). Semantic cognition: A parallel distributed processing approach. Cambridge, MA : MIT Press.

Singley M. K. , & Anderson J. R. ( 1989 ). The transfer of cognitive skill. Cambridge, MA : Harvard University Press.

Sternberg R. J. ( 1990 ). Metaphors of mind: Conceptions of the nature of intelligence. New York : Cambridge University Press.

Sternberg R. J. ( 1999 ). Handbook of creativity. New York : Cambridge University Press.

Sternberg R. J. , & Gregorenko E. L. (Eds.). ( 2003 ). The psychology of abilities, competencies, and expertise. New York : Cambridge University Press.

Tharp R. G. , & Gallimore R. ( 1988 ). Rousing minds to life: Teaching, learning, and schooling in social context. New York : Cambridge University Press.

Thorndike E. L. ( 1911 ). Animal intelligence. New York: Hafner.

Thorndike E. L. , & Woodworth R. S. ( 1901 ). The influence of improvement in one mental function upon the efficiency of other functions. Psychological Review, 8, 247–261.

Wertheimer M. ( 1959 ). Productive thinking. New York : Harper and Collins.

Wundt W. ( 1973 ). An introduction to experimental psychology. New York : Arno Press. (Original work published in 1911).

Further Reading

Baron, J. ( 2008 ). Thinking and deciding (4th ed). New York: Cambridge University Press.

Duncker, K. ( 1945 ). On problem solving. Psychological Monographs , 58(3) (Whole No. 270).

Holyoak, K. J. , & Morrison, R. G. ( 2005 ). The Cambridge handbook of thinking and reasoning . New York: Cambridge University Press.

Mayer, R. E. , & Wittrock, M. C. ( 2006 ). Problem solving. In P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (2nd ed., pp. 287–304). Mahwah, NJ: Erlbaum.

Sternberg, R. J. , & Ben-Zeev, T. ( 2001 ). Complex cognition: The psychology of human thought . New York: Oxford University Press.

Weisberg, R. W. ( 2006 ). Creativity . New York: Wiley.

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In This Article Expand or collapse the "in this article" section Problem Solving and Decision Making

Introduction.

• General Approaches to Problem Solving
• Representational Accounts
• Problem Space and Search
• Working Memory and Problem Solving
• Domain-Specific Problem Solving
• The Rational Approach
• Prospect Theory
• Dual-Process Theory
• Cognitive Heuristics and Biases

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Problem Solving and Decision Making by Emily G. Nielsen , John Paul Minda LAST REVIEWED: 26 June 2019 LAST MODIFIED: 26 June 2019 DOI: 10.1093/obo/9780199828340-0246

Problem solving and decision making are both examples of complex, higher-order thinking. Both involve the assessment of the environment, the involvement of working memory or short-term memory, reliance on long term memory, effects of knowledge, and the application of heuristics to complete a behavior. A problem can be defined as an impasse or gap between a current state and a desired goal state. Problem solving is the set of cognitive operations that a person engages in to change the current state, to go beyond the impasse, and achieve a desired outcome. Problem solving involves the mental representation of the problem state and the manipulation of this representation in order to move closer to the goal. Problems can vary in complexity, abstraction, and how well defined (or not) the initial state and the goal state are. Research has generally approached problem solving by examining the behaviors and cognitive processes involved, and some work has examined problem solving using computational processes as well. Decision making is the process of selecting and choosing one action or behavior out of several alternatives. Like problem solving, decision making involves the coordination of memories and executive resources. Research on decision making has paid particular attention to the cognitive biases that account for suboptimal decisions and decisions that deviate from rationality. The current bibliography first outlines some general resources on the psychology of problem solving and decision making before examining each of these topics in detail. Specifically, this review covers cognitive, neuroscientific, and computational approaches to problem solving, as well as decision making models and cognitive heuristics and biases.

General Overviews

Current research in the area of problem solving and decision making is published in both general and specialized scientific journals. Theoretical and scholarly work is often summarized and developed in full-length books and chapter. These may focus on the subfields of problem solving and decision making or the larger field of thinking and higher-order cognition.

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Educational Psychology: Learning and Instruction

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Educational psychology is a field that straddles two large domains: education and psychology. Reaching far back into antiquity, the field was borne from philosophies and theories that weaved back and forth between each domain all with the intent of understanding the way learners learn, teachers teach, and educational settings should be effectively designed. This chapter tells the story of educational psychology – its evolution, its characteristics, and the insights it provides for understanding it as a field of study, teaching it at the tertiary level of education, and leveraging its findings in the classroom. The chapter begins with a rationale for a curriculum of educational psychology, tracing its core teaching and learning objectives. It describes the topics that are core to the field, as well as the theory-based and evidence-based strategies and approaches for teaching it effectively. It discusses the basic principles of effective teaching, including problem-based learning, inquiry-based learning, and small-group and service-based learning, among others. Finally, it addresses technology in learning, open-university teaching and learning, and closes with a discussion of the best approaches – both theory-based and evidence-based – for assessing the core competencies of the field.

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Abd-El-Khalick, F., Boujaoude, S., Duschl, R., Lederman, N. G., Mamlok-Naaman, R., Hofstein, A., … Tuan, H. L. (2004). Inquiry in science education: International perspectives. Science Education, 88 (3), 397–419.

Article   Google Scholar  

Adler, M. (Ed.). (1952). The great ideas: A syntopicon of the great books of the Western world . Encyclopedia Britannica.

Google Scholar  

Aguilera-Hermida, A. P. (2020). College students’ use and acceptance of emergency online learning due to Covid-19. International Journal of Educational Research Open, 1 (2020), 100011.

Alba, J. W., & Hasher, L. (1983). Is memory schematic? Psychological Bulletin, 93 (2), 203.

Al Janabi, H. F., Aydin, A., Palaneer, S., Macchione, N., Al-Jabir, A., Khan, M. S., … Ahmed, K. (2020). Effectiveness of the HoloLens mixed-reality headset in minimally invasive surgery: A simulation-based feasibility study. Surgical Endoscopy, 34 (3), 1143–1149.

Aleven, V., McLaughlin, E. A., Glenn, R. A., & Koedinger, K. R. (2016). Instruction based on adaptive learning technologies. In R. E. Mayer & P. Alexander (Eds.), Handbook of research on learning and instruction (pp. 522–560). Taylor & Francis.

Alfieri, L., Brooks, P. J., Aldrich, N. J., & Tenenbaum, H. R. (2011). Does discovery-based instruction enhance learning? Journal of Educational Psychology, 103 (1), 1–18.

Ali, W. (2020). Online and remote learning in higher education institutes: A necessity in light of COVID-19 pandemic. Higher Education, 10 (3), 16–25.

American Psychological Association. (2012). A practical guidebook for the competency benchmarks . American Psychological Association.

American Psychological Association. (2016). Revision of Ethical Standard 3.04 of the “Ethical Principles of Psychologists and Code of Conduct” (2002, as amended 2010). The American Psychologist , 71 (9), 900.

Anderson, L. M., Blumenfeld, P., Pintrich, P. R., Clark, C. M., Marx, R. W., & Peterson, P. (1995). Educational psychology for teachers: Reforming our courses, rethinking our roles. Educational Psychologist, 30 (3), 143–157.

APA Presidential Task Force on Evidence-Based Practice. (2006). Evidence-based practice in psychology. The American Psychologist, 61 (4), 271.

Ausubel, D. P. (1960). The use of advance organizers in the learning and retention of meaningful verbal material. Journal of Educational Psychology, 51 (5), 267.

Ausubel, D. P. (1968). Educational Psychology: A cognitive view . Holt Rinehart and Winston.

Bandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84 (2), 191.

Berliner, D. C. (1993). The 100-year journey of educational psychology: From interest, to disdain, to respect for practice . In T. K. Fagan & G. R. VandenBos (Eds.), Master lectures in psychology. Exploring applied psychology: Origins and critical analyses (pp. 37–78). American Psychological Association. https://doi-org.mantis.csuchico.edu/10.1037/11104-002

Berliner, D. C. (2006). Educational psychology: Searching for essence throughout a century of influence. In I. P. A. Alexander & P. H. Winne (Eds.), Handbook of educational psychology (pp. 3–28). Routledge.

Bernacki, M. L., Crompton, H., & Greene, J. A. (2020). Towards convergence of mobile and psychological theories of learning. Contemporary Educational Psychology, 60 (2020), 101828.

Berninger, V. W. (Ed.). (2012). Past, present, and future contribution of cognitive writing research to cognitive psychology . Psychology Press.

Black, P., & Wiliam, D. (1998). Assessment and classroom learning. Assessment in Education: Principles, Policy & Practice, 5 (1), 7–74.

Black, P., & Wiliam, D. (2009). Developing the theory of formative assessment. Educational Assessment, Evaluation and Accountability, 21 (1), 5–31.

Boland, J. A. (2014). Orientations to civic engagement: Insights into the sustainability of a challenging pedagogy. Studies in Higher Education, 39 (1), 180–195.

Boud, D. (2000). Sustainable assessment: Rethinking assessment for the learning society. Studies in Continuing Education, 22 (2), 151–167.

Boyce, T. E., & Hineline, P. N. (2002). Interteaching: A strategy for enhancing the user-friendliness of behavioral arrangements in the college classroom. The Behavior Analyst, 25 (2), 215–226.

Boyle, J., & Kelly, B. (2016). The role of evidence in educational psychology. In B. Kelly, L. M. Woolfson, & J. Boyle (Eds.), Frameworks for practice in educational psychology: A textbook for trainees and practitioners (2nd ed.). Jessica Kingsley Publishers.

Bransford, J. D., Brown, A. L., & Cocklin, R. R. (2000). How people learn: Brain, mind, experience, and school: Expanded edition. In National Research Council (Ed.), Early childhood development and learning: New knowledge for policy (pp. 57–86). National Academy Press.

Brown, M., McCormack, M., Reeves, J., Brooks, D. C., Grajek, S., Alexander, B., … Weber, N. (2020). 2020 Educause horizon report: Teaching and learning edition . EDUCAUSE.

Burgess, A. W., McGregor, D. M., & Mellis, C. M. (2014). Applying established guidelines to team-based learning programs in medical schools: A systematic review. Academic Medicine, 89 (4), 678–688.

Buskist, W. (2013). Preparing the new psychology professoriate to teach: Past, present, and future. Teaching of Psychology, 40 (4), 333–339.

Butler, A. C., & Roediger, H. L., III. (2007). Testing improves long-term retention in a simulated classroom setting. European Journal of Cognitive Psychology, 19 (4–5), 514–527.

Carpenter, S. K. (2012). Testing enhances the transfer of learning. Current Directions in Psychological Science, 21 (5), 279–283.

Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: A review and quantitative synthesis. Psychological Bulletin, 132 (3), 354–380.

Charles, D. C. (1987). The emergence of educational psychology. In J. A. Glover & R. R. Ronning (Eds.), Historical foundations of educational psychology . Plenum Press.

Chi, M. T., Feltovich, P. J., & Glaser, R. (1981). Categorization and representation of physics problems by experts and novices. Cognitive Science, 5 (2), 121–152.

Clark, J. M., & Paivio, A. (1991). Dual coding theory and education. Educational Psychology Review, 3 (3), 149–210.

Collins, A. (1991). Cognitive apprenticeship and instructional technology. Educational values and cognitive instruction: Implications for reform, 1991 , 121–138.

Collins, A., Brown, J. S., & Holum, A. (1991). Cognitive apprenticeship: Making thinking visible. American Educator, 15 (3), 6–11.

Craik, F. I., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11 (6), 671–684.

Cranney, J., & Dunn, D. S. (Eds.). (2011). The psychologically literate citizen: Foundations and global perspectives . Oxford University Press.

Cranney, J., & Voudouris, N. J. (2012). Psychology education and training in Australia: Shaping the future. In S. McCarthy, K. L. Dickson, J. Cranney, V. Karandashev, & A. Trapp (Eds.), Teaching psychology around the world (Vol. 3, pp. 2–14). Cambridge Scholars Press.

Cranney, J. (2013). Towards psychological literacy: A snapshot of evidence-based learning and teaching. Australian Journal of Psychology, 65 , 1–4.

Crompton, H., Bernacki, M., & Greene, J. A. (2020). Psychological foundations of emerging technologies for teaching and learning in higher education. Current Opinion in Psychology, 36 , 101–105.

Cronin, C. (2017). Openness and praxis: Exploring the use of open educational practices in higher education. The International Review of Research in Open and Distance Learning, 18 (5), 15–34.

Darling-Hammond, L., & Baratz-Snowden, J. (2007). A good teacher in every classroom: Preparing the highly qualified teachers our children deserve. Educational Horizons, 85 (2), 111–132.

de Jong, T., Sotiriou, S., & Gillet, D. (2014). Innovations in STEM education: The Go-Lab federation of online labs. Smart Learning Environments, 1 (3), 1–16.

Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14 (1), 4–58.

Dunn, D. S., Saville, B. K., Baker, S. C., & Marek, P. (2013). Evidence-based teaching: Tools and techniques that promote learning in the psychology classroom. Australian Journal of Psychology, 65 (1), 5–13.

Dunn, D. S. (1994). Lessons learned from an interdisciplinary-writing course: Implications for student writing in psychology. Teaching of Psychology, 21 (4), 223–227.

Dunn, D. (2011). A short guide to writing about psychology (3rd ed.). Longman.

Dutke, S., Bakker, H. E., Papageorgi, I., & Taylor, J. (2017). PLAT 16 (2) 2017: Introduction to the special issue on evidence-based teaching (EBT): Examples from learning and teaching psychology. Psychology of Learning & Teaching, 16 (2), 175–178.

Dutke, S., Bakker, H., Sokolová, L., Stuchlikova, I., Salvatore, S., & Papageorgi, I. (2019). Psychology curricula for non-psychologists? A framework recommended by the European Federation of Psychologists’ Associations’ Board of Educational Affairs. Psychology Learning & Teaching, 18 (2), 111–120.

Dweck, C. S., & Leggett, E. L. (1988). A social-cognitive approach to motivation and personality. Psychological Review, 95 (2), 256.

Educational Testing Service. (2004). Study guide: Principles of learning and teaching (2nd ed.). Educational Testing Service.

Educational Testing Service. (2009). About the praxis series™ tests . Educational Testing Service.

Fischer, C., Pardos, Z. A., Baker, R. S., Williams, J. J., Smyth, P., Yu, R., … Warschauer, M. (2020). Mining big data in education: Affordances and challenges. Review of Research in Education, 44 (1), 130–160.

Fiske, E. B. (2002). Learning in deed: The power of service-learning for American schools . National Commission on Service-Learning.

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

Gikandi, J. W., Morrow, D., & Davis, N. E. (2011). Online formative assessment in higher education: A review of the literature. Computers & Education, 57 (4), 2333–2351.

Greenwood, G. E., & Fillmer, H. T. (1999). Educational psychology cases for teacher decision-making . Merrill.

Gurung, R. A., Hackathorn, J., Enns, C., Frantz, S., Cacioppo, J. T., Loop, T., & Freeman, J. E. (2016). Strengthening introductory psychology: A new model for teaching the introductory course. American Psychologist, 71 (2), 112–124.

Haidet, P., Kubitz, K., & McCormack, W. T. (2014). Analysis of the team-based learning literature: TBL comes of age. Journal on Excellence in College Teaching, 25 (3–4), 303–333.

Harrison, C. J., Könings, K. D., Molyneux, A., Schuwirth, L. W., Wass, V., & van der Vleuten, C. P. (2013). Web-based feedback after summative assessment: How do students engage? Medical Education, 47 (7), 734–744.

Harrison, C. J., Könings, K. D., Schuwirth, L., Wass, V., & van der Vleuten, C. (2015). Barriers to the uptake and use of feedback in the context of summative assessment. Advances in Health Sciences Education, 20 (1), 229–245.

Hattie, J. (2009). Visible learning. A synthesis of over 800 meta-analyses relating to achievement . Routledge.

Hattie, J. (2012). Visible learning for teachers: Maximizing impact on learning . Routledge.

Book   Google Scholar  

Heeneman, S., Schut, S., Donkers, J., van der Vleuten, C., & Muijtjens, A. (2017). Embedding of the progress test in an assessment program designed according to the principles of programmatic assessment. Medical Teacher, 39 (1), 44–52.

Hmelo, C. E. (1998). Problem-based learning: Effects on the early acquisition of cognitive skill in medicine. Journal of Learning Science, 7 (2), 173–208.

Hoy, A. W. (2019). Educational psychology . Pearson.

Hung, W., Jonassen, D. H., & Liu, R. (2008). Problem-based learning. In: Handbook of Research on Educational Communications and Technology, 3 (1), 485–506.

Interstate New Teacher Assessment and Support Consortium. (1992). Model standards for beginning teacher licensing, assessment and development: A resource for state dialogue. Interstate New Teacher Assessment and Support Consortium.

James, W. (1890). Principles of psychology . New York: Henry Holt. Reprinted : Harvard.

James, W. (1983). Talks to teachers on psychology and to students on some of life’s ideals . Harvard University Press. (Original work published 1899).

Karpicke, J. D., Butler, A. C., & Roediger, H. L., III. (2009). Metacognitive strategies in student learning: Do students practise retrieval when they study on their own? Memory, 17 (4), 471–479.

Katz, J., DuBois, M., & Wigderson, S. (2014). Learning by helping? Undergraduate communication outcomes associated with training or service-learning experiences. Teaching of Psychology, 41 (3), 251–255.

Kebritchi, M., Lipschuetz, A., & Santiague, L. (2017). Issues and challenges for teaching successful online courses in higher education: A literature review. Journal of Educational Technology Systems, 46 (1), 4–29.

Kelly, B. (2016). Frameworks for practice in educational psychology. In B. Kelly, L. M. Woolfson, & J. Boyle (Eds.), Frameworks for practice in educational psychology: A textbook for trainees and practitioners (2nd ed.). Jessica Kingsley Publishers.

Keselman, A. (2003). Supporting inquiry learning by promoting normative understanding of multivariable causality. Journal of Research in Science Teaching, 40 (9), 898–921.

Kibble, J. D. (2017). Best practices in summative assessment. Advances in Physiology Education, 41 , 110–119.

Kirschner, P. A., & Hendrick, C. (2020). How learning happens: Seminal works in educational psychology and what they mean in practice . Routledge.

Klieme, E., & Maag Merki, K. (2008). Introduction of educational standards in German-speaking countries. In J. Hartig, E. Klieme, & D. Leutner (Eds.), Assessment of competencies in educational contexts (pp. 215–224). Hogrefe.

Lazonder, A. W., & Harmsen, R. (2016). Meta-analysis of inquiry-based learning: Effects of guidance. Review of Educational Research, 86 (3), 681–718.

Liu, S. N. C., & Beaujean, A. A. (2017). The effectiveness of team-based learning on academic outcomes: A meta-analysis. Scholarship of Teaching and Learning in Psychology, 3 (1), 1–14.

Lohse-Bossenz, H., Kunina-Habenicht, O., & Kunter, M. (2013). The role of educational psychology in teacher education: Expert opinions on what teachers should know about learning, development, and assessment. European Journal of Psychology of Education, 28 (4), 1543–1565.

Lou, Y., Bernard, R. M., & Abrami, P. C. (2006). Media and pedagogy in undergraduate distance education: A theory-based meta-analysis of empirical literature. Educational Technology Research and Development, 54 (2), 141–176.

Macías Gomez-Estern, B., Arias-Sánchez, S., Marco Macarro, M. J., Cabillas Romero, M. R., & Martínez Lozano, V. (2019). Does service learning make a difference? Comparing students’ valuations in service learning and non-service learning teaching of psychology. Studies in Higher Education , 1–11.

McCutcheon, K., Lohan, M., Traynor, M., & Martin, D. (2015). A systematic review evaluating the impact of online or blended learning vs. face-to-face learning of clinical skills in undergraduate nurse education. Journal of Advanced Nursing, 71 (2), 255–270.

Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2009). Evaluation of evidence-based practices in online learning: A meta-analysis and review of online learning studies. US Department of Education.

Merrill, M. D. (2002). First principles of instruction. Educational Technology Research and Development, 50 (3), 43–59.

Mayer, R. E. (2005). Cognitive theory of multimedia learning. The Cambridge handbook of multimedia learning, 41 , 31–48.

Meyer, C. L., Harned, M., Schaad, A., Sunder, K., Palmer, J., & Tinch, C. (2016). Inmate education as a service learning opportunity for students: Preparation, benefits, and lessons learned. Teaching of Psychology, 43 (2), 120–125.

Michaelsen, L. K., & Sweet, M. (2008). The essential elements of team-based learning. New Directions for Teaching and Learning, 2008 (116), 7–27.

Narciss, S. (2019). Curriculum design for (non-) psychology programs–a reflection on general and specific issues, and approaches on how to address them: Comment on Dutke et al., 2019. Psychology Learning & Teaching, 18 (2), 144–147.

Nash, J. M., & Larkin, K. T. (2012). Geometric models of competency development in specialty areas of professional psychology. Training and Education in Professional Psychology, 6 (1), 37.

National Center for Education Statistics. (2019). Integrated postsecondary education data system (IPEDS) fall 2000 through fall 2018, completions component. US Department of Education.

National Council for the Accreditation of Teacher Education. (2008). Professional standards for the accreditation of teacher preparation institutions. National Council for the Accreditation of Teacher Education.

Nguyen, T. (2015). The effectiveness of online learning: Beyond no significant difference and future horizons. MERLOT Journal of Online Learning and Teaching, 11 (2), 309–319.

Nicol, D. J., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31 (2), 199–218.

Nicol, D. (2010). From monologue to dialogue: Improving written feedback processes in mass higher education. Assessment & Evaluation in Higher Education, 35 (5), 501–517.

Nichols, M. (2003). A theory for eLearning. Journal of Educational Technology & Society, 6 (2), 1–10.

Oliver, R. (1999). Exploring strategies for online teaching and learning. Distance Education, 20 (2), 240–254.

Ormrod, J. E. (2006). Commentary: Similarities and differences among educational psychology textbooks: An author’s perspective. Teaching Educational Psychology, 1 (3), 1–4.

Ormrod, J. E., Anderman, E. M., & Anderman, L. H. (2020). Educational psychology: Developing learners . Pearson.

Ormrod, J. E., & McGuire, D. J. (Eds.). (2007). Case studies: Applying educational psychology (2nd ed.). Merrill.

Parmelee, D., Michaelsen, L. K., Cook, S., & Hudes, P. D. (2012). Team-based learning: A practical guide: AMEE guide no. 65. Medical Teacher, 34 (5), e275–e287.

Patrick, H., Anderman, L. H., Bruening, P. S., & Duffin, L. C. (2011). The role of educational psychology in teacher education: Three challenges for educational psychologists. Educational Psychologist, 46 (2), 71–83.

Palincsar, A. S., & Brown, A. L. (1984). Reciprocal teaching of comprehension-fostering and comprehension-monitoring activities. Cognition and Instruction, 1 (2), 117–175.

Pedaste, M., Mäeots, M., Siiman, L. A., De Jong, T., Van Riesen, S. A., Kamp, E. T., … Tsourlidaki, E. (2015). Phases of inquiry-based learning: Definitions and the inquiry cycle. Educational Research Review, 14 (2015), 47–61.

Peterson, R. L., Peterson, D. R., Abrams, J. C., Stricker, G., & Ducheny, K. (2010). The National Council of schools and programs of professional psychology: Educational model 2009. In M. B. Kenkel & R. L. Peterson (Eds.), Competency-based education for professional psychology (pp. 13–42). American Psychological Association.

Chapter   Google Scholar  

Petticrew, M., & Roberts, H. (2003). Evidence, hierarchies, and typologies: Horses for courses. Journal of Epidemiology & Community Health, 57 (7), 527–529.

Pilcher, J., & Bedford, L. A. (2011). Hierarchies of evidence in education. The Journal of Continuing Education in Nursing, 42 (8), 371–377.

Pintrich, P. R. (2000). Multiple goals, multiple pathways: The role of goal orientation in learning and achievement. Journal of Educational Psychology, 92 (3), 544.

Popenici, S. A., & Kerr, S. (2017). Exploring the impact of artificial intelligence on teaching and learning in higher education. Research and Practice in Technology Enhanced Learning, 12 (1), 1–13.

Queensland College of Teachers, Professional Standards Unit. (2011). Australian professional standards for teachers . Queensland College of Teachers.

Quintilian, F. B. (1953). Institutio oratoria (4 Vols.; H. E. Butler, Trans.). Harvard University Press.

Quintilian, F. B. (1966). Quintilian on education (W. M. Smail, Trans.). Teachers College Press.

Reigeluth, C. M., & Stein, F. (1983). The elaboration theory of instruction. In C. M. Reigeluth (Ed.), Instructional design theories and models (pp. 335–381). Erlbaum.

Rockquemore, K. A., & Harwell Schaffer, R. (2000). Toward a theory of engagement: A cognitive mapping of service-learning experiences. Michigan Journal of Community Service Learning, 7 (1), 14–25.

Rodolfa, E., Bent, R., Eisman, E., Nelson, P., Rehm, L., & Ritchie, P. (2005). A cube model for competency development: Implications for psychology educators and regulators. Professional Psychology: Research and Practice, 36 (4), 347.

Roediger, H. L., III, & Karpicke, J. D. (2006). Test-enhanced learning: Taking memory tests improves long-term retention. Psychological Science, 17 (3), 249–255.

Sadler, D. R. (1989). Formative assessment and the design of instructional systems. Instructional Science, 18 (2), 119–144.

Sadler, D. R. (1998). Formative assessment: Revisiting the territory. Assessment in Education: Principles, Policy & Practice, 5 (1), 77–84.

Santrock, J. W. (2021). Educational psychology . McGraw-Hill.

Saville, B. K., & Zinn, T. E. (2009). Interteaching: The effects of quality points on exam scores. Journal of Applied Behavior Analysis, 42 (2), 369–374.

Saville, B. K., Lambert, T., & Robertson, S. (2011). Interteaching: Bringing behavioral education into the 21st century. The Psychological Record, 61 (1), 153–165.

Schwieren, J., Barenberg, J., & Dutke, S. (2017). The testing effect in the psychology classroom: A meta-analytic perspective. Psychology Learning & Teaching, 16 (2), 179–196.

Shek, D. T. L., Ma, C. M. S., & Yang, Z. (2019). Transformation and development of university students through service-learning: A corporate-community-university partnership initiative in Hong Kong (Project WeCan). Applied Research in Quality of Life, 15 (2020), 1375–1393.

Sibley, J., & Ostafichuk, P. (2015). Getting started with team-based learning. Stylus Publishing, LLC.

Slavin, R. E. (2021). Educational psychology: Theory and practice . Pearson.

Slovak Centre of Scientific and Technical Information. (2018). Štatistická ročenka - vysoké školy [Statistic yearbook – higher education] . Ministerstvo školstva, vedy, výskumu a športu Slovenskej Republiky [Ministry of Education, Science, Research and Sports of the Slovak Republic].

Snowman, J., & McCown, R. R. (2015). Educational psychology . Wadsworth/Cengage Learning.

Statistisches Bundesamt. (2017). Bildung und Kultur. Prüfungen an Hochschulen 2016 [Education and culture. Examinations at universities 2016] . Statistisches Bundesamt.

Sudzina, M. R. (1997). Case study as a constructivist pedagogy for teaching educational psychology. Educational Psychology Review, 9 (2), 199–218.

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12 (2), 257–285.

Sweller, J. (2020). Cognitive load theory and educational technology. Educational Technology Research and Development, 68 (1), 1–16.

Taras, M. (2005). Assessment–summative and formative–some theoretical reflections. British Journal of Educational Studies, 53 (4), 466–478.

Thorndike, E. L. (1910). The contribution of psychology to education. Journal of Educational Psychology, 1 , 5–12.

Training and Development Agency for Schools. (2007). Professional standards for teachers. Training and Development Agency.

Trapp, A., Banister, P., Ellis, J., Latto, R., Miell, D., & Upton, D. (2011). The future of undergraduate psychology in the United Kingdom. Higher Education Academy Psychology Network, University of York.

Van de Pol, J., Volman, M., & Beishuizen, J. (2010). Scaffolding in teacher–student interaction: A decade of research. Educational Psychology Review, 22 (3), 271–296.

van der Vleuten, C. P., Schuwirth, L. W. T., Driessen, E. W., Dijkstra, J., Tigelaar, D., Baartman, L. K. J., & van Tartwijk, J. (2012). A model for programmatic assessment fit for purpose. Medical Teacher, 34 (3), 205–214.

van Rens, L., Van Dijk, H., Mulder, J., & Nieuwland, P. (2013). Using a web application to conduct and investigate syntheses of methyl orange remotely. Journal of Chemical Education, 90 (5), 574–577.

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46 (4), 197–221.

Vives, J. L. (1913). De tradendis disciplinis. In Vives on education (F. Watson, Trans.). Cambridge University Press. (Original work published 1531).

Wahlheim, C. N., Dunlosky, J., & Jacoby, L. L. (2011). Spacing enhances the learning of natural concepts: An investigation of mechanisms, metacognition, and aging. Memory & Cognition, 39 (5), 750–763.

Watson, R. I. (1961). A brief history of educational psychology. Psychological Record, 11 , 209–242.

Weiner, B. (1985). An attributional theory of achievement motivation and emotion. Psychological Review, 92 (4), 548.

Weller, M., Jordan, K., DeVries, I., & Rolfe, V. (2018). Mapping the open education landscape: Citation network analysis of historical open and distance education research. Open Praxis, 10 (2), 109–126.

Wiggins, S., Chiriac, E. H., Abbad, G. L., Pauli, R., & Worrell, M. (2016). Ask not only ‘what can problem-based learning do for psychology?’ but ‘what can psychology do for problem-based learning?’ A review of the relevance of problem-based learning for psychology teaching and research. Psychology Learning & Teaching, 15 (2), 136–154.

Wilson-Doenges, G., & Gurung, R. A. R. (2013). Benchmarks for scholarly investigations of teaching and learning. Australian Journal of Psychology, 65 (1), 63–70.

Woolfolk Hoy, A. (1996). Teaching educational psychology: Texts in context. Educational Psychologist, 31 (1), 41–49.

Woolfolk Hoy, A. (2000). Educational psychology in teacher education. Educational Psychologist, 35 (4), 257–270.

Woolfolk Hoy, A. (2008). Educational psychology in teacher education . Teachers College Record.

Yorke, M. (2003). Formative assessment in higher education: Moves towards theory and the enhancement of pedagogic practice. Higher Education, 45 (4), 477–501.

Zheng, L., Li, X., Tian, L., & Cui, P. (2018). The effectiveness of integrating mobile devices with inquiry-based learning on students’ learning achievements: A meta-analysis. International Journal of Mobile Learning and Organisation, 12 (1), 77–95.

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81 (3), 329.

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Schwartz, N., Click, K., Bartel, A. (2022). Educational Psychology: Learning and Instruction. In: Zumbach, J., Bernstein, D., Narciss, S., Marsico, G. (eds) International Handbook of Psychology Learning and Teaching. Springer International Handbooks of Education. Springer, Cham. https://doi.org/10.1007/978-3-030-26248-8_67-1

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Definition:

Problem Solving is the process of identifying, analyzing, and finding effective solutions to complex issues or challenges.

Key Steps in Problem Solving:

• Identification of the problem: Recognizing and clearly defining the issue that needs to be resolved.
• Analysis and research: Gathering relevant information, data, and facts to understand the problem in-depth.
• Formulating strategies: Developing various approaches and plans to tackle the problem effectively.
• Evaluation and selection: Assessing the viability and potential outcomes of the proposed solutions and selecting the most appropriate one.
• Implementation: Putting the chosen solution into action and executing the necessary steps to resolve the problem.
• Monitoring and feedback: Continuously evaluating the implemented solution and obtaining feedback to ensure its effectiveness.
• Adaptation and improvement: Modifying and refining the solution as needed to optimize results and prevent similar problems from arising in the future.

Skills and Qualities for Effective Problem Solving:

• Analytical thinking: The ability to break down complex problems into smaller, manageable components and analyze them thoroughly.
• Creativity: Thinking outside the box and generating innovative solutions.
• Decision making: Making logical and informed choices based on available data and critical thinking.
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• Resilience: Maintaining a positive mindset, perseverance, and adaptability in the face of challenges.
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• Time management: Effectively organizing and prioritizing tasks to optimize problem-solving efficiency.

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What Is Educational Psychology?

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Amy Morin, LCSW, is a psychotherapist and international bestselling author. Her books, including "13 Things Mentally Strong People Don't Do," have been translated into more than 40 languages. Her TEDx talk,  "The Secret of Becoming Mentally Strong," is one of the most viewed talks of all time.

• Major Perspectives
• Topics of Study

Frequently Asked Questions

Educational psychology is the study of how people learn , including teaching methods, instructional processes, and individual differences in learning. It explores the cognitive, behavioral, emotional, and social influences on the learning process. Educational psychologists use this understanding of how people learn to develop instructional strategies and help students succeed in school.

This branch of psychology focuses on the learning process of early childhood and adolescence. However, it also explores the social, emotional, and cognitive processes that are involved in learning throughout the entire lifespan.

The field of educational psychology incorporates a number of other disciplines, including developmental psychology , behavioral psychology , and cognitive psychology . Approaches to educational psychology include behavioral, developmental, cognitive, constructivist, and experiential perspectives.

This article discusses some of the different perspectives taken within the field of educational psychology, topics that educational psychologists study, and career options in this field.

8 Things to Know About Educational Psychology

Perspectives in educational psychology.

As with other areas of psychology, researchers within educational psychology tend to take on different perspectives when considering a problem. These perspectives focus on specific factors that influence learning, including learned behaviors, cognition, experiences, and more.

The Behavioral Perspective

This perspective suggests that all behaviors are learned through conditioning. Psychologists who take this perspective rely firmly on the principles of operant conditioning to explain how learning happens.

For example, teachers might reward learning by giving students tokens that can be exchanged for desirable items such as candy or toys. The behavioral perspective operates on the theory that students will learn when rewarded for "good" behavior and punished for "bad" behavior.

While such methods can be useful in some cases, the behavioral approach has been criticized for failing to account for attitudes , emotions, and intrinsic motivations for learning.

The Developmental Perspective

This perspective focuses on how children acquire new skills and knowledge as they develop. Jean Piaget's stages of cognitive development is one example of an important developmental theory looking at how children grow intellectually.

By understanding how children think at different stages of development, educational psychologists can better understand what children are capable of at each point of their growth. This can help educators create instructional methods and materials aimed at certain age groups.

The Cognitive Perspective

The cognitive approach has become much more widespread, mainly because it accounts for how factors such as memories, beliefs, emotions , and motivations contribute to the learning process. This theory supports the idea that a person learns as a result of their own motivation, not as a result of external rewards.

Cognitive psychology aims to understand how people think, learn, remember, and process information.

Educational psychologists who take a cognitive perspective are interested in understanding how kids become motivated to learn, how they remember the things that they learn, and how they solve problems, among other topics.

The Constructivist Approach

This perspective focuses on how we actively construct our knowledge of the world. Constructivism accounts for the social and cultural influences that affect how we learn.

Those who take the constructivist approach believe that what a person already knows is the biggest influence on how they learn new information. This means that new knowledge can only be added on to and understood in terms of existing knowledge.

This perspective is heavily influenced by the work of psychologist Lev Vygotsky , who proposed ideas such as the zone of proximal development and instructional scaffolding.

Experiential Perspective

This perspective emphasizes that a person's own life experiences influence how they understand new information. This method is similar to constructivist and cognitive perspectives in that it takes into consideration the experiences, thoughts, and feelings of the learner.

This method allows someone to find personal meaning in what they learn instead of feeling that the information doesn't apply to them.

Different perspectives on human behavior can be useful when looking at topics within the field of educational psychology. Some of these include the behavioral perspective, the constructivist approach, and the experiential perspective.

Topics in Educational Psychology

From the materials teachers use to the individual needs of students, educational psychologists delve deep to more fully understand the learning process. Some these topics of study in educational psychology include:

• Educational technology : Looking at how different types of technology can help students learn
• Instructional design : Designing effective learning materials
• Special education : Helping students who may need specialized instruction
• Curriculum development : Creating coursework that will maximize learning
• Organizational learning : Studying how people learn in organizational settings, such as workplaces
• Gifted learners : Helping students who are identified as gifted learners

Careers in Educational Psychology

Educational psychologists work with educators, administrators, teachers, and students to analyze how to help people learn best. This often involves finding ways to identify students who may need extra help, developing programs for students who are struggling, and even creating new learning methods .

Many educational psychologists work with schools directly. Some are teachers or professors, while others work with teachers to try out new learning methods for their students and develop new course curricula. An educational psychologist may even become a counselor, helping students cope with learning barriers directly.

Other educational psychologists work in research. For instance, they might work for a government organization such as the U.S. Department of Education, influencing decisions about the best ways for kids to learn in schools across the nation.

In addition, an educational psychologist work in school or university administration. In all of these roles, they can influence educational methods and help students learn in a way that best suits them.

A bachelor's degree and master's degree are usually required for careers in this field; if you want to work at a university or in school administration, you may need to complete a doctorate as well.

Educational psychologists often work in school to help students and teachers improve the learning experience. Other professionals in this field work in research to investigate the learning process and to evaluate programs designed to foster learning.

History of Educational Psychology

Educational psychology is a relatively young subfield that has experienced a tremendous amount of growth. Psychology did not emerge as a separate science until the late 1800s, so earlier interest in educational psychology was largely fueled by educational philosophers.

Many regard philosopher Johann Herbart as the father of educational psychology.

Herbart believed that a student's interest in a topic had a tremendous influence on the learning outcome. He believed teachers should consider this when deciding which type of instruction is most appropriate.

Later, psychologist and philosopher William James made significant contributions to the field. His seminal 1899 text "Talks to Teachers on Psychology" is considered the first textbook on educational psychology.

Around this same period, French psychologist Alfred Binet was developing his famous IQ tests. The tests were originally designed to help the French government identify children who had developmental delays and create special education programs.

In the United States, John Dewey had a significant influence on education. Dewey's ideas were progressive; he believed schools should focus on students rather than on subjects. He advocated active learning, arguing that hands-on experience was an important part of the process.

More recently, educational psychologist Benjamin Bloom developed an important taxonomy designed to categorize and describe different educational objectives. The three top-level domains he described were cognitive, affective, and psychomotor learning objectives.

Significant Figures

Throughout history, a number of additional figures have played an important role in the development of educational psychology. Some of these well-known individuals include:

• John Locke : Locke is an English philosopher who suggested the concept of tabula rasa , or the idea that the mind is essentially a blank slate at birth. This means that knowledge is developed through experience and learning.
• Jean Piaget : A Swiss psychologist who is best known for his highly influential theory of cognitive development, Jean Piaget's influence on educational psychology is still evident today.
• B.F. Skinner : Skinner was an American psychologist who introduced the concept of operant conditioning, which influences behaviorist perspectives. His research on reinforcement and punishment continues to play an important role in education.

Educational psychology has been influenced by a number of philosophers, psychologists, and educators. Some thinkers who had a significant influence include William James, Alfred Binet, John Dewey, Jean Piaget, and Benjamin Bloom.

A Word From Verywell

Educational psychology offers valuable insights into how people learn and plays an important role in informing educational strategies and teaching methods. In addition to exploring the learning process itself, different areas of educational psychology explore the emotional, social, and cognitive factors that can influence how people learn. If you are interested in topics such as special education, curriculum design, and educational technology, then you might want to consider pursuing a career in the field of educational psychology.

A master's in educational psychology can prepare you for a career working in K-12 schools, colleges and universities, government agencies, community organizations, and counseling practices. A career as an educational psychologist involves working with children, families, schools, and other community and government agencies to create programs and resources that enhance learning. 

The primary focus of educational psychology is the study of how people learn. This includes exploring the instructional processes, studying individual differences in how people learn, and developing teaching methods to help people learn more effectively.

Educational psychology is important because it has the potential to help both students and teachers. It provides important information for educators to help them create educational experiences, measure learning, and improve student motivation.

Educational psychology can aid teachers in better understanding the principles of learning in order to design more engaging and effective lesson plans and classroom experiences. It can also foster a better understanding of how learning environments, social factors, and student motivation can influence how students learn.

Parsonson BS. Evidence-based classroom behaviour management strategies . Kairaranga . 2012;13(1):16-20.

Welsh JA, Nix RL, Blair C, Bierman KL, Nelson KE. The development of cognitive skills and gains in academic school readiness for children from low-income families .  J Educ Psychol . 2010;102(1):43-53. doi:10.1037/a0016738

Babakr ZH, Mohamedamin P, Kakamad K. Piaget’s cognitive developmental theory: Critical review . Asian Institute of Research: Education Quarterly Reviews. 2019;2(3). doi:10.31014/aior.1993.02.03.84

Roediger HL III. Applying cognitive psychology to education . Psychol Sci Public Interest . 2013;14(1):1-3. doi:10.1177/1529100612454415

Dennick R. Constructivism: Reflections on twenty five years teaching the constructivist approach in medical education . Int J Med Educ . 2016;7:200-205. doi:10.5116/ijme.5763.de11

Binson B, Lev-Wiesel R. Promoting personal growth through experiential learning: The case of expressive arts therapy for lecturers in Thailand . Front Psychol. 2018;8. doi:10.3389/fpsyg.2017.02276

Duque E, Gairal R, Molina S, Roca E. How the psychology of education contributes to research with a social impact on the education of students with special needs: The case of successful educational actions . Front Psychol. 2020;11. doi:10.3389/fpsyg.2020.00439

Barbier K, Donche V, Verschueren K. Academic (under)achievement of intellectually gifted students in the transition between primary and secondary education: An individual learner perspective . Front Psychol. 2019;10. doi:10.3389/fpsyg.2019.02533

American Psychological Association. Careers in psychology .

Greenfield PM. The changing psychology of culture from 1800 through 2000 . Psychol Sci. 2013;24(9):1722-1731. doi:10.1177/0956797613479387

Hogan JD, Devonis DC, Thomas RK, et al. Herbart, Johann Friedrich . In: Encyclopedia of the History of Psychological Theories . Springer US; 2012:508-510. doi:10.1007/978-1-4419-0463-8_134

Sutinen A. William James’s educational will to believe . In: Theories of Bildung and Growth . SensePublishers; 2012:213-226. doi:10.1007/978-94-6209-031-6_14

Michell J. Alfred Binet and the concept of heterogeneous orders . Front Psychol . 2012;3. doi:10.3389/fpsyg.2012.00261

Talebi K. John Dewey - philosopher and educational reformer . Eur J Educ Stud. 2015;1(1):1-4.

Anderson LW. Benjamin S. Bloom: His life, his works, and his legacy .  In: Zimmerman BJ, Schunk DH, eds.,  Educational Psychology: A Century of Contributions . Lawrence Erlbaum Associates Publishers.

Androne M. Notes on John Locke’s views on education . Procedia Soc Behav Sci. 2014;137:74-79. doi:10.1016/j.sbspro.2014.05.255

Overskeid G. Do we need the environment to explain operant behavior? . Front Psychol . 2018;9. doi:10.3389/fpsyg.2018.00373

American Psychological Association. Understanding educational psychology .

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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Problem solving through values: A challenge for thinking and capability development

• • This paper introduces the 4W framework of consistent problem solving through values.
• • The 4W suggests when, how and why the explication of values helps to solve a problem.
• • The 4W is significant to teach students to cope with problems having crucial consequences.
• • The paper considers challenges using such framework of thinking in different fields of education.

The paper aims to introduce the conceptual framework of problem solving through values. The framework consists of problem analysis, selection of value(s) as a background for the solution, the search for alternative ways of the solution, and the rationale for the solution. This framework reveals when, how, and why is important to think about values when solving problems. A consistent process fosters cohesive and creative value-based thinking during problem solving rather than teaching specific values. Therefore, the framework discloses the possibility for enabling the development of value-grounded problem solving capability.The application of this framework highlights the importance of responsibility for the chosen values that are the basis for the alternatives which determine actions. The 4W framework is meaningful for the people’s lives and their professional work. It is particularly important in the process of future professionals’ education. Critical issues concerning the development of problem solving through values are discussed when considering and examining options for the implementation of the 4W framework in educational institutions.

1. Introduction

The core competencies necessary for future professionals include problem solving based on complexity and collaborative approaches ( OECD, 2018 ). Currently, the emphasis is put on the development of technical, technological skills as well as system thinking and other cognitive abilities (e.g., Barber, 2018 ; Blanco, Schirmbeck, & Costa, 2018 ). Hence, education prepares learners with high qualifications yet lacking in moral values ( Nadda, 2017 ). Educational researchers (e.g., Barnett, 2007 ; Harland & Pickering, 2010 ) stress that such skills and abilities ( the how? ), as well as knowledge ( the what? ), are insufficient to educate a person for society and the world. The philosophy of education underlines both the epistemological and ontological dimensions of learning. Barnett (2007) points out that the ontological dimension has to be above the epistemological one. The ontological dimension encompasses the issues related to values that education should foster ( Harland & Pickering, 2010 ). In addition, values are closely related to the enablement of learners in educational environments ( Jucevičienė et al., 2010 ). For these reasons, ‘ the why ?’ based on values is required in the learning process. The question arises as to what values and how it makes sense to educate them. Value-based education seeks to address these issues and concentrates on values transfer due to their integration into the curriculum. Yazdani and Akbarilakeh (2017) discussed that value-based education could only convey factual knowledge of values and ethics. However, such education does not guarantee the internalization of values. Nevertheless, value-based education indicates problem solving as one of the possibilities to develop values.

Values guide and affect personal behavior encompassing the ethical aspects of solutions ( Roccas, Sagiv, & Navon, 2017 ; Schwartz, 1992 , 2012 ; Verplanken & Holland, 2002 ). Therefore, they represent the essential foundation for solving a problem. Growing evidence indicates the creative potential of values ( Dollinger, Burke, & Gump, 2007 ; Kasof, Chen, Himsel, & Greenberger, 2007 ; Lebedeva et al., 2019) and emphasizes their significance for problem solving. Meanwhile, research in problem solving pays little attention to values. Most of the problem solving models (e.g., Newell & Simon, 1972 ; Jonassen, 1997 ) utilize a rational economic approach. Principally, the research on the mechanisms of problem solving have been conducted under laboratory conditions performing simple tasks ( Csapó & Funke, 2017 ). Moreover, some of the decision-making models share the same steps as problem solving (c.f., Donovan, Guss, & Naslund, 2015 ). This explains why these terms are sometimes used interchangeably ( Huitt, 1992 ). Indeed, decision-making is a part of problem solving, which emerges while choosing between alternatives. Yet, values, moral, and ethical issues are more common in decision-making research (e.g., Keeney, 1994 ; Verplanken & Holland, 2002 ; Hall & Davis, 2007 ; Sheehan & Schmidt, 2015 ). Though, research by Shepherd, Patzelt, and Baron (2013) , Baron, Zhao, and Miao (2015) has affirmed that contemporary business decision makers rather often leave aside ethical issues and moral values. Thus, ‘ethical disengagement fallacy’ ( Sternberg, 2017, p.7 ) occurs as people think that ethics is more relevant to others. In the face of such disengagement, ethical issues lose their prominence.

The analysis of the literature revealed a wide field of problem solving research presenting a range of more theoretical insights rather empirical evidence. Despite this, to date, a comprehensive model that reveals how to solve problems emphasizing thinking about values is lacking. This underlines the relevance of the chosen topic, i.e. a challenge for thinking and for the development of capabilities addressing problems through values. To address this gap, the following issues need to be investigated: When, how, and why a problem solver should take into account values during problem solving? What challenges may occur for using such framework of thinking in different fields of education? Aiming this, the authors of the paper substantiated the conceptual framework of problem solving grounded in consistent thinking about values. The substantiation consists of several parts. First, different approaches to solving problems were examined. Second, searching to reveal the possibilities of values integration into problem solving, value-based approaches significant for problem solving were critically analyzed. Third, drawing on the effect of values when solving a problem and their creative potential, the authors of this paper claim that the identification of values and their choice for a solution need to be specified in the process of problem solving. As a synthesis of conclusions coming from the literature review and conceptual extensions regarding values, the authors of the paper created the coherent framework of problem solving through values (so called 4W).

The novelty of the 4W framework is exposed by several contributions. First, the clear design of overall problem solving process with attention on integrated thinking about values is used. Unlike in most models of problem solving, the first stage encompass the identification of a problem, an analysis of a context and the perspectives that influence the whole process, i.e. ‘What?’. The stage ‘What is the basis for a solution?’ focus on values identification and their choice. The stage ‘Ways how?’ encourages to create alternatives considering values. The stage ‘Why?’ represent justification of a chosen alternative according particular issues. Above-mentioned stages including specific steps are not found in any other model of problem solving. Second, even two key stages nurture thinking about values. The specificity of the 4W framework allows expecting its successful practical application. It may help to solve a problem more informed revealing when and how the explication of values helps to reach the desired value-based solution. The particular significance is that the 4W framework can be used to develop capabilities to solve problems through values. The challenges to use the 4W framework in education are discussed.

2. Methodology

To create the 4W framework, the integrative literature review was chosen. According to Snyder (2019) , this review is ‘useful when the purpose of the review is not to cover all articles ever published on the topic but rather to combine perspectives to create new theoretical models’ (p.334). The scope of this review focused on research disclosing problem solving process that paid attention on values. The following databases were used for relevant information search: EBSCO/Hostdatabases (ERIC, Education Source), Emerald, Google Scholar. The first step of this search was conducted using integrated keywords problem solving model , problem solving process, problem solving steps . These keywords were combined with the Boolean operator AND with the second keywords values approach, value-based . The inclusion criteria were used to identify research that: presents theoretical backgrounds and/or empirical evidences; performed within the last 5 years; within an educational context; availability of full text. The sources appropriate for this review was very limited in scope (N = 2).

We implemented the second search only with the same set of the integrated keywords. The inclusion criteria were the same except the date; this criterion was extended up to 10 years. This search presented 85 different sources. After reading the summaries, introductions and conclusions of the sources found, the sources that do not explicitly provide the process/models/steps of problem solving for teaching/learning purposes and eliminates values were excluded. Aiming to see a more accurate picture of the chosen topic, we selected secondary sources from these initial sources.

Several important issues were determined as well. First, most researchers ground their studies on existing problem solving models, however, not based on values. Second, some of them conducted empirical research in order to identify the process of studies participants’ problem solving. Therefore, we included sources without date restrictions trying to identify the principal sources that reveal the process/models/steps of problem solving. Third, decision-making is a part of problem solving process. Accordingly, we performed a search with the additional keywords decision-making AND values approach, value-based decision-making . We used such inclusion criteria: presents theoretical background and/or empirical evidence; no date restriction; within an educational context; availability of full text. These all searches resulted in a total of 16 (9 theoretical and 7 empirical) sources for inclusion. They were the main sources that contributed most fruitfully for the background. We used other sources for the justification the wholeness of the 4W framework. We present the principal results of the conducted literature review in the part ‘The background of the conceptual framework’.

3. The background of the conceptual framework

3.1. different approaches of how to solve a problem.

Researchers from different fields focus on problem solving. As a result, there still seems to be a lack of a conventional definition of problem solving. Regardless of some differences, there is an agreement that problem solving is a cognitive process and one of the meaningful and significant ways of learning ( Funke, 2014 ; Jonassen, 1997 ; Mayer & Wittrock, 2006 ). Differing in approaches to solving a problem, researchers ( Collins, Sibthorp, & Gookin, 2016 ; Jonassen, 1997 ; Litzinger et al., 2010 ; Mayer & Wittrock, 2006 ; O’Loughlin & McFadzean, 1999 ; ect.) present a variety of models that differ in the number of distinct steps. What is similar in these models is that they stress the procedural process of problem solving with the focus on the development of specific skills and competences.

For the sake of this paper, we have focused on those models of problem solving that clarify the process and draw attention to values, specifically, on Huitt (1992) , Basadur, Ellspermann, and Evans (1994) , and Morton (1997) . Integrating the creative approach to problem solving, Newell and Simon (1972) presents six phases: phase 1 - identifying the problem, phase 2 - understanding the problem, phase 3 - posing solutions, phase 4 - choosing solutions, phase 5 - implementing solutions, and phase 6 - final analysis. The weakness of this model is that these phases do not necessarily follow one another, and several can coincide. However, coping with simultaneously occurring phases could be a challenge, especially if these are, for instance, phases five and six. Certainly, it may be necessary to return to the previous phases for further analysis. According to Basadur et al. (1994) , problem solving consists of problem generation, problem formulation, problem solving, and solution implementation stages. Huitt (1992) distinguishes four stages in problem solving: input, processing, output, and review. Both Huitt (1992) and Basadur et al. (1994) four-stage models emphasize a sequential process of problem solving. Thus, problem solving includes four stages that are used in education. For example, problem-based learning employs such stages as introduction of the problem, problem analysis and learning issues, discovery and reporting, solution presentation and evaluation ( Chua, Tan, & Liu, 2016 ). Even PISA 2012 framework for problem solving composes four stages: exploring and understanding, representing and formulating, planning and executing, monitoring and reflecting ( OECD, 2013 ).

Drawing on various approaches to problem solving, it is possible to notice that although each stage is named differently, it is possible to reveal some general steps. These steps reflect the essential idea of problem solving: a search for the solution from the initial state to the desirable state. The identification of a problem and its contextual elements, the generation of alternatives to a problem solution, the evaluation of these alternatives according to specific criteria, the choice of an alternative for a solution, the implementation, and monitoring of the solution are the main proceeding steps in problem solving.

3.2. Value-based approaches relevant for problem solving

Huitt (1992) suggests that important values are among the criteria for the evaluation of alternatives and the effectiveness of a chosen solution. Basadur et al. (1994) point out to visible values in the problem formulation. Morton (1997) underlines that interests, investigation, prevention, and values of all types, which may influence the process, inspire every phase of problem solving. However, the aforementioned authors do not go deeper and do not seek to disclose the significance of values for problem solving.

Decision-making research shows more possibilities for problem solving and values integration. Sheehan and Schmidt (2015) model of ethical decision-making includes moral sensitivity, moral judgment, moral motivation, and moral action where values are presented in the component of moral motivation. Another useful approach concerned with values comes from decision-making in management. It is the concept of Value-Focused Thinking (VFT) proposed by Keeney (1994) . The author argues that the goals often are merely means of achieving results in traditional models of problem solving. Such models frequently do not help to identify logical links between the problem solving goals, values, and alternatives. Thus, according to Keeney (1994) , the decision-making starts with values as they are stated in the goals and objectives of decision-makers. VFT emphasizes the core values of decision-makers that are in a specific context as well as how to find a way to achieve them by using means-ends analysis. The weakness of VFT is its restriction to this means-ends analysis. According to Shin, Jonassen, and McGee (2003) , in searching for a solution, such analysis is weak as the problem solver focuses simply on removing inadequacies between the current state and the goal state. The strengths of this approach underline that values are included in the decision before alternatives are created. Besides, values help to find creative and meaningful alternatives and to assess them. Further, they include the forthcoming consequences of the decision. As VFT emphasizes the significant function of values and clarifies the possibilities of their integration into problem solving, we adapt this approach in the current paper.

3.3. The effect of values when solving a problem

In a broader sense, values provide a direction to a person’s life. Whereas the importance of values is relatively stable over time and across situations, Roccas et al. (2017) argue that values differ in their importance to a person. Verplanken and Holland (2002) investigated the relationship between values and choices or behavior. The research revealed that the activation of a value and the centrality of a value to the self, are the essential elements for value-guided behavior. The activation of values could happen in such cases: when values are the primary focus of attention; if the situation or the information a person is confronted with implies values; when the self is activated. The centrality of a particular value is ‘the degree to which an individual has incorporated this value as part of the self’ ( Verplanken & Holland, 2002, p.436 ). Thus, the perceived importance of values and attention to them determine value-guided behavior.

According to Argandoña (2003) , values can change due to external (changing values in the people around, in society, changes in situations, etc.) and internal (internalization by learning) factors affecting the person. The research by Hall and Davis (2007) indicates that the decision-makers’ applied value profile temporarily changed as they analyzed the issue from multiple perspectives and revealed the existence of a broader set of values. The study by Kirkman (2017) reveal that participants noticed the relevance of moral values to situations they encountered in various contexts.

Values are tightly related to personal integrity and identity and guide an individual’s perception, judgment, and behavior ( Halstead, 1996 ; Schwartz, 1992 ). Sheehan and Schmidt (2015) found that values influenced ethical decision-making of accounting study programme students when they uncovered their own values and grounded in them their individual codes of conduct for future jobs. Hence, the effect of values discloses by observing the problem solver’s decision-making. The latter observations could explain the abundance of ethics-laden research in decision-making rather than in problem solving.

Contemporary researchers emphasize the creative potential of values. Dollinger et al. (2007) , Kasof et al. (2007) , Lebedeva, Schwartz, Plucker, & Van De Vijver, 2019 present to some extent similar findings as they all used Schwartz Value Survey (respectively: Schwartz, 1992 ; ( Schwartz, 1994 ), Schwartz, 2012 ). These studies disclosed that such values as self-direction, stimulation and universalism foster creativity. Kasof et al. (2007) focused their research on identified motivation. Stressing that identified motivation is the only fully autonomous type of external motivation, authors define it as ‘the desire to commence an activity as a means to some end that one greatly values’ (p.106). While identified motivation toward specific values (italic in original) fosters the search for outcomes that express those specific values, this research demonstrated that it could also inhibit creative behavior. Thus, inhibition is necessary, especially in the case where reckless creativity could have painful consequences, for example, when an architect creates a beautiful staircase without a handrail. Consequently, creativity needs to be balanced.

Ultimately, values affect human beings’ lives as they express the motivational goals ( Schwartz, 1992 ). These motivational goals are the comprehensive criteria for a person’s choices when solving problems. Whereas some problem solving models only mention values as possible evaluation criteria, but they do not give any significant suggestions when and how the problem solver could think about the values coming to the understanding that his/her values direct the decision how to solve the problem. The authors of this paper claim that the identification of personal values and their choice for a solution need to be specified in the process of problem solving. This position is clearly reflected in humanistic philosophy and psychology ( Maslow, 2011 ; Rogers, 1995 ) that emphasize personal responsibility for discovering personal values through critical questioning, honest self-esteem, self-discovery, and open-mindedness in the constant pursuit of the truth in the path of individual life. However, fundamental (of humankind) and societal values should be taken into account. McLaughlin (1997) argues that a clear boundary between societal and personal values is difficult to set as they are intertwined due to their existence in complex cultural, social, and political contexts at a particular time. A person is related to time and context when choosing values. As a result, a person assumes existing values as implicit knowledge without as much as a consideration. This is particularly evident in the current consumer society.

Moreover, McLaughlin (1997) stresses that if a particular action should be tolerated and legitimated by society, it does not mean that this action is ultimately morally acceptable in all respects. Education has possibilities to reveal this. One such possibility is to turn to the capability approach ( Sen, 1990 ), which emphasizes what people are effectively able to do and to be. Capability, according to Sen (1990) , reflects a person’s freedom to choose between various ways of living, i.e., the focus is on the development of a person’s capability to choose the life he/she has a reason to value. According to Webster (2017) , ‘in order for people to value certain aspects of life, they need to appreciate the reasons and purposes – the whys – for certain valuing’ (italic in original; p.75). As values reflect and foster these whys, education should supplement the development of capability with attention to values ( Saito, 2003 ). In order to attain this possibility, a person has to be aware of and be able to understand two facets of values. Argandoña (2003) defines them as rationality and virtuality . Rationality refers to values as the ideal of conduct and involves the development of a person’s understanding of what values and why he/she should choose them when solving a problem. Virtuality approaches values as virtues and includes learning to enable a person to live according to his/her values. However, according to McLaughlin (1997) , some people may have specific values that are deep or self-evidently essential. These values are based on fundamental beliefs about the nature and purpose of the human being. Other values can be more or less superficial as they are based on giving priority to one or the other. Thus, virtuality highlights the depth of life harmonized to fundamentally rather than superficially laden values. These approaches inform the rationale for the framework of problem solving through values.

4. The 4W framework of problem solving through values

Similar to the above-presented stages of the problem solving processes, the introduced framework by the authors of this paper revisits them (see Fig. 1 ). The framework is titled 4W as its four stages respond to such questions: Analyzing the Problem: W hat ? → Choice of the value(s): W hat is the background for the solution? → Search for the alternative w ays of the solution: How ? → The rationale for problem solution: W hy is this alternative significant ? The stages of this framework cover seven steps that reveal the logical sequence of problem solving through values.

The 4 W framework: problem solving through values.

Though systematic problem solving models are criticized for being linear and inflexible (e.g., Treffinger & Isaksen, 2005 ), the authors of this paper assume a structural view of the problem solving process due to several reasons. First, the framework enables problem solvers to understand the thorough process of problem solving through values. Second, this framework reveals the depth of each stage and step. Third, problem solving through values encourages tackling problems that have crucial consequences. Only by understanding and mastering the coherence of how problems those require a value-based approach need to be addressed, a problem solver will be able to cope with them in the future. Finally, this framework aims at helping to recognize, to underline personal values, to solve problems through thinking about values, and to take responsibility for choices, even value-based. The feedback supports a direct interrelation between stages. It shapes a dynamic process of problem solving through values.

The first stage of problem solving through values - ‘ The analysis of the problem: What? ’- consists of three steps (see Fig. 1 ). The first step is ‘ Recognizing the problematic situation and naming the problem ’. This step is performed in the following sequence. First, the problem solver should perceive the problematic situation he/she faces in order to understand it. Dostál (2015) argues that the problematic situation has the potential to become the problem necessary to be addressed. Although each problem is limited by its context, not every problematic situation turns into a problem. This is related to the problem solver’s capability and the perception of reality: a person may not ‘see’ the problem if his/her capability to perceive it is not developed ( Dorst, 2006 ; Dostál, 2015 ). Second, after the problem solver recognizes the existence of the problematic situation, the problem solver has to identify the presence or absence of the problem itself, i.e. to name the problem. This is especially important in the case of the ill-structured problems since they cannot be directly visible to the problem solver ( Jonassen, 1997 ). Consequently, this step allows to determine whether the problem solver developed or has acquired the capability to perceive the problematic situation and the problem (naming the problem).

The second step is ‘ Analysing the context of the problem as a reason for its rise ’. At this step, the problem solver aims to analyse the context of the problem. The latter is one of the external issues, and it determines the solution ( Jonassen, 2011 ). However, if more attention is paid to the solution of the problem, it diverts attention from the context ( Fields, 2006 ). The problem solver has to take into account both the conveyed and implied contextual elements in the problematic situation ( Dostál, 2015 ). In other words, the problem solver has to examine it through his/her ‘contextual lenses’ ( Hester & MacG, 2017 , p.208). Thus, during this step the problem solver needs to identify the elements that shape the problem - reasons and circumstances that cause the problem, the factors that can be changed, and stakeholders that are involved in the problematic situation. Whereas the elements of the context mentioned above are within the problematic situation, the problem solver can control many of them. Such control can provide unique ways for a solution.

Although the problem solver tries to predict the undesirable results, some criteria remain underestimated. For that reason, it is necessary to highlight values underlying the various possible goals during the analysis ( Fields, 2006 ). According to Hester and MacG (2017) , values express one of the main features of the context and direct the attention of the problem solver to a given problematic situation. Hence, the problem solver should explore the value-based positions that emerge in the context of the problem.

The analysis of these contextual elements focus not only on a specific problematic situation but also on the problem that has emerged. This requires setting boundaries of attention for an in-depth understanding ( Fields, 2006 ; Hester & MacG, 2017 ). Such understanding influences several actions: (a) the recognition of inappropriate aspects of the problematic situation; (b) the emergence of paths in which identified aspects are expected to change. These actions ensure consistency and safeguard against distractions. Thus, the problem solver can now recognize and identify the factors that influence the problem although they are outside of the problematic situation. However, the problem solver possesses no control over them. With the help of such context analysis, the problem solver constructs a thorough understanding of the problem. Moreover, the problem solver becomes ready to look at the problem from different perspectives.

The third step is ‘ Perspectives emerging in the problem ’. Ims and Zsolnai (2009) argue that problem solving usually contains a ‘problematic search’. Such a search is a pragmatic activity as the problem itself induces it. Thus, the problem solver searches for a superficial solution. As a result, the focus is on control over the problem rather than a deeper understanding of the problem itself. The analysis of the problem, especially including value-based approaches, reveals the necessity to consider the problem from a variety of perspectives. Mitroff (2000) builds on Linstone (1989) ideas and claims that a sound foundation of both naming and solving any problem lays in such perspectives: the technical/scientific, the interpersonal/social, the existential, and the systemic (see Table 1 ).

The main characteristics of four perspectives for problem solving

Whereas all problems have significant aspects of each perspective, disregarding one or another may lead to the wrong way of solving the problem. While analysing all four perspectives is essential, this does not mean that they all are equally important. Therefore, it is necessary to justify why one or another perspective is more relevant and significant in a particular case. Such analysis, according to Linstone (1989) , ‘forces us to distinguish how we are looking from what we are looking at’ (p.312; italic in original). Hence, the problem solver broadens the understanding of various perspectives and develops the capability to see the bigger picture ( Hall & Davis, 2007 ).

The problem solver aims to identify and describe four perspectives that have emerged in the problem during this step. In order to identify perspectives, the problem solver search answers to the following questions. First, regarding the technical/scientific perspective: What technical/scientific reasons are brought out in the problem? How and to what extent do they influence a problem and its context? Second, regarding the interpersonal/social perspective: What is the impact of the problem on stakeholders? How does it influence their attitudes, living conditions, interests, needs? Third, regarding the existential perspective: How does the problem affect human feelings, experiences, perception, and/or discovery of meaning? Fourth, regarding the systemic perspective: What is the effect of the problem on the person → community → society → the world? Based on the analysis of this step, the problem solver obtains a comprehensive picture of the problem. The next stage is to choose the value(s) that will address the problem.

The second stage - ‘ The choice of value(s): What is the background for the solution?’ - includes the fourth and the fifth steps. The fourth step is ‘ The identification of value(s) as a base for the solution ’. During this step, the problem solver should activate his/her value(s) making it (them) explicit. In order to do this, the problem solver proceeds several sub-steps. First, the problem solver reflects taking into account the analysis done in previous steps. He/she raises up questions revealing values that lay in the background of this analysis: What values does this analyzed context allow me to notice? What values do different perspectives of the problem ‘offer’? Such questioning is important as values are deeply hidden ( Verplanken & Holland, 2002 ) and they form a bias, which restricts the development of the capability to see from various points of view ( Hall & Paradice, 2007 ). In the 4W framework, this bias is relatively eliminated due to the analysis of the context and exploration of the perspectives of a problem. As a result, the problem solver discovers distinct value-based positions and gets an opportunity to identify the ‘value uncaptured’ ( Yang, Evans, Vladimirova, & Rana, 2017, p.1796 ) within the problem analyzed. The problem solver observes that some values exist in the context (the second step) and the disclosed perspectives (the third step). Some of the identified values do not affect the current situation as they are not required, or their potential is not exploited. Thus, looking through various value-based lenses, the problem solver can identify and discover a congruence between the opportunities offered by the values in the problem’s context, disclosed perspectives and his/her value(s). Consequently, the problem solver decides what values he/she chooses as a basis for the desired solution. Since problems usually call for a list of values, it is important to find out their order of priority. Thus, the last sub-step requires the problem solver to choose between fundamentally and superficially laden values.

In some cases, the problem solver identifies that a set of values (more than one value) can lead to the desired solution. If a person chooses this multiple value-based position, two options emerge. The first option is concerned with the analysis of each value-based position separately (from the fifth to the seventh step). In the second option, a person has to uncover which of his/her chosen values are fundamentally laden and which are superficially chosen, considering the desired outcome in the current situation. Such clarification could act as a strategy where the path for the desired solution is possible going from superficially chosen value(s) to fundamentally laden one. When a basis for the solution is established, the problem solver formulates the goal for the desired solution.

The fifth step is ‘ The formulation of the goal for the solution ’. Problem solving highlights essential points that reveal the structure of a person’s goals; thus, a goal is the core element of problem solving ( Funke, 2014 ). Meantime, values reflect the motivational content of the goals ( Schwartz, 1992 ). The attention on the chosen value not only activates it, but also motivates the problem solver. The motivation directs the formulation of the goal. In such a way, values explicitly become a basis of the goal for the solution. Thus, this step involves the problem solver in formulating the goal for the solution as the desired outcome.

The way how to take into account value(s) when formulating the goal is the integration of value(s) chosen by the problem solver in the formulation of the goal ( Keeney, 1994 ). For this purpose the conjunction of a context for a solution (it is analyzed during the second step) and a direction of preference (the chosen value reveals it) serves for the formulation of the goal (that represents the desired solution). In other words, a value should be directly included into the formulation of the goal. The goal could lose value, if value is not included into the goal formulation and remains only in the context of the goal. Let’s take the actual example concerning COVID-19 situation. Naturally, many countries governments’ preference represents such value as human life (‘it is important of every individual’s life’). Thus, most likely the particular country government’s goal of solving the COVID situation could be to save the lifes of the country people. The named problem is a complex where the goal of its solution is also complex, although it sounds simple. However, if the goal as desired outcome is formulated without the chosen value, this value remains in the context and its meaning becomes tacit. In the case of above presented example - the goal could be formulated ‘to provide hospitals with the necessary equipment and facilities’. Such goal has the value ‘human’s life’ in the context, but eliminates the complexity of the problem that leads to a partial solution of the problem. Thus, this step from the problem solver requires caution when formulating the goal as the desired outcome. For this reason, maintaining value is very important when formulating the goal’s text. To avoid the loss of values and maintain their proposed direction, is necessary to take into account values again when creating alternatives.

The third stage - ‘ Search for the alternative ways for a solution: How? ’ - encompasses the sixth step, which is called ‘ Creation of value-based alternatives ’. Frequently problem solver invokes a traditional view of problem identification, generation of alternatives, and selection of criteria for evaluating findings. Keeney (1994) ; Ims and Zsolnai (2009) criticize this rational approach as it supports a search for a partial solution where an active search for alternatives is neglected. Moreover, a problematic situation, according to Perkins (2009) , can create the illusion of a fully framed problem with some apparent weighting and some variations of choices. In this case, essential and distinct alternatives to the solution frequently become unnoticeable. Therefore, Perkins (2009) suggest to replace the focus on the attempts to comprehend the problem itself. Thinking through the ‘value lenses’ offers such opportunities. The deep understanding of the problem leads to the search for the alternative ways of a solution.

Thus, the aim of this step is for the problem solver to reveal the possible alternative ways for searching a desired solution. Most people think they know how to create alternatives, but often without delving into the situation. First of all, the problem solver based on the reflection of (but not limited to) the analysis of the context and the perspectives of the problem generates a range of alternatives. Some of these alternatives represent anchored thinking as he/she accepts the assumptions implicit in generated alternatives and with too little focus on values.

The chosen value with the formulated goal indicates direction and encourages a broader and more creative search for a solution. Hence, the problem solver should consider some of the initial alternatives that could best support the achievement of the desired solution. Values are the principles for evaluating the desirability of any alternative or outcome ( Keeney, 1994 ). Thus, planned actions should reveal the desirable mode of conduct. After such consideration, he/she should draw up a plan setting out the actions required to implement each of considered alternatives.

Lastly, after a thorough examination of each considered alternative and a plan of its implementation, the problem solver chooses one of them. If the problem solver does not see an appropriate alternative, he/she develops new alternatives. However, the problem solver may notice (and usually does) that more than one alternative can help him/her to achieve the desired solution. In this case, he/she indicates which alternative is the main one and has to be implemented in the first place, and what other alternatives and in what sequence will contribute in searching for the desired solution.

The fourth stage - ‘ The rationale for the solution: Why ’ - leads to the seventh step: ‘ The justification of the chosen alternative ’. Keeney (1994) emphasizes the compatibility of alternatives in question with the values that guide the action. This underlines the importance of justifying the choices a person makes where the focus is on taking responsibility. According to Zsolnai (2008) , responsibility means a choice, i.e., the perceived responsibility essentially determines its choice. Responsible justification allows for discovering optimal balance when choosing between distinct value-based alternatives. It also refers to the alternative solution that best reflects responsibility in a particular value context, choice, and implementation.

At this stage, the problem solver revisits the chosen solution and revises it. The problem solver justifies his/her choice based on the following questions: Why did you choose this? Why is this alternative significant looking from the technical/scientific, the interpersonal/social, the existential, and the systemic perspectives? Could you take full responsibility for the implementation of this alternative? Why? How clearly do envisaged actions reflect the goal of the desired solution? Whatever interests and for what reasons do this alternative satisfies in principle? What else do you see in the chosen alternative?

As mentioned above, each person gives priority to one aspect or another. The problem solver has to provide solid arguments for the justification of the chosen alternative. The quality of arguments, according to Jonassen (2011) , should be judged based on the quality of the evidence supporting the chosen alternative and opposing arguments that can reject solutions. Besides, the pursuit of value-based goals reflects the interests of the individual or collective interests. Therefore, it becomes critical for the problem solver to justify the level of responsibility he/she takes in assessing the chosen alternative. Such a complex evaluation of the chosen alternative ensures the acceptance of an integral rather than unilateral solution, as ‘recognizing that, in the end, people benefit most when they act for the common good’ ( Sternberg, 2012, p.46 ).

5. Discussion

The constant emphasis on thinking about values as explicit reasoning in the 4W framework (especially from the choice of the value(s) to the rationale for problem solution) reflects the pursuit of virtues. Virtues form the features of the character that are related to the choice ( Argandoña, 2003 ; McLaughlin, 2005 ). Hence, the problem solver develops value-grounded problem solving capability as the virtuality instead of employing rationality for problem solving.

Argandoña (2003) suggests that, in order to make a sound valuation process of any action, extrinsic, transcendent, and intrinsic types of motives need to be considered. They cover the respective types of values. The 4W framework meets these requirements. An extrinsic motive as ‘attaining the anticipated or expected satisfaction’ ( Argandoña, 2003, p.17 ) is reflected in the formulation of the goal of the solution, the creation of alternatives and especially in the justification of the chosen alternative way when the problem solver revisits the external effect of his/her possible action. Transcendent motive as ‘generating certain effects in others’ ( Argandoña, 2003, p.17 ) is revealed within the analysis of the context, perspectives, and creating alternatives. When the learner considers the creation of alternatives and revisits the chosen alternative, he/she pays more attention to these motives. Two types of motives mentioned so far are closely related to an intrinsic motive that emphasizes learning development within the problem solver. These motives confirm that problem solving is, in fact, lifelong learning. In light of these findings, the 4W framework is concerned with some features of value internalization as it is ‘a psychological outcome of conscious mind reasoning about values’ ( Yazdani & Akbarilakeh, 2017, p.1 ).

The 4W framework is complicated enough in terms of learning. One issue is concerned with the educational environments ( Jucevičienė, 2008 ) required to enable the 4W framework. First, the learning paradigm, rather than direct instruction, lies at the foundation of such environments. Second, such educational environments include the following dimensions: (1) educational goal; (2) learning capacity of the learners; (3) educational content relevant to the educational goal: ways and means of communicating educational content as information presented in advance (they may be real, people among them, as well as virtual); (5) methods and means of developing educational content in the process of learners’ performance; (6) physical environment relevant to the educational goal and conditions of its implementation as well as different items in the environment; (7) individuals involved in the implementation of the educational goal.

Another issue is related to exercising this framework in practice. Despite being aware of the 4W framework, a person may still not want to practice problem solving through values, since most of the solutions are going to be complicated, or may even be painful. One idea worth looking into is to reveal the extent to which problem solving through values can become a habit of mind. Profound focus on personal values, context analysis, and highlighting various perspectives can involve changes in the problem solver’s habit of mind. The constant practice of problem solving through values could first become ‘the epistemic habit of mind’ ( Mezirow, 2009, p.93 ), which means a personal way of knowing things and how to use that knowledge. This echoes Kirkman (2017) findings. The developed capability to notice moral values in situations that students encountered changed some students’ habit of mind as ‘for having “ruined” things by making it impossible not to attend to values in such situations!’ (the feedback from one student; Kirkman, 2017, p.12 ). However, this is not enough, as only those problems that require a value-based approach are addressed. Inevitably, the problem solver eventually encounters the challenges of nurturing ‘the moral-ethical habit of mind’ ( Mezirow, 2009, p.93 ). In pursuance to develop such habits of mind, the curriculum should include the necessity of the practising of the 4W framework.

Thinking based on values when solving problems enables the problem solver to engage in thoughtful reflection in contrast to pragmatic and superficial thinking supported by the consumer society. Reflection begins from the first stage of the 4W framework. As personal values are the basis for the desired solution, the problem solver is also involved in self-reflection. The conscious and continuous reflection on himself/herself and the problematic situation reinforce each step of the 4W framework. Moreover, the fourth stage (‘The rationale for the solution: Why’) involves the problem solver in critical reflection as it concerned with justification of ‘the why , the reasons for and the consequences of what we do’ (italic, bold in original; Mezirow, 1990, p.8 ). Exercising the 4W framework in practice could foster reflective practice. Empirical evidence shows that reflective practice directly impacts knowledge, skills and may lead to changes in personal belief systems and world views ( Slade, Burnham, Catalana, & Waters, 2019 ). Thus, with the help of reflective practice it is possible to identify in more detail how and to what extent the 4W framework has been mastered, what knowledge gained, capabilities developed, how point of views changed, and what influence the change process.

Critical issues related to the development of problem solving through values need to be distinguished when considering and examining options for the implementation of the 4W framework at educational institutions. First, the question to what extent can the 4W framework be incorporated into various subjects needs to be answered. Researchers could focus on applying the 4W framework to specific subjects in the humanities and social sciences. The case is with STEM subjects. Though value issues of sustainable development and ecology are of great importance, in reality STEM teaching is often restricted to the development of knowledge and skills, leaving aside the thinking about values. The special task of the researchers is to help practitioners to apply the 4W framework in STEM subjects. Considering this, researchers could employ the concept of ‘dialogic space’ ( Wegerif, 2011, p.3 ) which places particular importance of dialogue in the process of education emphasizing both the voices of teachers and students, and materials. In addition, the dimensions of educational environments could be useful aligning the 4W framework with STEM subjects. As STEM teaching is more based on solving various special tasks and/or integrating problem-based learning, the 4W framework could be a meaningful tool through which content is mastered, skills are developed, knowledge is acquired by solving pre-prepared specific tasks. In this case, the 4W framework could act as a mean addressing values in STEM teaching.

Second is the question of how to enable the process of problem solving through values. In the current paper, the concept of enabling is understood as an integral component of the empowerment. Juceviciene et al. (2010) specify that at least two perspectives can be employed to explain empowerment : a) through the power of legitimacy (according to Freire, 1996 ); and b) through the perspective of conditions for the acquisition of the required knowledge, capabilities, and competence, i.e., enabling. In this paper the 4W framework does not entail the issue of legitimacy. This issue may occur, for example, when a teacher in economics is expected to provide students with subject knowledge only, rather than adding tasks that involve problem solving through values. Yet, the issue of legitimacy is often implicit. A widespread phenomenon exists that teaching is limited to certain periods that do not have enough time for problem solving through values. The issue of legitimacy as an organizational task that supports/or not the implementation of the 4W framework in any curriculum is a question that calls for further discussion.

Third (if not the first), the issue of an educator’s competence to apply such a framework needs to be addressed. In order for a teacher to be a successful enabler, he/she should have the necessary competence. This is related to the specific pedagogical knowledge and skills, which are highly dependent on the peculiarities of the subject being taught. Nowadays actualities are encouraging to pay attention to STEM subjects and their teacher training. For researchers and teacher training institutions, who will be interested in implementing the 4W framework in STEM subjects, it would be useful to draw attention to ‘a material-dialogic approach to pedagogy’ ( Hetherington & Wegerif, 2018, p.27 ). This approach creates the conditions for a deep learning of STEM subjects revealing additional opportunities for problem solving through values in teaching. Highlighting these opportunities is a task for further research.

In contrast to traditional problem solving models, the 4W framework is more concerned with educational purposes. The prescriptive approach to teaching ( Thorne, 1994 ) is applied to the 4W framework. This approach focuses on providing guidelines that enable students to make sound decisions by making explicit value judgements. The limitation is that the 4W framework is focused on thinking but not executing. It does not include the fifth stage, which would focus on the execution of the decision how to solve the problem. This stage may contain some deviation from the predefined process of the solution of the problem.

6. Conclusions

The current paper focuses on revealing the essence of the 4W framework, which is based on enabling the problem solver to draw attention to when, how, and why it is essential to think about values during the problem solving process from the perspective of it’s design. Accordingly, the 4W framework advocates the coherent approach when solving a problem by using a creative potential of values.

The 4W framework allows the problem solver to look through the lens of his/her values twice. The first time, while formulating the problem solving goal as the desired outcome. The second time is when the problem solver looks deeper into his/her values while exploring alternative ways to solve problems. The problem solver is encouraged to reason about, find, accept, reject, compare values, and become responsible for the consequences of the choices grounded on his/her values. Thus, the problem solver could benefit from the 4W framework especially when dealing with issues having crucial consequences.

An educational approach reveals that the 4W framework could enable the development of value-grounded problem solving capability. As problem solving encourages the development of higher-order thinking skills, the consistent inclusion of values enriches them.

The 4W framework requires the educational environments for its enablement. The enablement process of problem solving through values could be based on the perspective of conditions for the acquisition of the required knowledge and capability. Continuous practice of this framework not only encourages reflection, but can also contribute to the creation of the epistemic habit of mind. Applying the 4W framework to specific subjects in the humanities and social sciences might face less challenge than STEM ones. The issue of an educator’s competence to apply such a framework is highly important. The discussed issues present significant challenges for researchers and educators. Caring that the curriculum of different courses should foresee problem solving through values, both practicing and empirical research are necessary.

Declaration of interests

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Both authors have approved the final article.

• Argandoña A. Fostering values in organizations. Journal of Business Ethics. 2003; 45 (1–2):15–28. https://link.springer.com/content/pdf/10.1023/A:1024164210743.pdf [ Google Scholar ]
• Barber S. A truly “Transformative” MBA: Executive education for the fourth industrial revolution. Journal of Pedagogic Development. 2018; 8 (2):44–55. [ Google Scholar ]
• Barnett R. McGraw-Hill Education; UK): 2007. Will to learn: Being a student in an age of uncertainty. [ Google Scholar ]
• Baron R.A., Zhao H., Miao Q. Personal motives, moral disengagement, and unethical decisions by entrepreneurs: Cognitive mechanisms on the “slippery slope” Journal of Business Ethics. 2015; 128 (1):107–118. doi: 10.1007/s10551-014-2078-y. [ CrossRef ] [ Google Scholar ]
• Basadur M., Ellspermann S.J., Evans G.W. A new methodology for formulating ill-structured problems. Omega. 1994; 22 (6):627–645. doi: 10.1016/0305-0483(94)90053-1. [ CrossRef ] [ Google Scholar ]
• Blanco E., Schirmbeck F., Costa C. International Conference on Remote Engineering and Virtual Instrumentation . Springer; Cham: 2018. Vocational Education for the Industrial Revolution; pp. 649–658. [ Google Scholar ]
• Chua B.L., Tan O.S., Liu W.C. Journey into the problem-solving process: Cognitive functions in a PBL environment. Innovations in Education and Teaching International. 2016; 53 (2):191–202. doi: 10.1080/14703297.2014.961502. [ CrossRef ] [ Google Scholar ]
• Collins R.H., Sibthorp J., Gookin J. Developing ill-structured problem-solving skills through wilderness education. Journal of Experiential Education. 2016; 39 (2):179–195. doi: 10.1177/1053825916639611. [ CrossRef ] [ Google Scholar ]
• Csapó B., Funke J., editors. The nature of problem solving: Using research to inspire 21st century learning. OECD Publishing; 2017. The development and assessment of problem solving in 21st-century schools. (Chapter 1). [ CrossRef ] [ Google Scholar ]
• Dollinger S.J., Burke P.A., Gump N.W. Creativity and values. Creativity Research Journal. 2007; 19 (2-3):91–103. doi: 10.1080/10400410701395028. [ CrossRef ] [ Google Scholar ]
• Donovan S.J., Guss C.D., Naslund D. Improving dynamic decision making through training and self-reflection. Judgment and Decision Making. 2015; 10 (4):284–295. http://digitalcommons.unf.edu/apsy_facpub/2 [ Google Scholar ]
• Dorst K. Design problems and design paradoxes. Design Issues. 2006; 22 (3):4–17. doi: 10.1162/desi.2006.22.3.4. [ CrossRef ] [ Google Scholar ]
• Dostál J. Theory of problem solving. Procedia-Social and Behavioral Sciences. 2015; 174 :2798–2805. doi: 10.1016/j.sbspro.2015.01.970. [ CrossRef ] [ Google Scholar ]
• Fields A.M. Ill-structured problems and the reference consultation: The librarian’s role in developing student expertise. Reference Services Review. 2006; 34 (3):405–420. doi: 10.1108/00907320610701554. [ CrossRef ] [ Google Scholar ]
• Freire P. Continuum; New York: 1996. Pedagogy of the oppressed (revised) [ Google Scholar ]
• Funke J. Problem solving: What are the important questions?. Proceedings of the 36th Annual Conference of the Cognitive Science Society; Austin, TX: Cognitive Science Society; 2014. pp. 493–498. [ Google Scholar ]
• Hall D.J., Davis R.A. Engaging multiple perspectives: A value-based decision-making model. Decision Support Systems. 2007; 43 (4):1588–1604. doi: 10.1016/j.dss.2006.03.004. [ CrossRef ] [ Google Scholar ]
• Hall D.J., Paradice D. Investigating value-based decision bias and mediation: do you do as you think? Communications of the ACM. 2007; 50 (4):81–85. [ Google Scholar ]
• Halstead J.M. Values and values education in schools. In: Halstead J.M., Taylor M.J., editors. Values in education and education in values. The Falmer Press; London: 1996. pp. 3–14. [ Google Scholar ]
• Harland T., Pickering N. Routledge; 2010. Values in higher education teaching. [ Google Scholar ]
• Hester P.T., MacG K. Springer; New York: 2017. Systemic decision making: Fundamentals for addressing problems and messes. [ Google Scholar ]
• Hetherington L., Wegerif R. Developing a material-dialogic approach to pedagogy to guide science teacher education. Journal of Education for Teaching. 2018; 44 (1):27–43. doi: 10.1080/02607476.2018.1422611. [ CrossRef ] [ Google Scholar ]
• Huitt W. Problem solving and decision making: Consideration of individual differences using the Myers-Briggs type indicator. Journal of Psychological Type. 1992; 24 (1):33–44. [ Google Scholar ]
• Ims K.J., Zsolnai L. The future international manager. Palgrave Macmillan; London: 2009. Holistic problem solving; pp. 116–129. [ Google Scholar ]
• Jonassen D. Supporting problem solving in PBL. Interdisciplinary Journal of Problem-based Learning. 2011; 5 (2):95–119. doi: 10.7771/1541-5015.1256. [ CrossRef ] [ Google Scholar ]
• Jonassen D.H. Instructional design models for well-structured and III-structured problem-solving learning outcomes. Educational Technology Research and Development. 1997; 45 (1):65–94. doi: 10.1007/BF02299613. [ CrossRef ] [ Google Scholar ]
• Jucevičienė P. Educational and learning environments as a factor for socioeducational empowering of innovation. Socialiniai mokslai. 2008; 1 :58–70. [ Google Scholar ]
• Jucevičienė P., Gudaitytė D., Karenauskaitė V., Lipinskienė D., Stanikūnienė B., Tautkevičienė G. Technologija; Kaunas: 2010. Universiteto edukacinė galia: Atsakas XXI amžiaus iššūkiams [The educational power of university: the response to the challenges of the 21st century] [ Google Scholar ]
• Kasof J., Chen C., Himsel A., Greenberger E. Values and creativity. Creativity Research Journal. 2007; 19 (2–3):105–122. doi: 10.1080/10400410701397164. [ CrossRef ] [ Google Scholar ]
• Keeney R.L. Creativity in decision making with value-focused thinking. MIT Sloan Management Review. 1994; 35 (4):33–41. [ Google Scholar ]
• Kirkman R. Problem-based learning in engineering ethics courses. Interdisciplinary Journal of Problem-based Learning. 2017; 11 (1) doi: 10.7771/1541-5015.1610. [ CrossRef ] [ Google Scholar ]
• Lebedeva N., Schwartz S., Plucker J., Van De Vijver F. Domains of everyday creativity and personal values. Frontiers in Psychology. 2019; 9 :1–16. doi: 10.3389/fpsyg.2018.02681. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Linstone H.A. Multiple perspectives: Concept, applications, and user guidelines. Systems Practice. 1989; 2 (3):307–331. [ Google Scholar ]
• Litzinger T.A., Meter P.V., Firetto C.M., Passmore L.J., Masters C.B., Turns S.R.…Zappe S.E. A cognitive study of problem solving in statics. Journal of Engineering Education. 2010; 99 (4):337–353. [ Google Scholar ]
• Maslow A.H. Vaga; Vilnius: 2011. Būties psichologija. [Psychology of Being] [ Google Scholar ]
• Mayer R., Wittrock M. Problem solving. In: Alexander P., Winne P., editors. Handbook of educational psychology. Psychology Press; New York, NY: 2006. pp. 287–303. [ Google Scholar ]
• McLaughlin T. The educative importance of ethos. British Journal of Educational Studies. 2005; 53 (3):306–325. doi: 10.1111/j.1467-8527.2005.00297.x. [ CrossRef ] [ Google Scholar ]
• McLaughlin T.H. Technologija; Kaunas: 1997. Šiuolaikinė ugdymo filosofija: demokratiškumas, vertybės, įvairovė [Contemporary philosophy of education: democracy, values, diversity] [ Google Scholar ]
• Mezirow J. Jossey-Bass Publishers; San Francisco: 1990. Fostering critical reflection in adulthood; pp. 1–12. https://my.liberatedleaders.com.au/wp-content/uploads/2017/02/How-Critical-Reflection-triggers-Transformative-Learning-Mezirow.pdf [ Google Scholar ]
• Mezirow J. Contemporary theories of learning. Routledge; 2009. An overview on transformative learning; pp. 90–105. (Chapter 6) [ Google Scholar ]
• Mitroff I. Šviesa; Kaunas: 2000. Kaip neklysti šiais beprotiškais laikais: ar mokame spręsti esmines problemas. [How not to get lost in these crazy times: do we know how to solve essential problems] [ Google Scholar ]
• Morton L. Teaching creative problem solving: A paradigmatic approach. Cal. WL Rev. 1997; 34 :375. [ Google Scholar ]
• Nadda P. Need for value based education. International Education and Research Journal. 2017; 3 (2) http://ierj.in/journal/index.php/ierj/article/view/690/659 [ Google Scholar ]
• Newell A., Simon H.A. Prentice-Hall; Englewood Cliffs, NJ: 1972. Human problem solving. [ Google Scholar ]
• OECD . PISA, OECD Publishing; Paris: 2013. PISA 2012 assessment and analytical framework: Mathematics, reading, science, problem solving and financial literacy . https://www.oecd.org/pisa/pisaproducts/PISA%202012%20framework%20e-book_final.pdf [ Google Scholar ]
• OECD . PISA, OECD Publishing; 2018. PISA 2015 results in focus . https://www.oecd.org/pisa/pisa-2015-results-in-focus.pdf [ Google Scholar ]
• O’Loughlin A., McFadzean E. Toward a holistic theory of strategic problem solving. Team Performance Management: An International Journal. 1999; 5 (3):103–120. [ Google Scholar ]
• Perkins D.N. Decision making and its development. In: Callan E., Grotzer T., Kagan J., Nisbett R.E., Perkins D.N., Shulman L.S., editors. Education and a civil society: Teaching evidence-based decision making. American Academy of Arts and Sciences; Cambridge, MA: 2009. pp. 1–28. (Chapter 1) [ Google Scholar ]
• Roccas S., Sagiv L., Navon M. Values and behavior. Cham: Springer; 2017. Methodological issues in studying personal values; pp. 15–50. [ Google Scholar ]
• Rogers C.R. Houghton Mifflin Harcourt; Boston: 1995. On becoming a person: A therapist’s view of psychotherapy. [ Google Scholar ]
• Saito M. Amartya Sen’s capability approach to education: A critical exploration. Journal of Philosophy of Education. 2003; 37 (1):17–33. doi: 10.1111/1467-9752.3701002. [ CrossRef ] [ Google Scholar ]
• Schwartz S.H. Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. In: Zanna M.P., editor. Vol. 25. Academic Press; 1992. pp. 1–65. (Advances in experimental social psychology). [ Google Scholar ]
• Schwartz S.H. Are there universal aspects in the structure and contents of human values? Journal of social issues. 1994; 50 (4):19–45. [ Google Scholar ]
• Schwartz S.H. An overview of the Schwartz theory of basic values. Online Readings in Psychology and Culture. 2012; 2 (1):1–20. doi: 10.9707/2307-0919.1116. [ CrossRef ] [ Google Scholar ]
• Sen A. Development as capability expansion. The community development reader. 1990:41–58. http://www.masterhdfs.org/masterHDFS/wp-content/uploads/2014/05/Sen-development.pdf [ Google Scholar ]
• Sheehan N.T., Schmidt J.A. Preparing accounting students for ethical decision making: Developing individual codes of conduct based on personal values. Journal of Accounting Education. 2015; 33 (3):183–197. doi: 10.1016/j.jaccedu.2015.06.001. [ CrossRef ] [ Google Scholar ]
• Shepherd D.A., Patzelt H., Baron R.A. “I care about nature, but…”: Disengaging values in assessing opportunities that cause harm. The Academy of Management Journal. 2013; 56 (5):1251–1273. doi: 10.5465/amj.2011.0776. [ CrossRef ] [ Google Scholar ]
• Shin N., Jonassen D.H., McGee S. Predictors of well‐structured and ill‐structured problem solving in an astronomy simulation. Journal of Research in Science Teaching. 2003; 40 (1):6–33. doi: 10.1002/tea.10058. [ CrossRef ] [ Google Scholar ]
• Slade M.L., Burnham T.J., Catalana S.M., Waters T. The impact of reflective practice on teacher candidates’ learning. International Journal for the Scholarship of Teaching and Learning. 2019; 13 (2):15. doi: 10.20429/ijsotl.2019.130215. [ CrossRef ] [ Google Scholar ]
• Snyder H. Literature review as a research methodology: An overview and guidelines. Journal of Business Research. 2019; 104 :333–339. doi: 10.1016/j.jbusres.2019.07.039. [ CrossRef ] [ Google Scholar ]
• Sternberg R. Teaching for ethical reasoning. International Journal of Educational Psychology. 2012; 1 (1):35–50. doi: 10.4471/ijep.2012.03. [ CrossRef ] [ Google Scholar ]
• Sternberg R. Speculations on the role of successful intelligence in solving contemporary world problems. Journal of Intelligence. 2017; 6 (1):4. doi: 10.3390/jintelligence6010004. [ PMC free article ] [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Thorne D.M. Environmental ethics in international business education: Descriptive and prescriptive dimensions. Journal of Teaching in International Business. 1994; 5 (1–2):109–122. doi: 10.1300/J066v05n01_08. [ CrossRef ] [ Google Scholar ]
• Treffinger D.J., Isaksen S.G. Creative problem solving: The history, development, and implications for gifted education and talent development. The Gifted Child Quarterly. 2005; 49 (4):342–353. doi: 10.1177/001698620504900407. [ CrossRef ] [ Google Scholar ]
• Verplanken B., Holland R.W. Motivated decision making: Effects of activation and self-centrality of values on choices and behavior. Journal of Personality and Social Psychology. 2002; 82 (3):434–447. doi: 10.1037/0022-3514.82.3.434. [ PubMed ] [ CrossRef ] [ Google Scholar ]
• Webster R.S. Re-enchanting education and spiritual wellbeing. Routledge; 2017. Being spiritually educated; pp. 73–85. [ Google Scholar ]
• Wegerif R. Towards a dialogic theory of how children learn to think. Thinking Skills and Creativity. 2011; 6 (3):179–190. doi: 10.1016/j.tsc.2011.08.002. [ CrossRef ] [ Google Scholar ]
• Yang M., Evans S., Vladimirova D., Rana P. Value uncaptured perspective for sustainable business model innovation. Journal of Cleaner Production. 2017; 140 :1794–1804. doi: 10.1016/j.jclepro.2016.07.102. [ CrossRef ] [ Google Scholar ]
• Yazdani S., Akbarilakeh M. The model of value-based curriculum for medicine and surgery education in Iran. Journal of Minimally Invasive Surgical Sciences. 2017; 6 (3) doi: 10.5812/minsurgery.14053. [ CrossRef ] [ Google Scholar ]
• Zsolnai L. Transaction Publishers; New Brunswick and London: 2008. Responsible decision making. [ Google Scholar ]

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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Academic Problems and Skills

Learning Problem, Learning Skill

Reviewed by Psychology Today Staff

Every school wants every child under its charge to receive the same educational opportunities. However, some students develop academic problems that may cause them to underachieve and, in extreme cases, drop out of school entirely. These problems include confusion about or disinterest in a subject, time management (including procrastination ), lack of attention from teachers, bullying , and inappropriate or violent behavior toward others. While many academic problems can be resolved if caught early and tackled with the help of professionals, some difficulties can persist for years, wreaking havoc on the student’s self-esteem and social relationships.

Conversely, academic skills can be protective influences for students, driving them to achieve their goals . Examples include staying organized, using time wisely, prioritizing effectively, concentrating on tasks, and keeping motivated. With all of the responsibilities that students need to manage at school and at home, these abilities are essential to their success.

• Signs and Causes of Trouble
• School and Mental Health
• Academic Strengths

Teachers and parents are often the first line of defense against academic problems. They should be attuned to any changes in the child’s behavior—such as a drop in grades, a sudden lack of interest in the classroom or at home, skipping classes, or a tendency to act out with teachers or peers or family members. These behaviors may signify an underlying cause that needs to be addressed. It’s important for adults to identify any contributing factors of trouble. A person’s physical health can have a powerful effect on academic performance, and vice versa. If adults see concerning behavior, they should find out if the student is experiencing a lack of sleep, poor nutrition , chronic illness , or a newly developed loss of vision or hearing.

Academic problems can also indicate a possible learning disability, such as  dyslexia  or  ADHD . In such cases, student performance may benefit from school accommodations, such as extra time on tests or additional visual or auditory learning aids for lessons. Parents may also want to consider whether there is a better fit for their child, including  placement in a special education classroom  with fewer students and specially trained staff.

Children and teens are more anxious than ever before. Risk factors like poor sleep and exposure to violence are on the rise. Parents and school personnel  need to know  how to identify the warning signs, deploying intervention immediately to prevent at-risk students from harming themselves and others.

Trouble at school can be both a symptom and a risk factor of mental health conditions. Students today are under extraordinary pressure to excel at academics and extracurriculars, leading to massive stress and worry. When students feel like they cannot measure up to these high and unfair standards, they may develop problems ranging from general anxiety to depression to thoughts of suicide .

Students also have to cope with greater insecurity and a feeling that the world is less safe, given the rise of political instability and violence at schools, particularly mass shootings . This can cause great emotional upset and make it difficult to perform at peak levels.

Ordinary disciplinary measures increase aggression in students. And in turn, this increases everyday violence. Students and teachers are on edge. Plus, anxiety about the possibility of a school shooting is common among students, parents, and school staff, despite the additional safety precautions that many schools are taking.

Students can build up resilience to the stress and anxiety they feel daily in several ways. They can cultivate strong relationships with their peers and teachers and look for opportunities to maximize their strengths as well as engage with the school community. They should also pay attention to their bodies and understand the importance of self-care—getting enough rest, hydrating, eating healthy foods, and exercising. 

Healthy ways to address these fears include making sure students have accurate information, keeping an open line of communication, asking questions rather than making statements, discussing emotions in an age-appropriate manner, and having students describe what would make them feel safer. 

Students who are confident and successful in school tend to share particular academic strengths. While some of these skills may come more easily than others, with time and attention, students can build up their proficiency in most of these areas. Not only do colleges and universities look for these qualities when considering applicants, but they also will serve people well as they transition into the workforce and adult life. Important academic strengths include:

Attention to Detail: Someone with this strength is able to follow instructions while making fewer mistakes. They find it easier to focus on the task at hand and complete an assignment.

Cognitive Flexibility: The most successful students are cognitively flexible and able to adapt to new challenges and changes. A flexible mind moves from task to task, applying what was previously learned to new contexts and problems.

Communication: Humans are social by nature and communicating well, both orally and in writing, is crucial. The ability to clarify goals and expectations furthers cooperation .

Creativity : Innovation and the ability to think more abstractly are in high demand both academically and professionally. Creative thinkers generate great works of art as well as smart solutions to modern problems. Technology evolves daily and creativity is a valuable strength.

Critical Thinking and Problem Solving: Over time, students may forget the details of what they formally studied. However, the ability to think critically allows one to learn efficiently, identify problems, find solutions, evaluate progress, and make plans for the future.

Organization: Students must juggle competing demands, including school assignments, exams, extracurricular activities, family obligations, relationships, and more. Planning ahead, stating clear goals, prioritizing tasks, and managing time can help organizational skills.

Passion: Being thoroughly engaged in a subject can be a powerful motivation for students. A person who is curious and enthusiastic shows a commitment to learning, a positive quality that stands out.

Resilience : Even the best students face academic challenges. After a failure, the resilient learn from their failures and bounce back. They persevere and overcome new obstacles readily.

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