importance of problem solving for students

Why Every Educator Needs to Teach Problem-Solving Skills

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

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

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

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

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

Problem-Solving Skills Help Students…

   develop resilience.

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

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

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

    Set and Achieve Goals

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

  Resolve Conflicts

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

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

    Achieve Success

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

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

Problem-Solving Skills Can Be Measured and Taught

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

What Are Performance-Based Assessments?

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

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

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

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

Preview a Performance-Based Assessment

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

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

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

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

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

Explore CAE’s Problem-Solving Assessments

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

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

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

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

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

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

Ready to Get Started?

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

Teaching problem solving: Let students get ‘stuck’ and ‘unstuck’

Subscribe to the center for universal education bulletin, kate mills and km kate mills literacy interventionist - red bank primary school helyn kim helyn kim former brookings expert @helyn_kim.

October 31, 2017

This is the second in a six-part  blog series  on  teaching 21st century skills , including  problem solving ,  metacognition , critical thinking , and collaboration , in classrooms.

In the real world, students encounter problems that are complex, not well defined, and lack a clear solution and approach. They need to be able to identify and apply different strategies to solve these problems. However, problem solving skills do not necessarily develop naturally; they need to be explicitly taught in a way that can be transferred across multiple settings and contexts.

Here’s what Kate Mills, who taught 4 th grade for 10 years at Knollwood School in New Jersey and is now a Literacy Interventionist at Red Bank Primary School, has to say about creating a classroom culture of problem solvers:

Helping my students grow to be people who will be successful outside of the classroom is equally as important as teaching the curriculum. From the first day of school, I intentionally choose language and activities that help to create a classroom culture of problem solvers. I want to produce students who are able to think about achieving a particular goal and manage their mental processes . This is known as metacognition , and research shows that metacognitive skills help students become better problem solvers.

I begin by “normalizing trouble” in the classroom. Peter H. Johnston teaches the importance of normalizing struggle , of naming it, acknowledging it, and calling it what it is: a sign that we’re growing. The goal is for the students to accept challenge and failure as a chance to grow and do better.

I look for every chance to share problems and highlight how the students— not the teachers— worked through those problems. There is, of course, coaching along the way. For example, a science class that is arguing over whose turn it is to build a vehicle will most likely need a teacher to help them find a way to the balance the work in an equitable way. Afterwards, I make it a point to turn it back to the class and say, “Do you see how you …” By naming what it is they did to solve the problem , students can be more independent and productive as they apply and adapt their thinking when engaging in future complex tasks.

After a few weeks, most of the class understands that the teachers aren’t there to solve problems for the students, but to support them in solving the problems themselves. With that important part of our classroom culture established, we can move to focusing on the strategies that students might need.

Here’s one way I do this in the classroom:

I show the broken escalator video to the class. Since my students are fourth graders, they think it’s hilarious and immediately start exclaiming, “Just get off! Walk!”

When the video is over, I say, “Many of us, probably all of us, are like the man in the video yelling for help when we get stuck. When we get stuck, we stop and immediately say ‘Help!’ instead of embracing the challenge and trying new ways to work through it.” I often introduce this lesson during math class, but it can apply to any area of our lives, and I can refer to the experience and conversation we had during any part of our day.

Research shows that just because students know the strategies does not mean they will engage in the appropriate strategies. Therefore, I try to provide opportunities where students can explicitly practice learning how, when, and why to use which strategies effectively  so that they can become self-directed learners.

For example, I give students a math problem that will make many of them feel “stuck”. I will say, “Your job is to get yourselves stuck—or to allow yourselves to get stuck on this problem—and then work through it, being mindful of how you’re getting yourselves unstuck.” As students work, I check-in to help them name their process: “How did you get yourself unstuck?” or “What was your first step? What are you doing now? What might you try next?” As students talk about their process, I’ll add to a list of strategies that students are using and, if they are struggling, help students name a specific process. For instance, if a student says he wrote the information from the math problem down and points to a chart, I will say: “Oh that’s interesting. You pulled the important information from the problem out and organized it into a chart.” In this way, I am giving him the language to match what he did, so that he now has a strategy he could use in other times of struggle.

The charts grow with us over time and are something that we refer to when students are stuck or struggling. They become a resource for students and a way for them to talk about their process when they are reflecting on and monitoring what did or did not work.

For me, as a teacher, it is important that I create a classroom environment in which students are problem solvers. This helps tie struggles to strategies so that the students will not only see value in working harder but in working smarter by trying new and different strategies and revising their process. In doing so, they will more successful the next time around.

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Center for Teaching

Teaching problem solving.

Print Version

Tips and Techniques

Expert vs. novice problem solvers, communicate.

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

Encourage Independence

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

Be sensitive

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

Encourage Thoroughness and Patience

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

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

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

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4 Strategies to Build Your Students’ Problem Solving Skills

Every teacher understands the importance of fostering problem-solving skills in their students. These skills not only help students navigate academic challenges, but they also translate into valuable tools for life beyond the classroom. In this article, we’ll delve into the reasons why it’s crucial to develop these skills and provide practical strategies you can implement in your classroom right away.

Why is Developing Problem Solving Skills Important?

Strategies to develop problem solving skills, real-world example, concluding thoughts.

Problem-solving skills are a crucial part of a well-rounded education. They encourage critical thinking, enhance creativity and flexibility, and equip students with the resilience needed to tackle obstacles head-on.

• Real-World Application:  Problem-solving skills aren’t confined to solving math problems or decoding a science experiment. They are applicable in everyday life situations, from resolving conflicts to making important decisions.
• Enhances Creativity and Critical Thinking:  Problem-solving activities often require students to think outside the box and use their critical thinking abilities. This stimulates creativity and fosters innovative thought.
• Boosts Confidence:  As students improve their problem-solving abilities, they gain confidence in their skills. This confidence can positively influence their academic performance and personal life.

There are numerous ways to incorporate problem-solving skill development into your classroom. Here are a few effective strategies:

• Project-Based Learning:  Projects that require planning, execution, and evaluation naturally involve problem-solving. For example, a project where students need to build a model bridge within a budget encourages them to solve logistical and financial problems.
• Group Work :  Group work allows students to face and solve problems together. It encourages communication, cooperation, and collective problem-solving. For example, a group assignment on preparing a presentation on an environmental issue can encourage problem-solving related to information gathering, presentation design, and time management.
• Encourage Questions :  Encourage students to ask and answer their own questions. This promotes independent thinking and problem solving. For example, instead of giving the answer to a complicated math problem, guide them towards the solution by prompting them with questions.
• Role-play Scenarios:  Role-play scenarios can help students develop problem-solving skills by putting them in hypothetical situations and asking them to come up with solutions. For example, a role-play scenario where a student has to navigate a disagreement between friends can help them develop conflict resolution skills.

As a school leader, I’ve seen the power of problem-solving skills firsthand. I remember a group of students who were working on a community garden project. They faced numerous challenges, like budget constraints and unpredictable weather. Despite the hurdles, they didn’t give up. Instead, they came up with creative solutions, such as fundraising to cover costs and building a small greenhouse for year-round gardening. This project not only enhanced their problem-solving skills but also their resilience and team collaboration.

Developing problem-solving skills in students is a crucial aspect of education that extends beyond academic success. By incorporating problem-solving activities into your teaching, you’re equipping your students with a tool that will serve them in all facets of life. Remember, the best learning happens when students are actively engaged , so make problem-solving a fun and integral part of your classroom culture.

1. What are problem-solving skills? Problem-solving skills are abilities that help individuals define problems, analyze potential solutions, and implement effective strategies to solve problems.

2. Why are problem-solving skills important for students? Problem-solving skills are important as they foster creativity, critical thinking, and resilience. They are applicable in real-world situations and can boost student confidence.

3. What are some strategies to develop problem-solving skills in students? Strategies can include project-based learning, group work, encouraging questions, and role-play scenarios.

4. How can I make problem-solving activities engaging for students? Making problem-solving part of a larger project or group work can make it more engaging. Also, try to relate problems to real-world situations that students find relevant.

5. How can I assess my students’ problem-solving skills? You can assess problem-solving skills through direct observation, group project participation, and individual assignments that require problem-solving.

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• Problem Solving in STEM

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

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

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

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

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

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

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

What are some benefits of having students work in groups?

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

What are some strategies for helping students to form groups?  

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

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

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

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

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

What happens if a student gives a wrong answer?

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

How can you make your classroom inclusive?

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

A few final notes…

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

For more information...

Tipsheet: Problem Solving in STEM Sections

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

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Problem-Solving

Jabberwocky

Problem-solving is the ability to identify and solve problems by applying appropriate skills systematically.

Problem-solving is a process—an ongoing activity in which we take what we know to discover what we don't know. It involves overcoming obstacles by generating hypo-theses, testing those predictions, and arriving at satisfactory solutions.

Problem-solving involves three basic functions:

Seeking information

Generating new knowledge

Making decisions

Problem-solving is, and should be, a very real part of the curriculum. It presupposes that students can take on some of the responsibility for their own learning and can take personal action to solve problems, resolve conflicts, discuss alternatives, and focus on thinking as a vital element of the curriculum. It provides students with opportunities to use their newly acquired knowledge in meaningful, real-life activities and assists them in working at higher levels of thinking (see Levels of Questions ).

Here is a five-stage model that most students can easily memorize and put into action and which has direct applications to many areas of the curriculum as well as everyday life:

Expert Opinion

Here are some techniques that will help students understand the nature of a problem and the conditions that surround it:

• List all related relevant facts.
• Make a list of all the given information.
• Restate the problem in their own words.
• List the conditions that surround a problem.
• Describe related known problems.

It's Elementary

For younger students, illustrations are helpful in organizing data, manipulating information, and outlining the limits of a problem and its possible solution(s). Students can use drawings to help them look at a problem from many different perspectives.

Understand the problem. It's important that students understand the nature of a problem and its related goals. Encourage students to frame a problem in their own words.

Describe any barriers. Students need to be aware of any barriers or constraints that may be preventing them from achieving their goal. In short, what is creating the problem? Encouraging students to verbalize these impediments is always an important step.

Identify various solutions. After the nature and parameters of a problem are understood, students will need to select one or more appropriate strategies to help resolve the problem. Students need to understand that they have many strategies available to them and that no single strategy will work for all problems. Here are some problem-solving possibilities:

Create visual images. Many problem-solvers find it useful to create “mind pictures” of a problem and its potential solutions prior to working on the problem. Mental imaging allows the problem-solvers to map out many dimensions of a problem and “see” it clearly.

Guesstimate. Give students opportunities to engage in some trial-and-error approaches to problem-solving. It should be understood, however, that this is not a singular approach to problem-solving but rather an attempt to gather some preliminary data.

Create a table. A table is an orderly arrangement of data. When students have opportunities to design and create tables of information, they begin to understand that they can group and organize most data relative to a problem.

Use manipulatives. By moving objects around on a table or desk, students can develop patterns and organize elements of a problem into recognizable and visually satisfying components.

Work backward. It's frequently helpful for students to take the data presented at the end of a problem and use a series of computations to arrive at the data presented at the beginning of the problem.

Look for a pattern. Looking for patterns is an important problem-solving strategy because many problems are similar and fall into predictable patterns. A pattern, by definition, is a regular, systematic repetition and may be numerical, visual, or behavioral.

Create a systematic list. Recording information in list form is a process used quite frequently to map out a plan of attack for defining and solving problems. Encourage students to record their ideas in lists to determine regularities, patterns, or similarities between problem elements.

Try out a solution. When working through a strategy or combination of strategies, it will be important for students to …

Keep accurate and up-to-date records of their thoughts, proceedings, and procedures. Recording the data collected, the predictions made, and the strategies used is an important part of the problem solving process.

Try to work through a selected strategy or combination of strategies until it becomes evident that it's not working, it needs to be modified, or it is yielding inappropriate data. As students become more proficient problem-solvers, they should feel comfortable rejecting potential strategies at any time during their quest for solutions.

Monitor with great care the steps undertaken as part of a solution. Although it might be a natural tendency for students to “rush” through a strategy to arrive at a quick answer, encourage them to carefully assess and monitor their progress.

Feel comfortable putting a problem aside for a period of time and tackling it at a later time. For example, scientists rarely come up with a solution the first time they approach a problem. Students should also feel comfortable letting a problem rest for a while and returning to it later.

Evaluate the results. It's vitally important that students have multiple opportunities to assess their own problem-solving skills and the solutions they generate from using those skills. Frequently, students are overly dependent upon teachers to evaluate their performance in the classroom. The process of self-assessment is not easy, however. It involves risk-taking, self-assurance, and a certain level of independence. But it can be effectively promoted by asking students questions such as “How do you feel about your progress so far?” “Are you satisfied with the results you obtained?” and “Why do you believe this is an appropriate response to the problem?”

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Essential Problem Solving Skills For College Life

You’ve found yourself in a pickle and you’re endlessly looking for a solution but somehow things just keep getting messier. It’s okay, we’ve all been there. Just take a step back, and take control of the situation. Finding easy problem-solving ideas for all problems, big or small, isn’t a difficult task with the right mindset. Whatever your strategy is, do what works for you. The question remains, how are you supposed to find those problem-solving skills that work for you?

Read on to discover some problem-solving techniques to try out, who knows, maybe one or more of them will work for you.

  try to prevent a problem in the first place.

This first one goes without saying. What better way is there to solve a problem than doing everything in your power to prevent a problem from occurring in the first place?  While sometimes this cannot be accomplished because some things happen beyond anyone’s control, there are times when certain problems or situations can be prevented. Some ways to try to prevent a problem are by planning ahead and staying organized . Students can stay organized by buying, and using a planner or a bulleting journal to write things down. If students prefer to not write things, they could use their phones to set reminders and to take notes. “Try to avoid a problem arising in the first place. Plan things out and just execute your plan,” Temple University junior Kennedy Catrambone said. If you try to plan things out to the best of your ability, in an organized manner, you might be able to prevent a problem from arising.

Weigh the Pros and Cons

Weighing the pros and cons of every option is a great way to problem solve. Yes, every solution has positive and negative aspects surrounding. In some cases, the pros, outweigh the cons and some choices prove better than others. Some ways to weigh the pros and cons of a situation include asking other people for advice, conducting background research and writing a list. Personally, I know I had to weigh the pros and cons when it came to picking which college to attend. I applied to around twenty colleges and  conducted research. I then wrote lists containing the pros and cons of each school I was considering. “The first step is not to panic. Then, keep a calm mind and assess the situation. Next, I look for pros and cons to make the best decision based on that,” SUNY Bighamton University senior Max Kline said.  College students can weigh pros and cons by asking what the good, and the bad things are. After all, we all always want the good to outweigh the bad. So why not weigh the pros and cons?

Use Process of Elimination

Another great problem solving skill is using process of elimination to eliminate possible solutions to a problem that might not make sense.  Like on an exam where choices might be unfitting for the question, there are answers, or solutions to problems that might not be applicable to the given situation. I know that I have used process of elimination many other times in my life such as when I had to decide what major to stick with in college. I picked out the few majors I felt could be a good fit for me, and used process of elimination to determine which ones weren’t until I ultimately made my choice. “Usually, I think about my options and then eliminate things that I don’t want to do or I feel like aren’t important,” said first year graduate school student at A.T Stillwell University, Marissa Credle. Eliminating solutions based on criteria like personal feelings is a great way to use process of elimination as a problem solving tool. In the end, process of elimination is a great way to approach problems.

Problem Solve Piece by Piece

Sometimes, there will be problems or situations that are more complex, and might be more difficult to find solutions for, or to solve than others. The best way to handle these kind of scenarios is to break it down into different sections, or pieces and try to solve the giant problem through steps. Personally, when I have a complex issue that I have to deal with concerning other people, such as arguments between friends, I try to solve them piece by piece to make sure every party involved is satisfied.  “I like to break down the problem, separate it into pieces and take care of it one piece at a time,” SUNY New Paltz sophomore Cody Bostino said. Though this method of problem solving might seem time consuming, it is one of the most effective ways of making sure the entirety of an issue is resolved. When looking at a problem piece by piece, you are more likely to find the best solutions – so channel your inner Nancy Drew and take it step by step.

Be Dependable

Dependability is vital to solving problems, especially in a college oriented environment. Those who are dependable typically solve problems and come through with long term solutions benefiting themselves, and all those involved in the end. For example, making sure you are present when need be, effectively paying attention to details and being a team player are ways one can be dependable.These aspects can definitely be worked on and someone can gain dependability. Someone who is dependable always has time to be there for you and if something goes wrong, they will have your back. Think about it this way: would you want a best friend who isn’t dependable? This also applies to bosses, co-workers, classmates etc. Having people who are dependable around you, and being dependable yourself definitely benefits everyone in the realm of problem solving.

Be Open-Minded and Accepting

Open Mindedness and being accepting are two key aspects of coming to terms with whatever life throws at you. When it comes to having an open mind, and accepting others, it is important to make sure you stay at ease and go with the flow. For example, if you are stressed out about an exam, going into it and being able to accept the fact that your life will go on, regardless of the number grade you receive, helps the situation. If you go into the exam feeling anxious and stressed, you are less likely to do well on it. In general, when you are feeling more relaxed rather than stressed, you are more likely to succeed. Looking at all of your problems differently, and embracing an accepting, open mindset will greatly benefit the problem solving process.

Communication is Key

When it comes to problem solving, most problems that come about involve multiple people. One of the best ways to make sure all of the people in a given situation are on the same page is to create an environment that thrives off of communicating . Talking face to face, texting, emailing, talking on the phone or any other form of communication where ideas are shared are acceptable in assuring that nothing is left unsaid. All of these outlets of communication are applicable for situations including a fight with a roommate, a boyfriend, or any other sort of girl drama or boy problems. Like the saying goes, communication is key, and it can prevent and solve any given problem.

Utilize Your School’s Resources

While you’re at college, you will surely come face to face with different problems and situations. However, lots of college students tend to forget that their college has resources for them to utilize. When it comes to academics, college students can contact their academic advisers or professors. When it involves a physical health related issue, students can visit their campus health clinic. Finally, if students are struggling with mental health, they can speak to specialists working at their respective colleges. If you have trouble with something, remember that colleges have resources for you to use, so use them. “Just get things done,” Catrambone said. Whatever the problem is, your college surely has a resource that can help you.

Look to Others for Help

When it comes down to it, you know that your loved ones can always be there for you. Your family and friends provide different insights and perspectives that you probably wouldn’t get if you didn’t ask them. Remember that asking for help is okay , it helps you in the long run. “If I had a problem I would most likely get advice from my parents, or friends,” rising SUNY New Paltz junior Katherine Parente said. When it comes down to it, more insight only helps you get closer to, if not find a solution to your problem. So, why not look to others for help?

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What Are Problem-Solving Skills? Definition and Examples

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Forage puts students first. Our blog articles are written independently by our editorial team. They have not been paid for or sponsored by our partners. See our full  editorial guidelines .

Why do employers hire employees? To help them solve problems. Whether you’re a financial analyst deciding where to invest your firm’s money, or a marketer trying to figure out which channel to direct your efforts, companies hire people to help them find solutions. Problem-solving is an essential and marketable soft skill in the workplace. 

So, how can you improve your problem-solving and show employers you have this valuable skill? In this guide, we’ll cover:

Problem-Solving Skills Definition

Why are problem-solving skills important, problem-solving skills examples, how to include problem-solving skills in a job application, how to improve problem-solving skills, problem-solving: the bottom line.

Problem-solving skills are the ability to identify problems, brainstorm and analyze answers, and implement the best solutions. An employee with good problem-solving skills is both a self-starter and a collaborative teammate; they are proactive in understanding the root of a problem and work with others to consider a wide range of solutions before deciding how to move forward. 

Examples of using problem-solving skills in the workplace include:

• Researching patterns to understand why revenue decreased last quarter
• Experimenting with a new marketing channel to increase website sign-ups
• Brainstorming content types to share with potential customers
• Testing calls to action to see which ones drive the most product sales
• Implementing a new workflow to automate a team process and increase productivity

Problem-solving skills are the most sought-after soft skill of 2022. In fact, 86% of employers look for problem-solving skills on student resumes, according to the National Association of Colleges and Employers Job Outlook 2022 survey . 

It’s unsurprising why employers are looking for this skill: companies will always need people to help them find solutions to their problems. Someone proactive and successful at problem-solving is valuable to any team.

“Employers are looking for employees who can make decisions independently, especially with the prevalence of remote/hybrid work and the need to communicate asynchronously,” Eric Mochnacz, senior HR consultant at Red Clover, says. “Employers want to see individuals who can make well-informed decisions that mitigate risk, and they can do so without suffering from analysis paralysis.”

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Problem-solving includes three main parts: identifying the problem, analyzing possible solutions, and deciding on the best course of action.

>>MORE: Discover the right career for you based on your skills with a career aptitude test .

Research is the first step of problem-solving because it helps you understand the context of a problem. Researching a problem enables you to learn why the problem is happening. For example, is revenue down because of a new sales tactic? Or because of seasonality? Is there a problem with who the sales team is reaching out to? 

Research broadens your scope to all possible reasons why the problem could be happening. Then once you figure it out, it helps you narrow your scope to start solving it. 

Analysis is the next step of problem-solving. Now that you’ve identified the problem, analytical skills help you look at what potential solutions there might be.

“The goal of analysis isn’t to solve a problem, actually — it’s to better understand it because that’s where the real solution will be found,” Gretchen Skalka, owner of Career Insights Consulting, says. “Looking at a problem through the lens of impartiality is the only way to get a true understanding of it from all angles.”

Decision-Making

Once you’ve figured out where the problem is coming from and what solutions are, it’s time to decide on the best way to go forth. Decision-making skills help you determine what resources are available, what a feasible action plan entails, and what solution is likely to lead to success.

On a Resume

Employers looking for problem-solving skills might include the word “problem-solving” or other synonyms like “ critical thinking ” or “analytical skills” in the job description.

“I would add ‘buzzwords’ you can find from the job descriptions or LinkedIn endorsements section to filter into your resume to comply with the ATS,” Matthew Warzel, CPRW resume writer, advises. Warzel recommends including these skills on your resume but warns to “leave the soft skills as adjectives in the summary section. That is the only place soft skills should be mentioned.”

On the other hand, you can list hard skills separately in a skills section on your resume .

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In a Cover Letter or an Interview

Explaining your problem-solving skills in an interview can seem daunting. You’re required to expand on your process — how you identified a problem, analyzed potential solutions, and made a choice. As long as you can explain your approach, it’s okay if that solution didn’t come from a professional work experience.

“Young professionals shortchange themselves by thinking only paid-for solutions matter to employers,” Skalka says. “People at the genesis of their careers don’t have a wealth of professional experience to pull from, but they do have relevant experience to share.”

Aaron Case, career counselor and CPRW at Resume Genius, agrees and encourages early professionals to share this skill. “If you don’t have any relevant work experience yet, you can still highlight your problem-solving skills in your cover letter,” he says. “Just showcase examples of problems you solved while completing your degree, working at internships, or volunteering. You can even pull examples from completely unrelated part-time jobs, as long as you make it clear how your problem-solving ability transfers to your new line of work.”

Learn How to Identify Problems

Problem-solving doesn’t just require finding solutions to problems that are already there. It’s also about being proactive when something isn’t working as you hoped it would. Practice questioning and getting curious about processes and activities in your everyday life. What could you improve? What would you do if you had more resources for this process? If you had fewer? Challenge yourself to challenge the world around you.

Think Digitally

“Employers in the modern workplace value digital problem-solving skills, like being able to find a technology solution to a traditional issue,” Case says. “For example, when I first started working as a marketing writer, my department didn’t have the budget to hire a professional voice actor for marketing video voiceovers. But I found a perfect solution to the problem with an AI voiceover service that cost a fraction of the price of an actor.”

Being comfortable with new technology — even ones you haven’t used before — is a valuable skill in an increasingly hybrid and remote world. Don’t be afraid to research new and innovative technologies to help automate processes or find a more efficient technological solution.

Collaborate

Problem-solving isn’t done in a silo, and it shouldn’t be. Use your collaboration skills to gather multiple perspectives, help eliminate bias, and listen to alternative solutions. Ask others where they think the problem is coming from and what solutions would help them with your workflow. From there, try to compromise on a solution that can benefit everyone.

If we’ve learned anything from the past few years, it’s that the world of work is constantly changing — which means it’s crucial to know how to adapt . Be comfortable narrowing down a solution, then changing your direction when a colleague provides a new piece of information. Challenge yourself to get out of your comfort zone, whether with your personal routine or trying a new system at work.

Put Yourself in the Middle of Tough Moments

Just like adapting requires you to challenge your routine and tradition, good problem-solving requires you to put yourself in challenging situations — especially ones where you don’t have relevant experience or expertise to find a solution. Because you won’t know how to tackle the problem, you’ll learn new problem-solving skills and how to navigate new challenges. Ask your manager or a peer if you can help them work on a complicated problem, and be proactive about asking them questions along the way.

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What careers are right for you based on your skills? Take this quiz to find out. It’s completely free — you’ll just need to sign up to get your results!

Step 1 of 3

Companies always need people to help them find solutions — especially proactive employees who have practical analytical skills and can collaborate to decide the best way to move forward. Whether or not you have experience solving problems in a professional workplace, illustrate your problem-solving skills by describing your research, analysis, and decision-making process — and make it clear that you’re the solution to the employer’s current problems. 

Looking to learn more workplace professional skills? Check out Two Sigma’s Professional Skills Development Virtual Experience Program .

Image Credit: Christina Morillo / Pexels 

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MSU Extension

Problem-solving skills are an important factor in academic success.

Elizabeth Gutierrez, Michigan State University Extension - May 11, 2012

Updated from an original article written by [email protected]..

Parents and caregivers can ensure their children's success by teaching and modeling effective problem-solving at home.

Helping your child learn how to problem solve is a critical skill for school readiness. Parents and caregivers are a child’s first and most important teacher; therefore, modeling good problem solving skills is very important. Children learn by watching parents and caregivers handle different situations and solve problems. If a parent handles problems by yelling, throwing things, hitting, grabbing or using other unacceptable strategies, a child will learn to do the same thing.

Often, adults will prevent their children from seeing all conflicts or disagreements. Remember, it is important for children to see adults negotiate differences, compromise and resolve conflicts. Learning to negotiate differences in a constructive way and allowing children to see how this is done is very effective and important. If parent and caregivers handle these situations privately, there is no example for the child/children to learn from.

Children can learn how to be assertive verbally as a result of seeing and listening to how adults resolve conflict. Another simple way a child can learn how to be assertive verbally is by role-playing with puppets and through pretend play with an adult. When using these techniques, it is important to help your child think of constructive ways to respond to different situations. By using puppets and role-play, your child can also learn about how others may feel in specific situations. When using these techniques, it is important not to criticize or label the child for past misbehavior.

There are some basic steps to problem solving from Incredible Years :

• Identify the problem.
• List the possible solutions or courses of action.
• Weigh the possible solutions.
• Choose a solution to try.
• Put the solution into practice.
• Evaluate the solution.

Using effective problem solving techniques will help children avoid conflict with others in a school setting and in their everyday lives. It will also strengthen children’s beginning empathy skills and help them learn more positive attributions about another person’s intentions. Effective problem solving skills is essential for academic and social success.

For more articles on child development, academic success, parenting and life skill development, please visit the Michigan State University Extension website.

This article was published by Michigan State University Extension . For more information, visit https://extension.msu.edu . To have a digest of information delivered straight to your email inbox, visit https://extension.msu.edu/newsletters . To contact an expert in your area, visit https://extension.msu.edu/experts , or call 888-MSUE4MI (888-678-3464).

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Don’t Just Tell Students to Solve Problems. Teach Them How.

The positive impact of an innovative uc san diego problem-solving educational curriculum continues to grow.

• Daniel Kane - [email protected]

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Problem solving is a critical skill for technical education and technical careers of all types. But what are best practices for teaching problem solving to high school and college students? 

The University of California San Diego Jacobs School of Engineering is on the forefront of efforts to improve how problem solving is taught. This UC San Diego approach puts hands-on problem-identification and problem-solving techniques front and center. Over 1,500 students across the San Diego region have already benefited over the last three years from this program. In the 2023-2024 academic year, approximately 1,000 upper-level high school students will be taking the problem solving course in four different school districts in the San Diego region. Based on the positive results with college students, as well as high school juniors and seniors in the San Diego region, the project is getting attention from educators across the state of California, and around the nation and the world.

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In Summer 2023, th e 27 community college students who took the unique problem-solving course developed at the UC San Diego Jacobs School of Engineering thrived, according to Alex Phan PhD, the Executive Director of Student Success at the UC San Diego Jacobs School of Engineering. Phan oversees the project. 

Over the course of three weeks, these students from Southwestern College and San Diego City College poured their enthusiasm into problem solving through hands-on team engineering challenges. The students brimmed with positive energy as they worked together. 

What was noticeably absent from this laboratory classroom: frustration.

“In school, we often tell students to brainstorm, but they don’t often know where to start. This curriculum gives students direct strategies for brainstorming, for identifying problems, for solving problems,” sai d Jennifer Ogo, a teacher from Kearny High School who taught the problem-solving course in summer 2023 at UC San Diego. Ogo was part of group of educators who took the course themselves last summer.

The curriculum has been created, refined and administered over the last three years through a collaboration between the UC San Diego Jacobs School of Engineering and the UC San Diego Division of Extended Studies. The project kicked off in 2020 with a generous gift from a local philanthropist.

Not getting stuck

One of the overarching goals of this project is to teach both problem-identification and problem-solving skills that help students avoid getting stuck during the learning process. Stuck feelings lead to frustration – and when it’s a Science, Technology, Engineering and Math (STEM) project, that frustration can lead students to feel they don’t belong in a STEM major or a STEM career. Instead, the UC San Diego curriculum is designed to give students the tools that lead to reactions like “this class is hard, but I know I can do this!” –  as Ogo, a celebrated high school biomedical sciences and technology teacher, put it. 

Three years into the curriculum development effort, the light-hearted energy of the students combined with their intense focus points to success. On the last day of the class, Mourad Mjahed PhD, Director of the MESA Program at Southwestern College’s School of Mathematics, Science and Engineering came to UC San Diego to see the final project presentations made by his 22 MESA students.

“Industry is looking for students who have learned from their failures and who have worked outside of their comfort zones,” said Mjahed. The UC San Diego problem-solving curriculum, Mjahed noted, is an opportunity for students to build the skills and the confidence to learn from their failures and to work outside their comfort zone. “And from there, they see pathways to real careers,” he said. 

What does it mean to explicitly teach problem solving? 

This approach to teaching problem solving includes a significant focus on learning to identify the problem that actually needs to be solved, in order to avoid solving the wrong problem. The curriculum is organized so that each day is a complete experience. It begins with the teacher introducing the problem-identification or problem-solving strategy of the day. The teacher then presents case studies of that particular strategy in action. Next, the students get introduced to the day’s challenge project. Working in teams, the students compete to win the challenge while integrating the day’s technique. Finally, the class reconvenes to reflect. They discuss what worked and didn't work with their designs as well as how they could have used the day’s problem-identification or problem-solving technique more effectively. 

The challenges are designed to be engaging – and over three years, they have been refined to be even more engaging. But the student engagement is about much more than being entertained. Many of the students recognize early on that the problem-identification and problem-solving skills they are learning can be applied not just in the classroom, but in other classes and in life in general. 

Gabriel from Southwestern College is one of the students who saw benefits outside the classroom almost immediately. In addition to taking the UC San Diego problem-solving course, Gabriel was concurrently enrolled in an online computer science programming class. He said he immediately started applying the UC San Diego problem-identification and troubleshooting strategies to his coding assignments. 

Gabriel noted that he was given a coding-specific troubleshooting strategy in the computer science course, but the more general problem-identification strategies from the UC San Diego class had been extremely helpful. It’s critical to “find the right problem so you can get the right solution. The strategies here,” he said, “they work everywhere.”

Phan echoed this sentiment. “We believe this curriculum can prepare students for the technical workforce. It can prepare students to be impactful for any career path.”

The goal is to be able to offer the course in community colleges for course credit that transfers to the UC, and to possibly offer a version of the course to incoming students at UC San Diego. 

As the team continues to work towards integrating the curriculum in both standardized high school courses such as physics, and incorporating the content as a part of the general education curriculum at UC San Diego, the project is expected to impact thousands more students across San Diego annually. 

Portrait of the Problem-Solving Curriculum

On a sunny Wednesday in July 2023, an experiential-learning classroom was full of San Diego community college students. They were about half-way through the three-week problem-solving course at UC San Diego, held in the campus’ EnVision Arts and Engineering Maker Studio. On this day, the students were challenged to build a contraption that would propel at least six ping pong balls along a kite string spanning the laboratory. The only propulsive force they could rely on was the air shooting out of a party balloon.

A team of three students from Southwestern College – Valeria, Melissa and Alondra – took an early lead in the classroom competition. They were the first to use a plastic bag instead of disposable cups to hold the ping pong balls. Using a bag, their design got more than half-way to the finish line – better than any other team at the time – but there was more work to do. 

As the trio considered what design changes to make next, they returned to the problem-solving theme of the day: unintended consequences. Earlier in the day, all the students had been challenged to consider unintended consequences and ask questions like: When you design to reduce friction, what happens? Do new problems emerge? Did other things improve that you hadn’t anticipated? 

Other groups soon followed Valeria, Melissa and Alondra’s lead and began iterating on their own plastic-bag solutions to the day’s challenge. New unintended consequences popped up everywhere. Switching from cups to a bag, for example, reduced friction but sometimes increased wind drag. 

Over the course of several iterations, Valeria, Melissa and Alondra made their bag smaller, blew their balloon up bigger, and switched to a different kind of tape to get a better connection with the plastic straw that slid along the kite string, carrying the ping pong balls. 

One of the groups on the other side of the room watched the emergence of the plastic-bag solution with great interest. 

“We tried everything, then we saw a team using a bag,” said Alexander, a student from City College. His team adopted the plastic-bag strategy as well, and iterated on it like everyone else. They also chose to blow up their balloon with a hand pump after the balloon was already attached to the bag filled with ping pong balls – which was unique. 

“I don’t want to be trying to put the balloon in place when it's about to explode,” Alexander explained. 

Asked about whether the structured problem solving approaches were useful, Alexander’s teammate Brianna, who is a Southwestern College student, talked about how the problem-solving tools have helped her get over mental blocks. “Sometimes we make the most ridiculous things work,” she said. “It’s a pretty fun class for sure.” 

Yoshadara, a City College student who is the third member of this team, described some of the problem solving techniques this way: “It’s about letting yourself be a little absurd.”

Alexander jumped back into the conversation. “The value is in the abstraction. As students, we learn to look at the problem solving that worked and then abstract out the problem solving strategy that can then be applied to other challenges. That’s what mathematicians do all the time,” he said, adding that he is already thinking about how he can apply the process of looking at unintended consequences to improve both how he plays chess and how he goes about solving math problems.

Looking ahead, the goal is to empower as many students as possible in the San Diego area and  beyond to learn to problem solve more enjoyably. It’s a concrete way to give students tools that could encourage them to thrive in the growing number of technical careers that require sharp problem-solving skills, whether or not they require a four-year degree. 

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Why engaging students in problem-solving is needed now

Just as our world and nation face humanitarian, infrastructure and other challenges, our local communities have their own obstacles. As part of their core mission, universities devote considerable time and resources to helping solve problems.

In light of the coronavirus, for instance, they are engaged in everything from the global race to develop a vaccine to the local production of face masks. In the diverse expertise of their faculties, universities are uniquely equipped to help solve a range of problems.

Not actively engaging our students in these pursuits is a lost opportunity.

Most universities participate in improving quality of life in their communities on some level. As their respective communities thrive (or languish), so do they—and vice versa. Engaging in this symbiotic dance exemplifies the American Association of State Colleges and Universities’  call for its members to be “stewards of place.”

Read:   Updated: 106 free higher ed resources during coronavirus pandemic

Cultivating students’ humanitarian ideals

In the South Carolina low country, we face multiple challenges. They include sustainability, workforce housing, elder care, transportation, opioid abuse, cultural heritage preservation, rural education, sea-level rise and others.

Our local agencies and businesses value the fresh perspectives our students provide. Their active engagement in problem-solving, alongside a mentoring professoriate, involves multiple best practices.

Our local agencies and businesses value the fresh perspectives our students provide.

Imagine a bright cable running through the middle of campus; the cable is labeled problem-solving. When we involve students, the cable seamlessly pulls along with it skills such as critical thinking, teamwork and communication. These skills are more important than ever in today’s ambiguous job market.

Employers today are calling for workers who are adaptable, creative and entrepreneurial—all problem-solving traits. Moreover, most college graduates will change jobs, and even fields, frequently during their careers. In a high-tech, high-speed economy in which new jobs surface all the time (think data scientists, drone operators and intelligence engineers), universities must cultivate “learnability” in their graduates.

Problem-solving activities cultivate the humanitarian ideals of today’s students. Today’s universities must challenge a generation of students who want to make the world a better place, and equip them with the means to do so.

Addressing regional, state challenges

At University of South Carolina Beaufort , we have adopted the nonprofit Educational Partnerships for Innovation in Communities–Network’s model for tying the needs of communities to the resources of universities. The model helps us to mobilize students’ inquisitiveness, energy and desire to effect change toward problem-solving projects that tie directly to community challenges.

USCB students participate early on in “beloved communities” experiences, course-embedded modules that emphasize understanding regional issues. Students then advance to community-partnered courses that create collaborations between students, faculty and local organizations for specialized projects. USCB offers Graduation with Leadership Distinction in Community Engagement as a degree designation for students completing related coursework and service hours.

As part of the initiative, which we call “Students Connected: Fieldwork for the Future,” professors have trained and mobilized students to address public transportation, dietary health, cultural heritage preservation, needs of the retirement-age population, and other regional challenges.

On other fronts, our scientists engage students regularly in research projects studying water quality and ecological shifts in the coastal waterways that are so critical to our economy and our way of life. Business majors present strategy-consulting reports to select local companies. Through literacy outreach and tutoring, education majors help improve outcomes in local schools.

Multiple internal and system funding sources incentivize faculty to engage students in research addressing regional and state challenges.

There is much work still to do. As our community grows and improves, so do our students.

The needs are great and the call is clear. Engaging students in problem-solving improves our communities. Just as important, it provides experiences that equip students with skills needed to compete and thrive in a rapidly changing job market and world.

Eric Skipper is provost and executive vice chancellor for Academic Affairs at University of South Carolina Beaufort.

UB’s coronavirus page offers complete coverage of the impacts on higher ed.

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Why Problem Solving Is Important For Students?

Have you ever found yourself struggling to come up with a solution to a complex problem? Perhaps you felt overwhelmed, unsure where to start, or uncertain about the best course of action. If so, you are not alone. Many students face similar challenges when confronted with complex problems.

Problem-solving is important for students because it helps them develop critical thinking, creativity, and metacognitive skills. It allows them to approach complex problems systematically and logically, leading to better solutions.

This article will explore why problem solving is important for students and the benefits of developing these skills. By the end of this article, you will better understand why problem-solving skills are crucial for student success and how you can develop these skills to become a more effective problem-solver.

Table of Contents

Why Are Problem-Solving Skills Important In Today’s World?

With the rapidly changing and complex nature of the modern world, individuals must be equipped to think critically and solve problems effectively to thrive. Below are some reasons why problem-solving skills are so important:

• Innovation And Creativity: Problem-solving skills are essential for innovation and creativity.
• Career Success: These skills are highly valued by employers. The ability to identify and solve problems in the workplace is a key skill that leads to career success and advancement.
• P ersonal Growth: Problem-solving skills are also important for personal growth and development.
• Social Impact: Many of the world’s most pressing problems, such as poverty, inequality, and climate change, require effective problem-solving skills.

Problem-solving skills enable students to approach challenges and obstacles with a solution-oriented mindset. Below are some reasons why problem-solving skills are essential for students:

• Success In Academics: Problem-solving skills are crucial for success in academics. Students who think critically and creatively better understand and apply the concepts they learn in the classroom. These skills help students to tackle complex and challenging academic tasks, leading to better grades and academic performance.
• Life Skills: These skills are important for students’ lives beyond the classroom. These skills help students to navigate real-world problems and challenges, both personal and professional. Students who think critically and creatively are better equipped to handle unexpected situations, make sound decisions, and achieve their goals
• Development Of Critical Thinking Skills: Problem-solving skills are closely linked to critical thinking skills. These skills are essential for analyzing information, evaluating arguments, and making informed decisions. By developing problem-solving skills, students also develop their critical thinking abilities.
• Learning Process: These skills enhance the learning process. When students identify and solve problems, they actively participate in their learning. These skills also help students identify knowledge gaps and seek new information.
• Metacognitive Skills: Problem-solving skills also help to develop metacognitive skills. These skills involve reflecting on one’s thought processes and monitoring one’s learning. By practicing problem-solving skills, students learn to evaluate their thinking, identify improvement areas, and adjust their strategies accordingly.
• Creative Solutions: These skills promote creativity and innovation. Students who think outside the box and develop innovative solutions to problems are more likely to succeed in today’s rapidly changing world.
• Opportunities: Problem-solving skills open up opportunities for students. Employers value employees who can solve problems independently and creatively. Students with critical thinking skills are better equipped to take advantage of job and business opportunities.
• Classroom Culture: These skills also help to create a positive classroom culture. Students learn to collaborate and communicate effectively when they work together to solve problems. This fosters a sense of community and engagement in the classroom.

Get to know: How To Promote Critical Thinking In The Classroom?

What Are The Classroom Approaches To Problem-Solving For Students?

A classroom approach to problem-solving is an effective way to equip students with the skills and knowledge they need to tackle real-world challenges.

Teaching Problem-Solving Skills In Classrooms

One approach to teaching problem-solving skills in classrooms is explicitly teaching students a problem-solving process, such as identifying the problem, brainstorming possible solutions, evaluating the solutions, and selecting the best solution. Teachers can provide opportunities for students to practice this process through real-world scenarios and simulations and encourage them to reflect on their critical thinking skills and strategies.

Problem-Based Learning Approach

In problem-based learning (PBL), students are presented with a real-world problem or scenario and are tasked with working collaboratively to find a solution. This approach encourages students to engage in critical thinking, communication, and problem-solving skills and promotes a deeper understanding of the subject.

Self-Directed Learning Strategy

Self-directed learning is an approach where students take responsibility for their learning and are encouraged to identify and pursue their learning goals. Teachers can support self-directed learning by providing opportunities for students to choose their learning tasks, reflect on their learning, and receive feedback on their progress.

Collaborative Learning

Collaborative learning involves students working in small groups to solve problems, share ideas, and learn from one another. This approach effectively promotes problem-solving skills and encourages students to engage in critical thinking, communication, and teamwork. Collaborative learning is facilitated through various activities, such as discussions, group projects, and problem-solving tasks.

What Are The Benefits Of Problem-Solving Skills For Students?

Problem-solving skills offer numerous benefits to individuals, including academic success, daily problem-solving, job and business opportunities, and community relationships.

Having proficient problem-solving skills puts students in a better position to excel academically. They can analyze and understand complex concepts, think critically, and apply knowledge in new situations.

• Life Skills And Daily Problem-Solving: Problem-solving skills are crucial for everyday situations. People with these skills are better equipped to make informed decisions, solve personal problems, and manage their lives effectively.
• Opportunities In Job And Business: Employers highly value problem-solving skills in various industries. Individuals with these skills have better job prospects and are more likely to succeed. They also identify opportunities for business growth and development.
• Community Relationship: Individuals with strong problem-solving skills are valuable contributors to their communities. They identify and address community problems, work collaboratively with others to find solutions and improve the quality of life for all community members.

What Is The Importance Of Problem-Solving Skills In Everyday Life?

Problem-solving skills are an essential part of a student’s everyday life. These skills enable students to analyze situations critically, identify potential solutions, and implement the most effective course of action. This ability is vital for success in both personal and professional life.

In school, students face numerous problems, from academic challenges to social and emotional issues. Possessing problem-solving skills helps students to manage these challenges effectively. Students with strong problem-solving skills are better equipped to make informed decisions, communicate effectively, and work collaboratively.

They are also better prepared for the demands of the 21st-century workforce, where problem-solving skills are highly valued. Furthermore, problem-solving skills are transferable, meaning they can apply to any situation or context, making them an invaluable asset throughout a student’s life.

Read Also: How to Improve Your Problem-Solving Skills for Conflict Management?

What Is The Role Of Teachers In Developing Problem-Solving Skills For Students?

Effective teaching strategies for developing problem-solving skills

Effective teaching strategies for developing problem-solving skills in students include:

• Encouraging students to ask questions and explore possible solutions on their own.
• Providing hands-on, experiential learning opportunities where students can apply problem-solving skills in real-world situations.
• Using problem-based learning approaches that allow students to work on open-ended, complex problems.
• Providing collaboration and group work opportunities where students can share ideas, perspectives, and solutions.
• Encourage metacognition by asking students to reflect on their thinking processes and critical thinking strategies.

Which Challenges Teachers Faces In Teaching Problem-Solving Skills To Students?

Teaching problem-solving skills is challenging for teachers, requiring a unique approach and pedagogy. The following are some of the challenges that teachers face while teaching problem-solving skills:

• Limited Time: Teachers do not have enough time to devote to teaching problem-solving skills as they need to cover a specific curriculum or course material within a set timeframe.
• Limited Resources: They cannot access adequate tools, technology, and materials to facilitate effective problem-solving learning.
• Students’ Lack Of Prior Knowledge: Students do not have the knowledge needed to solve complex problems, making it challenging for teachers to engage them in problem-solving activities .
• Limited Experience: Teachers may have limited experience in solving complex problems, hindering their ability to teach problem-solving skills effectively.
• Different Learning Styles: Students have different learning styles and abilities, making it challenging for teachers to design a curriculum that meets the needs of all learners.

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How To Develop Problem Solving Skills For Remote Workers?

Common Challenges in Developing Problem Solving Skills for Kindergarten

Throughout the article, we have discussed why problem-solving is important for students. These skills enable students to think critically, analyze situations, and develop creative solutions. These skills are crucial for success in the 21st century, where innovation and adaptability are highly valued.

In the future, problem-solving skills will become even more important as the world changes rapidly. Students who develop strong problem-solving skills will be better equipped to handle the challenges and opportunities that arise in their personal and professional lives.

There are various effective teaching strategies and approaches that teachers can use to develop problem-solving skills in their students. Problem-solving skills are crucial for students’ success and development. Teachers, parents, and communities must prioritize the development of these skills to prepare students for the challenges and opportunities of the future.

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Article search, creative problem solving in primary education: exploring the role of fact finding, problem finding, and solution finding across tasks.

• • Fact finding, problem finding and solution finding were included in creative problem solving tasks • Fact finding and problem finding were positively associated with fluency and originality • Problem finding seemed to help in finding complete ideas, fact finding did not. • Primary school students were able to identify their most creative ideas • Students did not undervalue certain aspects of creativity when applying solution finding Interest in fostering creative problem solving (CPS) from primary education onwards is growing. However, embedding CPS in Education seems to be a challenge. One problem is that generating creative ideas (idea finding) is often taught in isolation, rather than also including processes such as exploring knowledge (fact finding), defining the problem (problem finding) and comparing ideas to identify the most creative ones (solution finding). In the current study, we prepared CPS tasks for primary education that represent this more complete CPS model and studied whether successful fact finding and problem finding were positively associated with the creativity of the ideas found. Additionally, we studied whether solution finding is doable for these young students and how they select the most creative ideas. Bayesian analyses indicated a positive association of fact finding and problem finding with the number of ideas generated and the originality of these ideas. In addition, problem finding seemed to be positively associated with the completeness of ideas, whereas fact finding seemed not. We also found that primary school students were able to identify their most creative ideas. Students did not seem to undervalue certain aspects of creativity when applying solution finding. Our results indicate that when aiming for more and original solutions, teachers could embed fact finding and problem finding in their CPS teaching practices. Our results also indicate primary school students are able to recognize creativity.

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What Is Creative Problem-Solving & Why Is It Important?

• 01 Feb 2022

One of the biggest hindrances to innovation is complacency—it can be more comfortable to do what you know than venture into the unknown. Business leaders can overcome this barrier by mobilizing creative team members and providing space to innovate.

There are several tools you can use to encourage creativity in the workplace. Creative problem-solving is one of them, which facilitates the development of innovative solutions to difficult problems.

Here’s an overview of creative problem-solving and why it’s important in business.

Access your free e-book today.

What Is Creative Problem-Solving?

Research is necessary when solving a problem. But there are situations where a problem’s specific cause is difficult to pinpoint. This can occur when there’s not enough time to narrow down the problem’s source or there are differing opinions about its root cause.

In such cases, you can use creative problem-solving , which allows you to explore potential solutions regardless of whether a problem has been defined.

Creative problem-solving is less structured than other innovation processes and encourages exploring open-ended solutions. It also focuses on developing new perspectives and fostering creativity in the workplace . Its benefits include:

• Finding creative solutions to complex problems : User research can insufficiently illustrate a situation’s complexity. While other innovation processes rely on this information, creative problem-solving can yield solutions without it.
• Adapting to change : Business is constantly changing, and business leaders need to adapt. Creative problem-solving helps overcome unforeseen challenges and find solutions to unconventional problems.
• Fueling innovation and growth : In addition to solutions, creative problem-solving can spark innovative ideas that drive company growth. These ideas can lead to new product lines, services, or a modified operations structure that improves efficiency.

Creative problem-solving is traditionally based on the following key principles :

1. Balance Divergent and Convergent Thinking

Creative problem-solving uses two primary tools to find solutions: divergence and convergence. Divergence generates ideas in response to a problem, while convergence narrows them down to a shortlist. It balances these two practices and turns ideas into concrete solutions.

2. Reframe Problems as Questions

By framing problems as questions, you shift from focusing on obstacles to solutions. This provides the freedom to brainstorm potential ideas.

3. Defer Judgment of Ideas

When brainstorming, it can be natural to reject or accept ideas right away. Yet, immediate judgments interfere with the idea generation process. Even ideas that seem implausible can turn into outstanding innovations upon further exploration and development.

4. Focus on "Yes, And" Instead of "No, But"

Using negative words like "no" discourages creative thinking. Instead, use positive language to build and maintain an environment that fosters the development of creative and innovative ideas.

Creative Problem-Solving and Design Thinking

Whereas creative problem-solving facilitates developing innovative ideas through a less structured workflow, design thinking takes a far more organized approach.

Design thinking is a human-centered, solutions-based process that fosters the ideation and development of solutions. In the online course Design Thinking and Innovation , Harvard Business School Dean Srikant Datar leverages a four-phase framework to explain design thinking.

The four stages are:

• Clarify: The clarification stage allows you to empathize with the user and identify problems. Observations and insights are informed by thorough research. Findings are then reframed as problem statements or questions.
• Ideate: Ideation is the process of coming up with innovative ideas. The divergence of ideas involved with creative problem-solving is a major focus.
• Develop: In the development stage, ideas evolve into experiments and tests. Ideas converge and are explored through prototyping and open critique.
• Implement: Implementation involves continuing to test and experiment to refine the solution and encourage its adoption.

Creative problem-solving primarily operates in the ideate phase of design thinking but can be applied to others. This is because design thinking is an iterative process that moves between the stages as ideas are generated and pursued. This is normal and encouraged, as innovation requires exploring multiple ideas.

Creative Problem-Solving Tools

While there are many useful tools in the creative problem-solving process, here are three you should know:

Creating a Problem Story

One way to innovate is by creating a story about a problem to understand how it affects users and what solutions best fit their needs. Here are the steps you need to take to use this tool properly.

1. Identify a UDP

Create a problem story to identify the undesired phenomena (UDP). For example, consider a company that produces printers that overheat. In this case, the UDP is "our printers overheat."

2. Move Forward in Time

To move forward in time, ask: “Why is this a problem?” For example, minor damage could be one result of the machines overheating. In more extreme cases, printers may catch fire. Don't be afraid to create multiple problem stories if you think of more than one UDP.

3. Move Backward in Time

To move backward in time, ask: “What caused this UDP?” If you can't identify the root problem, think about what typically causes the UDP to occur. For the overheating printers, overuse could be a cause.

Following the three-step framework above helps illustrate a clear problem story:

• The printer is overused.
• The printer overheats.
• The printer breaks down.

You can extend the problem story in either direction if you think of additional cause-and-effect relationships.

4. Break the Chains

By this point, you’ll have multiple UDP storylines. Take two that are similar and focus on breaking the chains connecting them. This can be accomplished through inversion or neutralization.

• Inversion: Inversion changes the relationship between two UDPs so the cause is the same but the effect is the opposite. For example, if the UDP is "the more X happens, the more likely Y is to happen," inversion changes the equation to "the more X happens, the less likely Y is to happen." Using the printer example, inversion would consider: "What if the more a printer is used, the less likely it’s going to overheat?" Innovation requires an open mind. Just because a solution initially seems unlikely doesn't mean it can't be pursued further or spark additional ideas.
• Neutralization: Neutralization completely eliminates the cause-and-effect relationship between X and Y. This changes the above equation to "the more or less X happens has no effect on Y." In the case of the printers, neutralization would rephrase the relationship to "the more or less a printer is used has no effect on whether it overheats."

Even if creating a problem story doesn't provide a solution, it can offer useful context to users’ problems and additional ideas to be explored. Given that divergence is one of the fundamental practices of creative problem-solving, it’s a good idea to incorporate it into each tool you use.

Brainstorming

Brainstorming is a tool that can be highly effective when guided by the iterative qualities of the design thinking process. It involves openly discussing and debating ideas and topics in a group setting. This facilitates idea generation and exploration as different team members consider the same concept from multiple perspectives.

Hosting brainstorming sessions can result in problems, such as groupthink or social loafing. To combat this, leverage a three-step brainstorming method involving divergence and convergence :

• Have each group member come up with as many ideas as possible and write them down to ensure the brainstorming session is productive.
• Continue the divergence of ideas by collectively sharing and exploring each idea as a group. The goal is to create a setting where new ideas are inspired by open discussion.
• Begin the convergence of ideas by narrowing them down to a few explorable options. There’s no "right number of ideas." Don't be afraid to consider exploring all of them, as long as you have the resources to do so.

Alternate Worlds

The alternate worlds tool is an empathetic approach to creative problem-solving. It encourages you to consider how someone in another world would approach your situation.

For example, if you’re concerned that the printers you produce overheat and catch fire, consider how a different industry would approach the problem. How would an automotive expert solve it? How would a firefighter?

Be creative as you consider and research alternate worlds. The purpose is not to nail down a solution right away but to continue the ideation process through diverging and exploring ideas.

Continue Developing Your Skills

Whether you’re an entrepreneur, marketer, or business leader, learning the ropes of design thinking can be an effective way to build your skills and foster creativity and innovation in any setting.

If you're ready to develop your design thinking and creative problem-solving skills, explore Design Thinking and Innovation , one of our online entrepreneurship and innovation courses. If you aren't sure which course is the right fit, download our free course flowchart to determine which best aligns with your goals.

About the Author

Problem Solving

Ai generator.

Problem solving is a crucial skill in both personal and professional settings. Whether it’s addressing a personal challenge or drafting a business problem solving proposal , the ability to identify a problem and develop a solution is essential. Writing a problem solving essay helps articulate the issue clearly and systematically outline potential solutions. Effective problem and solution involves critical thinking, creativity, and a structured approach to overcome obstacles and achieve goals.

What is Problem Solving?

Problem solving is the process of identifying a challenge, analyzing its components, and finding an effective solution. It involves critical thinking, creativity, and the application of various techniques and tools.

Examples of Problem Solving

• Analytical Thinking : Breaking down complex problems into manageable parts.
• Creativity : Developing innovative solutions to problems.
• Critical Thinking : Evaluating information and arguments to make a reasoned decision.
• Decision-Making : Choosing the best course of action from various alternatives.
• Research : Gathering relevant information to understand and solve a problem.
• Communication : Clearly conveying ideas and solutions to others.
• Collaboration : Working effectively with others to solve problems.
• Time Management : Prioritizing tasks to efficiently address problems.
• Adaptability : Adjusting strategies as new information or challenges arise.
• Attention to Detail : Ensuring all aspects of a problem are considered.
• Logical Reasoning : Using logic to identify solutions and predict outcomes.
• Empathy : Understanding others’ perspectives to create more effective solutions.
• Negotiation : Finding mutually acceptable solutions through discussion.
• Conflict Resolution : Addressing and resolving disagreements.
• Patience : Remaining calm and persistent when solving complex problems.
• Organization : Structuring tasks and information systematically.
• Leadership : Guiding and motivating a team to solve problems.
• Decision Analysis : Evaluating the potential impact of different solutions.
• Project Management : Planning and executing solutions effectively.
• Technical Skills : Using specialized knowledge to solve technical problems.
• Customer Service : Resolving customer issues effectively and efficiently.
• Risk Management : Identifying and mitigating potential problems.
• Innovation : Implementing new ideas to solve existing problems.
• Strategic Planning : Developing long-term solutions and plans.
• Resourcefulness : Finding quick and clever ways to overcome difficulties.
• Stress Management : Handling pressure while solving problems.
• Observation : Noticing subtle details that could be key to solving a problem.
• Data Analysis : Interpreting data to inform problem-solving decisions.
• Flexibility : Being open to new approaches and changing plans when necessary.
• Self-Assessment : Reflecting on your own problem-solving process to improve future performance.

Problem-Solving Examples for Students

1. math word problems.

Problem: Jane has 3 apples, and she buys 4 more apples from the store. How many apples does she have now?

• Understand the problem: Jane starts with 3 apples and buys 4 more.
• Break it down: 3 apples (initial) + 4 apples (additional).
• Solve: 3 + 4 = 7.
• Answer: Jane has 7 apples.

2. Group Project Coordination

Problem: A group of students needs to complete a science project, but they are having trouble coordinating their schedules.

• Understand the problem: The main issue is scheduling conflicts.
• Break it down: Identify each member’s available times.
• Research: Use tools like Doodle or Google Calendar to find common free times.
• Brainstorm solutions: Propose meeting during lunch breaks or weekends.
• Evaluate: Choose the most convenient and feasible option for everyone.
• Develop an action plan: Set a recurring meeting time and delegate tasks.
• Implement: Start meeting and working on the project according to the plan.
• Monitor and review: Adjust schedules if conflicts arise and keep track of progress.

3. Essay Writing

Problem: A student struggles to start writing an essay on a given topic.

• Understand the problem: The difficulty is starting the essay.
• Break it down: Identify the essay topic, main points, and required structure.
• Research: Gather information and resources related to the topic.
• Brainstorm solutions: Create an outline, jot down ideas, and decide on the thesis statement.
• Evaluate: Choose the most compelling points and organize them logically.
• Develop an action plan: Write a draft based on the outline, then revise and edit.
• Implement: Begin writing the introduction, followed by the body paragraphs and conclusion.
• Monitor and review: Proofread the essay and make necessary corrections.

4. Time Management

Problem: A student has trouble managing time between homework, extracurricular activities, and leisure.

• Understand the problem: The issue is balancing multiple responsibilities.
• Break it down: Identify all tasks and time commitments.
• Research: Look for time management techniques and tools.
• Brainstorm solutions: Use planners, to-do lists, or apps like Trello or Todoist.
• Evaluate: Choose the most effective tool and technique.
• Develop an action plan: Create a weekly schedule, prioritizing tasks by importance and deadlines.
• Implement: Follow the schedule and adjust as necessary.
• Monitor and review: Reflect on the effectiveness of the schedule and make improvements.

5. Conflict Resolution

Problem: Two students have a disagreement over a shared locker space.

• Understand the problem: The conflict is about sharing limited space.
• Break it down: Identify each student’s concerns and needs.
• Research: Look into conflict resolution strategies.
• Brainstorm solutions: Propose solutions like dividing the locker into specific sections or creating a rotation schedule.
• Evaluate: Choose the fairest and most practical solution.
• Develop an action plan: Agree on the solution and set guidelines.
• Implement: Follow the agreed plan and make adjustments if needed.
• Monitor and review: Ensure both students are satisfied with the arrangement and resolve any further issues.

Problem-Solving Examples in Real-life

Example 1: workplace conflict.

Situation : Two team members have a disagreement that affects their productivity.

• Identify the Problem : Understand the root cause of the conflict.
• Analyze : Talk to both parties separately to get their perspectives.
• Generate Solutions : Consider solutions like mediation, reassignment of tasks, or team-building exercises.
• Evaluate : Assess which solution is likely to resolve the conflict without affecting team morale.
• Implement : Arrange a mediation session.
• Review : Follow up to ensure the conflict is resolved and monitor team dynamics.

Example 2: Personal Finance Management

Situation : Struggling to manage monthly expenses and savings.

• Identify the Problem : Determine specific areas where overspending occurs.
• Analyze : Review bank statements and categorize expenses.
• Generate Solutions : Create a budget, reduce unnecessary expenses, and set savings goals.
• Evaluate : Choose a budgeting method that fits your lifestyle.
• Implement : Start tracking expenses and adjust spending habits.
• Review : Regularly review your budget and savings to ensure you are on track.

How to Improve Your Problem-Solving Skills?

Understand the Problem: Before attempting to solve any problem, it’s crucial to fully understand it. Read through the problem statement carefully and make sure you grasp every detail.

Break It Down : Divide the problem into smaller, more manageable parts. This approach, known as decomposition, makes it easier to tackle complex issues by focusing on individual components one at a time.

Research and Gather Information : Collect all relevant information and data that might help in solving the problem. Look for similar problems and their solutions.

Brainstorm Possible Solutions : Generate as many potential solutions as possible. Don’t worry about evaluating them at this stage; the goal is to think creatively and come up with a wide range of ideas.

Evaluate and Select the Best Solution : Assess the feasibility, pros, and cons of each potential solution. Consider factors such as resources, time, and potential risks. Choose the solution that best addresses the problem and is most practical.

Develop an Action Plan : Create a detailed plan for implementing your chosen solution. Outline the steps you need to take, assign tasks if working in a team, and set deadlines to ensure timely progress.

Implement the Solution : Put your plan into action. Stay focused and be prepared to adapt if necessary. Keep track of your progress and make adjustments as needed.

Monitor and Review : After implementing the solution, monitor the results to ensure the problem is resolved. Evaluate the outcome and review the process to learn from any mistakes or successes.

Problem-solving in workplace

• Enhancing Efficiency : Quick and effective problem resolution can streamline processes and reduce downtime.
• Boosting Productivity : Employees who can solve problems independently help maintain workflow and productivity.
• Improving Customer Satisfaction : Solving customer issues promptly can lead to higher satisfaction and loyalty.
• Fostering Innovation : Problem-solving often leads to new ideas and improvements that drive innovation.
• Promoting Employee Development : Encouraging problem-solving helps employees grow and develop their skills.

How To Highlight Problem-Solving Skills?

1. on your resume.

When listing problem-solving skills on your resume, provide concrete examples. Use action verbs and quantify your achievements where possible.

• Resolved a customer service issue that increased customer satisfaction by 20%.
• Developed a new process that reduced production errors by 15%.

2. In a Cover Letter

Your cover letter is a great place to elaborate on your problem-solving abilities. Describe a specific situation where you successfully addressed a challenge.

“In my previous role at XYZ Company, I identified a bottleneck in our production line. I conducted a thorough analysis and implemented a new workflow, which reduced production time by 25% and saved the company $50,000 annually.”

3. During an Interview

Be prepared to discuss your problem-solving skills in depth during an interview. Use the STAR (Situation, Task, Action, Result) method to structure your responses.

Example: “Can you give an example of a time when you solved a difficult problem at work?”

• Situation: Our sales team was struggling with declining numbers.
• Task: I was tasked with identifying the root cause and finding a solution.
• Action: I analyzed sales data, conducted team meetings, and identified a lack of training as the main issue.
• Result: I organized comprehensive training sessions, which led to a 30% increase in sales over the next quarter.

4. On Social Media and Professional Profiles

Highlight problem-solving skills on LinkedIn and other professional profiles. Share posts or articles about your problem-solving experiences and successes.

“I’m thrilled to share that I recently led a project to overhaul our customer service protocol, resulting in a 40% reduction in response time and a significant boost in customer satisfaction!”

5. In Performance Reviews

During performance reviews, make sure to emphasize your problem-solving contributions. Provide specific examples and outcomes.

“In the past year, I resolved three major project roadblocks, enabling our team to meet all deadlines and exceed our performance goals.”

6. Through Projects and Case Studies

If applicable, create case studies or detailed project descriptions that showcase your problem-solving process and results. This can be particularly useful for portfolios or presentations.

Case Study: Improving IT System Efficiency

• Problem: Frequent system downtimes affecting productivity.
• Solution: Implemented a new monitoring system and revised maintenance schedules.
• Outcome: System downtimes were reduced by 50%, significantly improving productivity.

7. By Demonstrating Soft Skills

Problem-solving often involves other soft skills such as communication, creativity, and teamwork. Highlighting these related skills can further emphasize your ability to solve problems effectively.

“By fostering open communication within my team and encouraging creative brainstorming sessions, we were able to devise innovative solutions to our most pressing challenges.”

How to Answer Problem-Solving Interview Questions

• Understand the Question : Make sure you fully understand the problem before you try to solve it. Ask clarifying questions if needed to ensure you have all the relevant information.
• Think Aloud : Demonstrate your thinking process by explaining your thoughts as you work through the problem. This shows your interviewer how you approach problems and organize your thoughts.
• Break It Down : Divide the problem into smaller, manageable parts. This can make a complex issue seem more approachable and allows you to tackle each component systematically.
• Use a Structured Approach : Employ frameworks or methodologies that are relevant to the question. For example, you might use the STAR method (Situation, Task, Action, Result) for behavioral questions, or a simple problem-solving framework like Define, Measure, Analyze, Improve, Control (DMAIC) for process improvements.
• Be Creative : Employers often look for creativity in your answers. Think outside the box and propose innovative solutions when appropriate.
• Prioritize Solutions : If there are multiple potential solutions, discuss the pros and cons of each and explain why you would choose one over the others.
• Stay Calm and Positive : Problem-solving under pressure is part of the test. Maintain a calm and positive demeanor, showing that you can handle stress effectively.
• Summarize Your Steps : After you have worked through the problem, summarize the steps you took and the conclusion you reached. This helps ensure the interviewer followed your process and underscores your methodical approach.
• Ask for Feedback : After presenting your solution, it can be beneficial to ask if there are any additional factors you might consider. This shows openness to learning and adapting.
• Practice Regularly : Like any skill, problem-solving improves with practice. Regularly engage in brain teasers, logic puzzles, or case studies to sharpen your skills.

Why Are Problem-Solving is Important?

• Effective Decision-Making : Problem-solving is essential for making decisions that are logical, informed, and well-considered. This skill helps individuals and organizations make choices that lead to better outcomes.
• Innovation and Improvement : Solving problems effectively often requires innovative thinking. This can lead to new ideas and improvements in processes, products, and services, which are essential for business growth and adaptation.
• Handling Complex Situations : Many roles involve complex situations that are not straightforward to manage. Problem-solving skills enable individuals to dissect these situations and devise effective strategies to deal with them.
• Enhances Productivity : Efficient problem-solving contributes to higher productivity, as it allows for the identification and removal of obstacles that impede workflow and performance.
• Career Advancement : Individuals who are effective problem solvers are often seen as leaders and can advance more quickly in their careers. This skill is valuable because it demonstrates the ability to handle difficult situations and complex challenges.
• Adaptability and Resilience : Problem-solving is key to adapting to new situations and overcoming challenges. Those who can creatively navigate through difficulties are generally more resilient.
• Quality of Life : On a personal level, strong problem-solving skills can improve one’s quality of life by enabling better management of the challenges that come with daily living.
• Team Collaboration : Problem-solving often requires collaboration. Being good at solving problems can improve your ability to work with others, as it involves communication, persuasion, and negotiation skills.

How to Include Problem-Solving in a Job Application

• Resume : Detail specific problem-solving instances in your job descriptions using action verbs like “analyzed” and “implemented”. Mention the positive outcomes achieved.
• Cover Letter : Narrate a specific instance where your problem-solving skills led to a successful outcome, demonstrating initiative and effectiveness.
• Skills Section : Include “problem-solving” in a skills section if the job ad specifically mentions it.
• Quantify Achievements : Use numbers to describe the impact of your solutions, such as cost savings or efficiency improvements.
• Job Interviews : Prepare to discuss specific examples of your problem-solving skills, focusing on the challenge, your action, and the result.
• References : Brief your references about your problem-solving achievements so they can provide specific examples when contacted by employers.

Tips for Enhancing Problem-Solving

• Practice Regularly: Like any skill, problem-solving improves with regular practice. Engage in activities that challenge your thinking, such as puzzles, games, or real-world problem-solving scenarios.
• Learn from Others: Study how others approach and solve problems. This can provide new strategies and perspectives that you can incorporate into your own problem-solving toolkit.
• Stay Calm and Positive: Maintaining a calm and positive mindset can significantly improve your ability to solve problems. Stress and negativity can cloud your judgment and hinder creative thinking.
• Develop Critical Thinking: Sharpen your critical thinking skills by questioning assumptions, analyzing information, and evaluating evidence. This will help you make more informed and logical decisions.
• Collaborate with Others: Working with others can bring new insights and ideas. Collaboration can also help you see the problem from different angles and develop more effective solutions.
• Keep Learning: Continuously expand your knowledge and skills. The more you know, the better equipped you are to tackle a variety of problems.

How can I improve my problem-solving skills?

Practice regularly, learn various problem-solving techniques, and engage in activities that challenge your thinking.

What are common problem-solving techniques?

Common techniques include brainstorming, root cause analysis, the 5 Whys, and SWOT analysis.

What are the steps in the problem-solving process?

Identify the problem, analyze the problem, generate solutions, select a solution, implement, and evaluate.

How do I demonstrate problem-solving skills in an interview?

Discuss specific situations where you effectively solved problems, highlighting your thought process and outcomes.

What’s the difference between critical thinking and problem-solving?

Critical thinking involves analyzing and evaluating information, while problem-solving focuses on finding solutions to problems.

How do problem-solving skills help in leadership?

They enable leaders to manage challenges effectively, inspire innovation, and guide teams through obstacles.

How to measure problem-solving skills?

Assess through scenarios or challenges that require identifying, analyzing, and resolving problems.

What role does creativity play in problem-solving?

Creativity enables out-of-the-box thinking, which can lead to innovative and effective solutions.

How do you use problem-solving in project management?

Apply it to anticipate potential issues, plan solutions, and ensure smooth project execution.

What’s an example of a problem-solving situation?

Resolving customer complaints by identifying the issue, brainstorming solutions, and implementing changes to prevent future complaints.

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How a Mindset Shift Can Help Solve Special Education Misidentification

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The misidentification of special education students is a problem for many educators, and some experts say the solution is more individualized than some may think.

In a recent ‘A Seat at the Table’ webinar , focused on proven interventions for academic success in special education, panelists agreed there are a handful of issues that contribute to the misidentification of Black and brown students as needing special education, with one being the mindsets educators have.

The number of students in special education in the United States has doubled over the past four decades, from 3.6 million in the 1976-77 school year to almost 7.3 million in 2021-22, according to the Pew Research Center.

When it comes to special education, students of color can be misidentified based on teacher bias, as shown in a 2020 National Center for Learning Disabilities report . Some experts say that the solution to this challenge depends on teachers’ mindset.

“Due to bias within the education system (including within assessments and academic and other policies), students of color can be misidentified as needing special education, and are then placed in more restrictive settings,” says the 2020 report.

Refining support systems and prioritizing data-driven engagement with students can help educators change their mindsets, as panelists discussed.

“When we have a mindset that every student comes to us with strengths and assets, and things to learn ... and every part of their identity is beneficial and an asset to our community, that goes a long way,” Spencer-Iiams said.

Jennifer Spencer-Iiams, an assistant superintendent of the West Linn-Wilsonville school district in Oregon, believes mindset plays an important role in developing special education services and programs for students.

Individualized support is fundamental in understanding the resources students need on a case-by-case basis, instead of generalizing students’ needs, Spencer-Iiams added. She emphasized the importance of believing in every student’s strengths to be able to develop an appropriate support system.

Tiffany Anderson, the superintendent of the Topeka, Kan. public schools said it is important to train educators on what it means for a student to require a special education curriculum. Otherwise, teachers may categorize students as needing the special education curriculum when they actually need an alternative.

“An aligned, standards-based curriculum that is culturally relevant makes a difference in ensuring that there is not an overidentification or a disproportionate number of Black or brown students labeled as special education,” Anderson said.

She also emphasized the importance of “systems of support” that include parents to help them better understand how to advocate for themselves and their children. These systems also include the necessary instruction at home for students to “work within a space [in] which they can self-regulate their behavior,” she said.

Dorothy Valentine, a teacher in Spencer-Iiam’s district, added that support systems should be demystified to better serve students, and “explicit instruction” works for general education as well.

“It’s not just a special education thing, especially in literacy and foundational skills that all students benefit from explicit instruction,” Valentine said.

She says it’s important for educators to look at the makeup of their students, given their different individual needs, and redesign instruction to meet those needs.

When Valentine noticed some of her students having literacy struggles, instead of classifying them as needing special education, she dug further into their backgrounds. Finding that many were English-language learners, she redesigned her approach to student learning.

“I probably spent the first six to eight weeks really digging into self-regulation and tools, ... and in the end, that really served my students long term, and it served them academically as well,” Valentine said.

Valentine describes her classroom as “just a classroom,” where all students are treated equally. She says that mindset helps students more than immediately classifying them as a part of the special education system.

Spencer-Iiams, West Linn’s assistant superintendent, speaks to school leaders nationally, emphasizing the importance of diverse systems that work to meet students’ needs, instead of a generalized method of special education.

“We as leaders have to make sure there are truly well-developed systems of support where we’re not [defaulting] to disability,” Spencer-Iiams said.

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Student Question Bank: Math Questions

Because each question on the Math section deals with different numbers and mathematical scenarios, it's not as simple as the Reading and Writing section to identify exactly what each question stem will look like. You can still use the descriptions in this section to determine which math domains and skills you want to focus on in the Student Question Bank.

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Helping Students Manage Conflict

Answering questions designed to regulate emotions may make it easier for students to find solutions to common disagreements.

These days, our world is inundated with heated discussions, polarizing debates, tense protests, and culture wars, whether they be about abortion rights, gun control, affirmative action, climate change, the Russia-Ukraine war, or the Israeli-Palestinian conflict. Discord is part and parcel of life. At a time when the nation is so divided, schools must do more to help students manage conflict. How can schools empower students to resolve conflicts with peers or adults?

Problem-solving is an emotion-regulation strategy of taking action to directly address an emotional situation. Think about 14-year-old Padma talking to a peer who called her names about how sad she felt. Or 17-year-old Alejandro encouraging his classmates to put more effort into their group project after being pressured to do the heavy lifting. Problem-solving empowers students to take charge of their emotional needs . It can increase students’ self-efficacy in problem resolution and prevent similar situations from happening again.

A powerful problem-solving tool for conflict resolution is students’ expressing their emotional needs to peers or adults in a clear and civil manner. Consider 16-year-old Chris, who feels angry and advocates his need for an apology from a peer who shoved him in the hallway. Or 13-year-old Max, who feels excluded and shares their need for meaningful social interactions. There are five evidence-based steps to problem-solving.

5 Problem-Solving Questions for Conflict Resolution

• What is the problem? Students state how they feel and perceive the situation. ”I” statements are a helpful communication tool for students to state behavior that bothers them without sounding unkind. For example, Chris can say, “I feel annoyed when you shove me without apologizing because it hurts.” Or Padma may say, “I feel sad when you call me fat because it puts me down.” Unlike “you” statements, “I” statements enable students to express their emotions and concerns without others shutting down.
• What are the solutions? Students identify what they need from the situation . They come up with different action steps that others can take to remedy the situation. For instance, Padma may expect an apology or want the name-calling to stop. Max may expect an invite to a social activity or want to tag along.
• What are the consequences? Students assess the helpfulness of each action step . What is good about this action step? What might be bad about this action step? Students choose an action step that is specific, reasonable, and doable for others. For example, Chris may want his peer to never push him, but accidents may occur in a crowded hallway. Alejandro may prefer his classmates to finish the remaining work themselves, but they may not know what to do, resulting in a bad grade for the group project.
• What is the best solution? Students state what they need out of the situation. ”I” statements are an effective communication tool in this case for students to state how others can meet their needs without sounding coercive. For instance, Max can say, “Can I go with you to the movies?” Or Alejandro may say, “I need us to work together on this project. Would you help write up the results?”
• What is the result? Students determine the helpfulness of their solution . If it is helpful, the problem is resolved. If it is not helpful, students could retry by returning to step one and perhaps enlist an adult they trust at school to problem-solve with them.

However, problem-solving requires time and effort to generate, select, and enact solutions. Problem-solving can also lead to frustration when the solution, or some part of it, is not within students’ control. Imagine that 18-year-old Cody, who feels trapped and is being made the subject of rumors, asks others to stop spreading or fueling them, but he has little control over their behavior. So, if students are fatigued or solutions are beyond their control, they should try other emotion regulation strategies (e.g., cognitive reframing, distraction, emotional support seeking) in tandem.

Conflict resolution through these problem-solving strategies is one way to help students manage minor disagreements with classmates. More serious disputes may require some degree of adult intervention. The bottom line is that all students should feel safe and accepted at school, no matter their race, gender, language, religion, or ability, especially amid the current contentious social-political landscape, and educators have to take steps to create this inclusive, welcoming environment.

Collaborative Problem-Solving in Knowledge-Rich Domains: A Multi-Study Structural Equation Model

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• Published: 24 June 2024

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• Laura Brandl   ORCID: orcid.org/0000-0001-7974-7892 1 ,
• Matthias Stadler 1 , 2 ,
• Constanze Richters 1 ,
• Anika Radkowitsch 3 ,
• Martin R. Fischer 2 ,
• Ralf Schmidmaier 4 &
• Frank Fischer 1  

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Collaborative skills are crucial in knowledge-rich domains, such as medical diagnosing. The Collaborative Diagnostic Reasoning (CDR) model emphasizes the importance of high-quality collaborative diagnostic activities (CDAs; e.g., evidence elicitation and sharing), influenced by content and collaboration knowledge as well as more general social skills, to achieve accurate, justified, and efficient diagnostic outcomes (Radkowitsch et al., 2022). However, it has not yet been empirically tested, and the relationships between individual characteristics, CDAs, and diagnostic outcomes remain largely unexplored. The aim of this study was to test the CDR model by analyzing data from three studies in a simulation-based environment and to better understand the construct and the processes involved ( N = 504 intermediate medical students) using a structural equation model including indirect effects. We found various stable relationships between individual characteristics and CDAs, and between CDAs and diagnostic outcome, highlighting the multidimensional nature of CDR. While both content and collaboration knowledge were important for CDAs, none of the individual characteristics directly related to diagnostic outcome. The study suggests that CDAs are important factors in achieving successful diagnoses in collaborative contexts, particularly in simulation-based settings. CDAs are influenced by content and collaboration knowledge, highlighting the importance of understanding collaboration partners’ knowledge. We propose revising the CDR model by assigning higher priority to collaboration knowledge compared with social skills, and dividing the CDAs into information elicitation and sharing, with sharing being more transactive. Training should focus on the development of CDAs to improve CDR skills.

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Introduction

Collaborative skills are highly relevant in many situations, ranging from computer-supported collaborative learning to collaborative problem-solving in professional practice (Fiore et al., 2018 ). While several broad collaborative problem-solving frameworks exist (OECD, 2017 ), most of them are situated in knowledge-lean settings. However, one example of collaborative problem-solving of knowledge-rich domains is collaborative diagnostic reasoning (CDR; Radkowitsch et al., 2022 )—which aligns closely with medical practice—as this is a prototypical knowledge-rich domain requiring high collaboration skills in daily practice. In daily professional practice, physicians from different specialties often need to collaborate with different subdisciplines to solve complex problems, such as diagnosing, that is, determining the causes of a patient’s problem. Moreover, research in medical education and computer-supported collaborative learning suggests that the acquisition of medical knowledge and skills is significantly enhanced by collaborative problem-solving (Hautz et al., 2015 ; Koschmann et al., 1992 ). For problem-solving and learning, it is crucial that all relevant information (e.g., evidence and hypotheses) is elicited from and shared with the collaboration partner (Schmidt & Mamede, 2015 ). However, CDR is not unique to the medical field but also relevant in other domains, such as teacher education (Heitzmann et al., 2019 ).

The CDR model has been the basis of empirical studies and describes how individual characteristics and the diagnostic process are related to the diagnostic outcome. However, it has not yet been empirically tested, and the relationships between individual characteristics, diagnostic process, and diagnostic outcome remain mostly unexplored (Fink et al., 2023 ). The aim of this study is to test the CDR model by analyzing data from three studies with similar samples and tasks investigating CDR in a simulation-based environment. By undertaking these conceptual replications, we aspire to better understand the construct and the processes involved. As prior research has shown, collaboration needs to be performed at a high quality to achieve accurate problem solutions respectively learning outcomes (Pickal et al., 2023 ).

Collaborative Diagnostic Reasoning (CDR) Model

Diagnosing can be understood as the process of solving complex diagnostic problems through “goal-oriented collection and interpretation of case-specific or problem-specific information to reduce uncertainty” in decision-making through performing diagnostic activities at a high quality (Heitzmann et al., 2019 , p. 4). To solve diagnostic problems, that is, to identify the causes of an undesired state, it is increasingly important to collaborate with experts from different fields, as these problems become too complex to be solved individually (Abele, 2018 ; Fiore et al., 2018 ). Collaboration provides advantages such as the division of labor, access to diverse perspectives and expertise, and enhanced solution quality through collaborative sharing of knowledge and skills (Graesser et al., 2018 ).

The CDR model is a theoretical model focusing on the diagnostic process in collaborative settings within knowledge-rich domains (Radkowitsch et al., 2022 ). The CDR model is based on scientific discovery as a dual-search model (SDDS; Klahr & Dunbar, 1988 ) and its further development by van Joolingen and Jong ( 1997 ). The SDDS model describes individual reasoning as the coordinated search through hypothetical evidence and hypotheses spaces and indicates that for successful reasoning it is important not only that high-quality cognitive activities within these spaces are performed but also that one is able to coordinate between them (Klahr & Dunbar, 1988 ). In the extended SDDS model (van Joolingen & Jong, 1997 ) focusing on learning in knowledge-rich domains, a learner hypothesis space was added including all the hypotheses one can search for without additional knowledge. Although Dunbar ( 1995 ) found that conceptual change occurs more often in groups than in individual work, emphasizing the importance of collaborative processes in scientific thinking and knowledge construction, the SDDS model has hardly been systematically applied in computer-supported collaborative learning and collaborative problem-solving.

Thus, the CDR model builds upon these considerations and describes the relationship between individual characteristics, the diagnostic process, and the diagnostic outcome. As in the SDDS model we assume that CDR involves activities within an evidence and hypotheses space; however, unlike the SDDS in the CDR model, these spaces are understood as cognitive storages of information. Which aligns more to the extended dual search space model of scientific discovery learning (van Joolingen & Jong, 1997 ). In summary we assume that coordinating between evidence (data) and hypothesis (theory) is essential for successful diagnosing. Further, the CDR model is extended to not only individual but also collaborative cognitive activities and describes the interaction of epistemic activities (F. Fischer et al., 2014 ) and collaborative activities (Liu et al., 2016 ) to construct a shared problem representation (Rochelle & Teasley, 1995 ) and effectively collaborate. Thus, we define CDR as a set of skills for solving a complex problem collaboratively “by generating and evaluating evidence and hypotheses that can be shared with, elicited from, or negotiated among collaborators” (Radkowitsch et al., 2020 , p. 2). The CDR model also makes assumptions about the factors necessary for successful CDR. First, we look at what successful CDR means, why people differ, and what the mediating processes are.

Diagnostic Outcome: Accuracy, Justification, and Efficiency

The primary outcome of diagnostic processes, such as CDR, is the accuracy of the given diagnosis, which indicates problem-solving performance or expertise (Boshuizen et al., 2020 ). However, competence in diagnostic reasoning, whether it is done individually or collaboratively, also includes justifying the diagnosis and reaching it effectively. This is why, in addition to diagnostic accuracy, diagnostic justification and diagnostic efficiency should also be considered as secondary outcomes of the diagnostic reasoning process (Chernikova et al., 2022 ; Daniel et al., 2019 ). Diagnostic justification makes the reasoning behind the decision transparent and understandable for others (Bauer et al., 2022 ). Good reasoning entails a justification including evidence, which supports the reasoning (Hitchcock, 2005 ). Diagnostic efficiency is related to how much time and effort is needed to reach the correct diagnosis; this is important for CDR, as diagnosticians in practice are usually under time pressure (Braun et al., 2017 ). Both diagnostic justification and diagnostic efficiency are thus indicators of a structured and high-quality reasoning process. So, while in many studies, the focus of assessments regarding diagnostic reasoning is on the accuracy of the given diagnosis (Daniel et al., 2019 ), the CDR model considers all three facets of the diagnostic outcome as relevant factors.

Individual Characteristics: Knowledge and Social Skills

Research has shown that content knowledge, social skills, and, in particular, collaboration knowledge are important prerequisites for, and outcomes of, computer-supported collaborative learning (Jeong et al., 2019 ; Vogel et al., 2017 ). CDR has integrated these dependencies into its model structure. Thus, the CDR model assumes that people engaging in CDR differ with respect to their content knowledge, collaboration knowledge, and domain general social skills.

Content knowledge refers to conceptual and strategic knowledge in a specific domain (Förtsch et al., 2018 ). Conceptual knowledge encompasses factual understanding of domain-specific concepts and their interrelations. Strategic knowledge entails contextualized knowledge regarding problem-solving during the diagnostic process (Stark et al., 2011 ). During expertise development, large amounts of content knowledge are acquired and restructured through experience with problem-solving procedures and routines (Boshuizen et al., 2020 ). Research has repeatedly shown that having high conceptual and strategic knowledge is associated with the diagnostic outcome (e.g., Kiesewetter et al., 2020 ; cf. Fink et al., 2023 ).

In addition to content knowledge, the CDR model assumes that collaborators need collaboration knowledge. A key aspect of collaboration knowledge (i.e., being aware of knowledge distribution in the group; Noroozi et al., 2013 ) is the pooling and processing of non-shared information, as research shows that a lack of collaboration knowledge has a negative impact on information sharing, which in turn has a negative impact on performance (Stasser & Titus, 1985 ).

Finally, general social skills influence the CDR process. These skills mainly influence the collaborative aspect of collaborative problem-solving and less the problem-solving aspect (Graesser et al., 2018 ). Social skills are considered particularly important when collaboration knowledge is low (F. Fischer et al., 2013 ). CDR assumes that in particular the abilities to share and negotiate ideas, to coordinate, and to take the perspective are relevant for the diagnostic process and the diagnostic outcome (Radkowitsch et al., 2022 ; see also Liu et al., 2016 , and Hesse et al., 2015 ).

Diagnostic Process: Collaborative Diagnostic Activities

The diagnostic process is thought to mediate the effect of the individual characteristics on the diagnostic outcome and is described in the CDR model using collaborative diagnostic activities (CDAs), such as evidence elicitation, evidence sharing, and hypotheses sharing (Heitzmann et al., 2019 ; Radkowitsch et al., 2022 ). One of the main functions of CDAs is to construct a shared problem representation (Rochelle & Teasley, 1995 ) by sharing and eliciting relevant information, as information may not be equally distributed among all collaborators initially. To perform these CDAs at a high quality, each collaborator needs to identify information relevant to be shared with the collaboration partner as well as information they need from the collaboration partner (OECD, 2017 ).

Evidence elicitation involves requesting information from a collaboration partner to access additional knowledge resources (Weinberger & Fischer, 2006 ). Evidence sharing and hypothesis sharing involve identifying the information needed by the collaborator to build a shared problem representation. This externalization of relevant information can be understood as the novelty aspect of transactivity (Vogel et al., 2023 ). However, challenges arise from a lack of relevant information due to deficient sharing, which can result from imprecise justification and insufficient clustering of information. In particular, research has shown that collaborators often lack essential information-sharing skills, such as identifying information relevant for others from available data, especially in the medical domain (Kiesewetter et al., 2017 ; Tschan et al., 2009 ).

It is crucial for the diagnostic outcome that all relevant evidence and hypotheses are elicited and shared for the specific collaborators (Tschan et al., 2009 ). However, diagnostic outcomes seem to be influenced more by the relevance and quality of the shared information than by their quantity (Kiesewetter et al., 2017 ; Tschan et al., 2009 ). In addition, recent research has shown that the diagnostic process is not only an embodiment of individual characteristics but also adds a unique contribution to diagnostic outcome (Fink et al., 2023 ). However, it remains difficult to assess and foster CDAs.

Collaboration in Knowledge-Rich Domains: Agent-Based Simulations

There are several challenges when it comes to modelling collaborative settings in knowledge-rich domains for both learning and research endeavors. First, many situations are not easily accessible, as they may be scarce (e.g., natural disasters) or too critical or overwhelming to be approached by novices (e.g., some medical procedures). In these cases, the use of simulation-based environments allows authentic situations approximating real-life diagnostic problems to be provided (Cook et al., 2013 ; Heitzmann et al., 2019 ). Further, the use of technology-enhanced simulations allows data from the ongoing CDR process to be collected in log files. This enables researchers to analyze process data without the need for additional assessments with dedicated tests. Analyzing process data instead of only product data (the assessment’s outcome) permits insights into the problem-solving processes leading to the eventual outcome (e.g., Goldhammer et al., 2017 ). Second, when using human-to-human collaboration, the results of one individual are typically influenced by factors such as group composition or motivation of the collaboration partner (Radkowitsch et al., 2022 ). However, we understand CDR as an individual set of skills enabling collaboration, as indicated by the broader definition of collaborative problem-solving (OECD, 2017 ). Thus, the use of simulated agents as collaboration partners allows a standardized and controlled setting to be created that would otherwise be hard to establish in collaborations among humans (Rosen, 2015 ). There is initial research showing that performance in simulations using computerized agents is moderately related to collaborative skills in other operationalizations (Stadler & Herborn et al., 2020 ). Thus, computerized agents allow for enhanced control over the collaborative process without significantly diverging from human-to-human interaction (Graesser et al., 2018 ; Herborn et al., 2020 ). Third, in less controlled settings it is hard to ensure a specific process is taking place during collaborative problem-solving. For example, when using a human-to-human setting, it is possible that, even though we envision measuring or fostering a specific activity (i.e. hypotheses sharing), it is not performed by the student. Through using an agent-based simulated collaboration partner, we can ensure that all required processes are taking place while solving the problem (Rosen, 2015 ).

Summarizing, by fostering a consistent and controlled setting, simulated agents facilitate the accurate measurement and enhancement of collaborative problem-solving. Evidential support for the application of simulated agents spans a variety of contexts, including tutoring, collaborative learning, knowledge co-construction, and collaborative problem-solving itself, emphasizing their versatility and effectiveness in educational settings (Graesser et al., 2018 ; Rosen, 2015 ).

Research Question and Current Study

In computer-supported collaborative learning there has been the distinction between approaches addressing collaboration to learn and approaches focusing on learning to collaborate. Our study is best understood as addressing the second approach, learning to collaborate. We want to better understand CDR to be able to facilitate collaborative problem-solving skills in learners. Thus, in this paper, we examine what it takes to be able to collaborate in professional practice of knowledge-rich domains, such as medical diagnosing.

When solving diagnostic problems, such as diagnosing a patient, it is often necessary to collaborate with experts from different fields (Radkowitsch et al., 2022 ). In CDR, the diagnostic outcome depends on effectively eliciting and sharing relevant evidence and hypotheses among collaborators, who often lack information-sharing skills (Tschan et al., 2009 ). Thus, the CDR model emphasizes the importance of high-quality CDAs influenced by content and collaboration knowledge as well as social skills to achieve accurate, justified, and efficient diagnostic outcomes (Radkowitsch et al., 2022 ).

This study reviews the relationships postulated in CDR model across three studies to test them empirically and investigate the extent to which the relationships in the CDR model are applicable across studies . By addressing this research question, the current study contributes to a better understanding of the underlying processes in collaborative problem-solving.

We derived a model (Fig. 1 ) from the postulated relationships made by the CDR model. We assume that the individual characteristics are positively related to the CDAs (Hypotheses 1–3), as well as that the CDAs are positively related to the diagnostic outcome (Hypotheses 4–6). Further, we expect that the relationship between the individual characteristics and the diagnostic outcome is partially mediated by the CDAs (Hypotheses 7–15).

Visualization of hypothesized relationships between individual characteristics, collaborative diagnostic activities, and diagnostic outcome

We used data from three studies with similar samples and tasks investigating CDR in an agent-based simulation in the medical domain. The studies can therefore be considered conceptual replication studies. Furthermore, we decided to use an agent-based simulation of a typical collaboration setting in diagnostic reasoning, namely the interdisciplinary collaboration between an internist and a radiologist (Radkowitsch et al., 2022 ).

To test the hypotheses, three studies were analyzed. Footnote 1 Study A was carried out in a laboratory setting in 2019 and included medical students in their third to sixth years. Study B included medical students in their fifth to sixth years. Data collection for this study was online due to the pandemic situation in 2020 and 2021. In both studies, participation was voluntary, and participants were paid 10 per hour. Study C was embedded as an online session in the curriculum of the third year of medical school in 2022. Participation was mandatory, but permission to use the data for research purposes was given voluntarily. All participants took part in only one of the three studies. All three studies received ethical approval from LMU Munich (approval numbers 18-261, 18-262 & 22-0436). For a sample description of each study, see Table 1 . We would like to emphasize that none of the students were specializing in internal medicine, ensuring that the study results reflect the competencies of regular medical students without specialized expertise.

Each of the three studies was organized in the same way, with participants first completing a pretest that included a prior knowledge test, socio-demographic questions, and questions about individual motivational-affective characteristics (e.g., social skills, interest, and motivation). Participants then moved on to the CDR simulation and worked on the patient case. The patient case was the same for studies B and C, but was different for study A. The complexity and difficulty of the patient case did not vary systematically between the patient cases.

Simulation and Task

In the CDR simulation, which is also used as a learning environment, the task was to take over the role of an internist and to collaborate with an agent-based radiologist to obtain further information by performing radiological examinations to diagnose fictitious patient cases with the chief symptom of fever. Medical experts from internal medicine, radiology, and general medicine constructed the patient cases. Each case was structured in the same way: by studying the medical record individually, then collaborating with an agent-based radiologist, and finally reporting the final diagnosis and its justification again individually. For a detailed description on the development and validation of the simulation, see Radkowitsch and colleagues ( 2020 ).

Before working within the simulation, participants were presented with an instruction for the simulated scenario and informed what they were to do with it. Then, we instructed participants how to access further information in the medical record by clicking on hyperlinks, as well as how they could use the toolbar to make notes for the later in the process. Furthermore, we acquainted the students with how they could request further information through collaborating with a radiologist.

During the collaboration with an agent-based radiologist, participants were asked to fill out request forms to obtain further evidence from radiological examinations needed to diagnose the patient case. To effectively collaborate with radiologists, it is crucial for internists to clearly communicate the type of evidence required to reduce uncertainty (referred to as “evidence elicitation”) and share any relevant patient information such as signs, symptoms, and medical history (referred to as “evidence sharing”) as well as suspected diagnoses under investigation (referred to as “hypotheses sharing”) that may impact the radiologists’ diagnostic process. Only when participants shared evidence and hypotheses appropriately for their requested examination did they receive a description and evaluation of the radiologist’s radiologic findings. What was considered appropriate was determined by medical experts for each case and examination in preparation of the cases. Therefore, this scenario involves more than a simple division of tasks, as the quality of one person’s activity (i.e., description and evaluation of the radiologic findings) depends on the collaborative efforts (i.e., CDAs) of the other person (OECD, 2017 )

Measures—Individual Characteristics

The individual characteristics were measured in the pretest. The internal consistencies of each measure per study are displayed in Table 4 in the Results section. We want to point out that the internal consistency of knowledge as a construct—determined by the intercorrelations among knowledge pieces—typically exhibits a moderate level. Importantly, recent research argues that a moderate level of internal consistency does not undermine the constructs’ capacity to explain a significant amount of variance (Edelsbrunner, 2024 ; Stadler et al., 2021 ; Taber, 2018 ).

Content knowledge was separated into radiology and internal medicine knowledge, as these two disciplines play a major role in the diagnosis of the simulated patient cases. For each discipline, conceptual and strategic knowledge was assessed (Kiesewetter et al., 2020 ; Stark et al., 2011 ). The items in each construct were presented in a randomized way in each study. However, the items for study C were shortened due to the embedding of the data collection in the curriculum. Therefore, items with a very high or low item difficulty in previous studies were excluded (Table 2 ).

Conceptual knowledge was measured using single-choice questions including five options adapted from a database of examination questions from the Medical Faculty of the LMU Munich, focusing on relevant and closely related diagnoses of the patient cases used in the simulation. A mean score of 0–1 was calculated, representing the percentage of correct answers and indicating the average conceptual knowledge of the participant per medical knowledge domain.

Strategic content knowledge was measured contextually using key features questions (M. R. Fischer et al., 2005 ). Short cases were introduced followed by two to three follow up questions (e.g., What is your most likely suspected diagnosis?, What is your next examination?, What treatment do you choose?). Each question had eight possible answers, from which the learners were asked to choose one. Again, a mean score of 0–1 was calculated, representing the percentage of correct responses, indicating the average strategic content knowledge of the participant per domain.

The measure of collaboration knowledge was consistent across the three studies and specific to the simulated task. Participants were asked to select all relevant information for seven different patient cases with the cardinal symptom of fever (internal medicine). The patient cases were presented in a randomized order and always included 12 pieces of information regarding the chief complaints, medical history, and physical examination of the patient cases. We then assessed whether each piece of information was shared correctly (i.e. whether relevant information was shared and irrelevant information was not shared) and assigned 1 point and divided it by the maximum of 12 points to standardized the range of measure to 0–1. Then we calculated a mean score for each case and then across all cases, resulting in a range of 0–1 indicating the participants’ collaboration knowledge

The construct of social skills was consistent across the three data collections and was measured on the basis of self-report on a 6-point Likert scale ranging from total disagreement to total agreement. The construct was measured using 23 questions divided into five subscales; for example items, see Table 3 . Five questions aimed to measure the overall construct, and the other four subscales were identified using the complex problem-solving frameworks of Liu et al. ( 2016 ) and Hesse et al. ( 2015 ): perspective taking (four questions), information sharing (five questions), negotiation (four questions), and coordination (five questions). For the final score, the mean of all subcategories was calculated, ranging from 1 to 6, representing general social skills.

Measures—Collaborative Diagnostic Activities (CDA)

We operationalize CDAs in the pretest case in terms of quality of evidence elicitation, evidence sharing, and hypotheses sharing. The internal consistencies of each measure per study are displayed in Table 4 in the Results section.

The quality of evidence elicitation was measured by assessing the appropriateness of the requested radiological examination for the indicated diagnosis. An expert solution was developed to indicate which radiological examinations were appropriate for each of the possible diagnoses. If participants requested an appropriate radiological examination for the indicated diagnoses, they received 1 point for that request attempt. Finally, a mean score across all request attempts (maximum of 3) was calculated and scored. The final mean score was transformed into a binary indicator, with 1 indicating that all requested radiological examinations were appropriated and 0 indicating that inappropriate radiological examinations were also requested, due to the categorical nature of the original data and its skewed distribution, with a majority of responses concentrated in a single category.

The quality of evidence sharing was measured using a precision indicator. This was calculated as the proportion of shared relevant evidence out of all shared evidence. Relevant evidence is defined per case and per diagnosis and indicated by the expert solution. The precision indicator was first calculated per radiological request. We then calculated the mean score, summarizing all attempts in that patient case. This resulted in a range from 0 points, indicating that only irrelevant evidence was shared, to 1 point, indicating that only relevant evidence was shared.

The quality of hypotheses sharing was also measured using a precision indicator. For each patient case, the proportion of diagnoses relevant for the respective patient case to all shared diagnoses was calculated. Which diagnoses were considered relevant for a specific case was determined by an expert solution. As with evidence elicitation, this score was evaluated and converted into a binary variable, where 1 indicated that only relevant diagnoses were shared and 0 indicated that also irrelevant diagnoses were shared, due to the categorical nature of the original data and its skewed distribution, with a majority of responses concentrated in a single category.

Measures—Diagnostic Outcome

We operationalize diagnostic outcome in the pretest case in terms of diagnostic accuracy, diagnostic justification, and diagnostic efficiency.

For diagnostic accuracy, a main diagnosis was assigned to each patient case as expert solution. After working on the patient case and requesting the radiological examination, participants indicated their final diagnosis. To do this, they typed in the first three letters of their desired diagnosis and then received suggestions from a list of 249 possible diagnoses. Diagnostic accuracy was then calculated by coding the agreement between the final diagnosis given and the expert solution. Accurate diagnoses (e.g., hospital-acquired pneumonia) were coded as 1, correct but inaccurate diagnoses (e.g., pneumonia) were coded as 0.5, and incorrect diagnoses were coded as 0. A binary indicator was used for the final diagnostic accuracy score, with 0 indicating an incorrect diagnosis and 1 indicating an at least inaccurate diagnosis, due to the categorical nature of the original data and its skewed distribution, with a majority of responses concentrated in a single category.

A prerequisite for diagnostic justification and diagnostic efficiency is the provision of at least an inaccurate diagnosis. If a participant provided an incorrect diagnosis (coded as 0), diagnostic justification and diagnostic efficiency were immediately scored as 0.

After choosing a final diagnosis, participants were asked to justify their decision in an open text field. Diagnostic justification was then calculated as the proportion of relevant reported information out of all relevant information that would have fully justified the final accurate diagnosis. Again, medical experts agreed on an expert solution that included all relevant information to justify the correct diagnosis. The participants’ solution was coded by two independent coders, each coding the full data, and differences in coding were discussed until the coders agreed. We obtained a range from 0 points, indicating a completely inadequate justification, to 1 point, indicating a completely adequately justified final diagnosis.

Diagnostic efficiency was defined as diagnostic accuracy (non-binary version) divided by the minutes required to solve the case.

Statistical Analyses

To answer the research question, a structural equation model (SEM) was estimated using MPlus Editor, version 8 (Muthén & Muthén, 2017 ). We decided to use a SEM, as it is a comprehensive statistical approach widely used in psychology and educational sciences for its ability to model complex relationships among observed and latent variables while accounting for measurement error (Hilbert & Stadler, 2017 ). SEM support the development and verification of theoretical models, enabling scholars to refine theories and interventions in psychology and education based on empirical evidence, as not only can one relationship be investigated but a system of regressions is also considered simultaneously (Nachtigall et al., 2003 ).

We included all links between the variables and applied a two-step approach, using mean-adjusted and variance-adjusted unweighted least squares (ULSMV, Savalei & Rhemtulla, 2013 ) as the estimator and THETA for parametrization, first examining the measurement model and then the structural model. The assessment of model fit was based on chi-square (χ2), root mean square error of approximation (RMSEA), and comparative fit index (CFI). Model fit is generally indicated by small chi-squared values; RMSEA values of < 0.08 (acceptable) and < 0.06 (excellent), and CFI values ≥ 0.90. We do not consider standardized root mean squared residual (SRMR), because, according to the definition used in MPlus, this index is not appropriate when the sample size is 200 or less, as natural variation in such small samples contributes to larger SRMR values (Asparouhov & Muthén, 2018 ). For hypotheses 1–6, we excluded path coefficients < 0.1 from our interpretation, as they are relatively small. In addition, at least two interpretable path coefficients, of which at least one is statistically significant, are required to find support for the hypothesis. For hypotheses 7–15, specific indirect effects (effect of an individual characteristic on diagnostic outcome through a specific CDA) and total indirect effects (mediation of the effect of an individual characteristic on diagnostic outcome through all mediators) were estimated.

We reported all measures in the study and outlined differences between the three samples. All data and analysis code have been made publicly available at the Open Science Framework (OSF) and can be accessed at https://osf.io/u8t62 . Materials for this study are available by email through the corresponding author. This study’s design and its analysis were not pre-registered.

The descriptive statistics of each measure per study are displayed in Table 4 . The intercorrelations between the measures per study can be found in Appendix Table 7 .

Overall Results of the SEM

All loadings were in the expected directions and statistically significant, except for conceptual knowledge in internal medicine in study C (λ = 0.241, p  = .120), conceptual knowledge in radiology in study A (λ = 0.398, p  = .018), and strategic knowledge in internal medicine (λ = 0.387, p  = .206) and radiology (λ = -0.166, p  = .302) in study B. Standardized factor loadings of the measurement model are shown in Appendix Table 8 .

The SEM has a good fit for study A [ X 2 (75) = 74.086, p = .508, RMSEA = 0.00, CFI = 1.00], study B [ X 2 (75) = 68.309, p  = .695, RMSEA = 0.000, CFI = 1.00], and study C [ X 2 (75) = 93.816, p  = .070, RMSEA = 0.036, CFI = 1.00].

Paths between Individual Characteristics, CDAs, and Diagnostic Outcome

The standardized path coefficients and hypotheses tests for the theoretical model are reported in Table 5 . An overview of the paths supported by the data is shown in Fig. 2 .

Evidence on supported relationships between individual characteristics, collaborative diagnostic activities, and diagnostic outcome

Overall, the R 2 for the CDAs ranged from medium to high for evidence elicitation and evidence sharing, depending on the study, and were consistently low for hypotheses sharing across all three studies. Looking at diagnostic outcome, R 2 is consistently large for diagnostic accuracy and medium to large for diagnostic justification and diagnostic efficiency (Table 6 ).

The path from content knowledge to evidence elicitation was positive and > 0.1 in all three studies, as well as statistically significant in two of them; therefore, we consider Hypothesis 1a supported. The path from content knowledge to evidence sharing was positive and > 0.1 in two studies, as well as statistically significant in one of them; therefore, Hypothesis 1b is also supported. In contrast, the path from content knowledge to hypotheses sharing was indeed also positive in two studies, but as neither was statistically significant, we conclude that Hypothesis 1c was not supported. The path from collaboration knowledge to evidence elicitation was positive and > 0.1 in only one study, but also not statistically significant. Thus, we found that Hypothesis 2a was not supported. For the path from collaboration knowledge to evidence sharing, we found relevant positive and statistically significant coefficients in all three studies. Hypothesis 2b is therefore fully supported by the data. This is not the case for Hypothesis 2c, for which we found no coefficient > 0.1 for the path from collaboration knowledge to hypotheses sharing. For the path from social skills to evidence elicitation, we found positive coefficients > 0.1 in two out of three studies, of which one was also statistically significant. Thus, we consider Hypothesis 3a to be supported. For the path from social skills to evidence sharing, we again found one statistically significant positive coefficient, but in the other two studies it was < 0.1. Therefore, we do not consider Hypothesis 3b to be supported by the data. The same applies to the path from social skills to hypotheses sharing, where the coefficient is < 0.1 in two studies. We therefore do not consider Hypothesis 3c to be supported.

The path from evidence elicitation to diagnostic accuracy was statistically significant and large in magnitude in two out of three studies. Hypothesis 4a is therefore supported. The path from evidence elicitation to diagnostic justification was only positive and > 0.1 in one study, which was also not statistically significant. Therefore, we find no support for Hypothesis 4b. In contrast, the path from evidence elicitation to diagnostic efficiency was positive and statistically significant in two out of three studies, with one large effect. Hypothesis 4c is therefore supported. The path from evidence sharing to diagnostic accuracy was only positive and reasonably large in one study. Therefore, we do not find support for Hypothesis 5a. The path from evidence sharing to diagnostic justification was positive and > 0.1 in two studies as well as statistically significant in one of them, so Hypothesis 5b is supported. In contrast, we did not find a positive coefficient > 0.1 for the path from evidence sharing to diagnostic efficiency. Therefore, Hypothesis 5c is not supported by the data. Although we found coefficients > 0.1 in two studies for the path from hypotheses sharing to diagnostic accuracy, we found no support for Hypothesis 6a, as none of these was statistically significant. This is different for Hypothesis 6b, as we found two positive paths from hypotheses sharing to diagnostic justification, one of which was statistically significant and large. Finally, we found two positive paths from evidence sharing to diagnostic efficiency in three studies, one of which was statistically significant. Hypothesis 6c is therefore supported.

Indirect Effects between Individual Characteristics, CDA, and Diagnostic Outcome

Indirect effects of CDAs on the effect of individual characteristics on the diagnostic outcome in CDR were estimated to test hypotheses 7–15. Although we found a mediating effect of all CDAs (β = .31, p = .008), and specifically for evidence elicitation (β = .27, p = .021) from content knowledge on diagnostic accuracy in study C, and some significant overall and direct effects for other relationships (Appendix Table 9 ), none of these were consistent across all of the studies. Thus, we conclude no consistent support for any of the Hypotheses 7–15.

The aim of the current study was to investigate the extent to which the relationships specified in the CDR model (Radkowitsch et al., 2022 ) are applicable across studies, to better understand the processes underlying CDR in knowledge-rich domains. Not only is this exploration crucial for the medical field or collaborative problem-solving in knowledge-rich domains, but it also offers valuable insights for computer-supported collaborative learning research. Despite CDR’s specific focus, the principles and findings have relevant implications for understanding and enhancing collaborative processes in various educational and professional settings.

Specifically, we investigated how individual learner characteristics, the CDAs, and the diagnostic outcome are related. We therefore analyzed data from three independent studies, all from the same context, a simulation-based environment in the medical domain. Our study found positive relationships between content knowledge and the quality of evidence elicitation as well as the quality of evidence sharing, but not for the quality of hypotheses sharing. Furthermore, collaboration knowledge is positively related to the quality of evidence sharing, but not to the quality of evidence elicitation and the quality of hypotheses sharing. Social skills are only positively related to the quality of evidence elicitation. This underscores the multifaceted nature of collaborative problem-solving situations. Thus, effective CDR, a form of collaborative problem-solving, necessitates a nuanced understanding of the interplay between individual characteristics and CDAs.

The relevance of content knowledge for diagnostic competence is well established in research (Chernikova et al., 2020 ). To develop any diagnostic skills in knowledge-rich domains, learners need to acquire large amounts of knowledge and to restructure it through experience with problem-solving procedures and routines (Boshuizen et al., 2020 ). In the case of CDR this enables the diagnostician to come up with an initial suspected diagnosis, which is likely to be relevant information for the collaboration partner and to guide the further CDAs effectively. The finding that content knowledge only has a relation to the quality of evidence elicitation but none of the other CDAs can be explained by the fact that evidence elicitation is the least transactive CDA within the collaborative decision-making process. When eliciting evidence, the collaboration partner is used as an external knowledge resource (Weinberger & Fischer, 2006 ). So, despite being a collaborative activity, evidence elicitation is about what information from the collaboration partner is needed rather than what the collaboration partner needs. Thus, elicitation is less transactive than sharing, which is focused at what the collaboration partner needs.

Not only content knowledge but also collaboration knowledge is related to the quality of evidence sharing. This finding implies that collaboration knowledge may influence the CDR above and beyond individual content knowledge. It also supports the differentiation of knowledge types made in the CDR model (Radkowitsch et al., 2022 ). Thus, it is important to learn not only the conceptual and strategic medical knowledge that is required for diagnosing but also knowledge about what information is relevant for specific collaboration partners when diagnosing collaboratively. This finding underpins the importance of being aware of the knowledge distribution among collaboration partners and the relevance of the transactive memory (Wegner, 1987 ). Thus, for collaborative problem-solving in knowledge-rich domains—as for computer-supported collaborative learning more generally—knowledge and information awareness is crucial (Engelmann & Hesse, 2010 ).

Thus, the relevance of collaboration knowledge in collaborative problem-solving is an important finding of our study, highlighting that it is critical in facilitating effective collaborative processes and outcomes. The current findings emphasize the need for educational strategies that explicitly target the development of collaborative knowledge to ensure that learners have the knowledge and skills necessary to participate in productive collaborative problem-solving and computer-supported collaborative learning processes. In doing so, the CDR model emphasizes the need for learners to master collaborative skills and build shared problem representations to take full advantage of collaborative learning opportunities.

As CDR is conceptualized to be an interplay of cognitive and social skills (Hesse et al., 2015 ), we also assumed that social skills are related to CDAs. However, we only found evidence of the expected relationship between social skills and CDAs for the quality of evidence elicitation. One explanation could be that collaboration knowledge was relatively high in all three samples, outweighing the influences of general skills. This is consistent with the assumption of the CDR model that the influence of more general social skills is reduced with an increasing level of professional collaboration knowledge (Radkowitsch et al., 2022 ). When collaboration knowledge is available to the diagnosticians, it becomes more important than social skills. This finding again underlines the importance of collaboration knowledge, which can be seen as a domain- and profession-specific development of social skills. However, another explanation could be that, when collaborating with an agent, the effect of social skills decreases, as the agent was not programmed to respond to social nuances. The design of the simulation would thus buffer against the effect of social skills. Although the study by Herborn et al. ( 2020 ) found no differences between human-to-human and human-to-agent collaboration, this does not necessarily invalidate the potential variability in outcomes associated with the social skills incorporated into the agent. For a thorough investigation into the impact of social skills, the agent would need variable social abilities, enabling the variation of the importance of basic social skills for successful collaboration.

Further, we need to conclude that there is no support for a relationship between the individual characteristics and hypotheses sharing, as we found no stable support for the relationship between any of the individual characteristics and the quality of hypotheses sharing. One possible explanation could be that the binary precision measure used to operationalize quality in hypotheses sharing is not sensitive enough or is not capturing the relevant aspect of quality in that activity. Another explanation could be that there is no direct relationship between the individual characteristics and hypotheses sharing, as this relationship is mediated by evidence sharing and thus influenced by the activated knowledge scripts (Schmidt & Rikers, 2007 ).

Looking at the relationships between CDAs and the diagnostic outcome, the current results highlight the need to distinguish between primary (diagnostic accuracy) and secondary (diagnostic justification and efficiency) outcomes of diagnostic reasoning (Daniel et al., 2019 ). Achieving diagnostic accuracy, a purely quantitative outcome measure, is less transactive than other aspects of the diagnostic outcome. This is also where we find the link to evidence elicitation, as we consider this to be the least transactive CDA within the collaborative decision-making process. However, the ability to justify and reach this decision efficiently is then highly dependent on evidence sharing and hypotheses sharing, activities that are more focused on transactivity within CDR (Weinberger & Fischer, 2006 ).

Although individual learner characteristics are found to have an effect on CDAs, and CDAs impact the diagnostic outcome, the effect is not mediated by CDAs across studies. Thus, we assume that, for effective collaborative problem-solving in knowledge-rich domains, such as CDR, it is not enough to have sufficient content and collaboration knowledge; it is also necessary to be able to engage in high quality CDAs to achieve a high-quality diagnostic outcome. This is consistent with research on individual diagnostic reasoning, which shows that diagnostic activities have a unique contribution to the diagnostic outcome after controlling for content knowledge (Fink et al., 2023 ).

In summary, we explored evidence elicitation, evidence sharing, and hypotheses sharing as crucial CDAs. The findings revealed diverse associations of these CDAs with individual characteristics and facets of the diagnostic outcome, supporting the notion that the CDR-process involves a variety of different skills (instead of being one overarching skill). On the basis of these results, we propose categorizing CDAs into activities primarily focused on individual goals and needs (e.g., elicitation) and more transactive activities directly targeted at the collaborator (e.g., sharing). To enhance quality in CDAs, instructional support should be considered. For instance, providing learners with an adaptive collaboration script has been shown to improve evidence sharing quality and promote the internalization of collaboration scripts, fostering the development of collaboration knowledge (Radkowitsch et al., 2021 ). Further, group awareness tools, such as shared concept maps, should be considered to compensate for deficits in one’s collaboration knowledge (Engelmann & Hesse, 2010 ). However, what is required to engage in high-quality CDAs remains an open question. One starting point is domain-general cognitive skills. These could influence CDAs, particularly in the early stages of skill development (Hetmanek et al., 2018 ). Previous research showed that, in diagnostic reasoning, instructional support is more beneficial when being domain-specific than domain-general (Schons et al., 2022 ). Thus, there is still a need for further research on how such instructional support might look like.

Future Research

Although we used data from three studies, all of them were in the same domain; thus, it remains an open question whether these findings are applicable across domains. The CDR model claims that the described relationships are not limited to the medical domain, but rather are valid across domains for collaboratively solving complex problems in knowledge-rich domains. Future research should explore generalizability, for example, for teacher education, which is a distinct field that also requires diagnosing and complex problem-solving (Heitzmann et al., 2019 ).

Regardless of domain, the non-mediating relationship of CDAs between individual characteristics and diagnostic outcomes, as well as the found effects of the CDAs in the current study, suggests that an isolated analysis of CDAs does not fully represent the complex interactions and relationships among activities, individual characteristics, and diagnostic outcomes. Future studies might assess CDAs as a bundle of necessary activities, including a focus on their possible non-linear interactions. We propose to use process data analysis to account for the inherent complexity of the data, as different activities in different sequences can lead to the same outcome (Y. Chen et al., 2019 ). More exploratory analyses of fine-grained, theory-based sequence data are needed to provide insights into more general and more specific processes involved in successful solving complex problems collaboratively (Stadler et al., 2020 ).

As our results have shown, collaboration knowledge and thus awareness of the knowledge distribution among collaboration partners is highly relevant. While a recent meta-analyses showed a moderate effect of group awareness of students’ performance in computer-supported collaborative learning (D. Chen et al., 2024 ), it has so far not been systematically investigated in collaborative problem-solving. Thus, more research on the influence collaboration knowledge in collaborative problem-solving is needed.

Further, additional factors associated with success in collaborative problem-solving—not yet incorporated into the model and thus not yet investigated systematically—include communication skills (OECD, 2017 ), the self-concept of problem-solving ability (Scalise et al., 2016 ), and positive activating emotions during problem-solving tasks (Camacho-Morles et al., 2019 ).

Limitations

There are, however, some limitations to be considered. One is that we have only considered CDAs and how they relate to individual characteristics and outcomes. However, the CDR model also introduces individual diagnostic activities, such as the generation of evidence and the drawing of conclusions. These occur before and after the CDAs and may therefore also have an impact on the described relationships. However, we decided to focus on the CDAs within the CDR process because they are particularly relevant for constructing a shared problem representation, being central to CDR. Future research might consider these individual diagnostic activities, as they could, for example, further explain the how content knowledge is related to the diagnostic outcome.

Another limitation of the current analyses is the operationalization of quality for the CDAs. We chose the appropriateness of radiological examination for the indicated diagnosis for quality of evidence elicitation and precision for quality of evidence sharing and hypotheses sharing. However, all of these only shed light on one perspective of each activity, while possibly obscuring others. For example, it may be that content knowledge is not related to the precision of hypotheses sharing, but this may be different when looking at other quality indicators, such as sensitivity or specificity. However, we decided to use the precision aspect of activities, as research shows that collaborators often fail to identify relevant information, and the amount of information is not related to performance (Tschan et al., 2009 ). Future research may explore a broader variety of quality indicators to be able to assess the quality of CDAs as comprehensively as possible. It should also be noted that in study B a suppression effect (Horst, 1941 ) between hypothesis sharing and evidence elicitation artificially inflated the observed effect size. This is to be expected with process data that can be highly correlated and needs to be considered when interpreting the effect sizes.

In addition, it should be noted that the omega values obtained for the conceptual and strategic knowledge measures were below the commonly accepted threshold of 0.7. While we chose to use omega values as a more appropriate measure of reliability in our context, given the complex and multifaceted nature of the knowledge constructs, these lower-than-expected values raise important questions about the quality of the data and the robustness of the findings. Thus, it is important to understand that knowledge constructs, by their very nature, may not always exhibit high levels of internal consistency due to the diverse and interrelated components they encompass (Edelsbrunner, 2024 ; Stadler et al., 2021 ; Taber, 2018 ). This complexity may be reflected in the moderate omega values observed, which, while seemingly counterintuitive, does not invalidate the potential of the constructs to account for substantial variance in related outcomes. However, findings related to these constructs should be interpreted with caution, and the results presented should be considered tentative. Future research should further explore the implications of using different reliability coefficients in assessing complex constructs within the learning sciences, potentially providing deeper insights into the nuanced nature of knowledge and its measurement.

Another limitation of this study is related to the agent-based collaboration, as a predictive validation of collaborative problem-solving for later human-to-human collaboration in comparable contexts has not yet been systematically conducted. Although the agent-based collaboration situation used has been validated in terms of perceived authenticity, it still does not fully correspond to a real collaboration situation (Rosen, 2015 ). This could be an explanation for the low influence of social skills, as the setting might not require the application of a broad set of social skills (Hesse et al., 2015 ; Radkowitsch et al., 2020 ). In a real-life collaboration, the effects of social skills might be more pronounced. However, research showed that the human-to-agent approach did not lead to different results in collaborative problem-solving than the human-to-human approach in the 2015 PISA study, and correlations with other measures of collaborative skills have been found (Herborn et al., 2020 ; Stadler, Herborn et al., 2020 ). Future studies should specifically test the relevance of social skills for CDR in a human-to-human setting to strengthen the generalizability of our findings.

In conclusion, the current study highlights the importance of individual characteristics and CDAs as independent predictors for achieving good diagnoses in collaborative contexts, at least in the simulation-based settings we used in the studies included in our analysis. Collaboration knowledge emerged as a critical factor, demonstrating its importance over early acquired, general social skills. Therefore, it is imperative to revise the CDR approach by giving higher priority to the proficiency of collaboration knowledge compared with social skills. Furthermore, we conclude that, in simulation-based CDR, content knowledge does not play such a crucial role in predicting diagnostic success compared with many other educational settings, most probably because of the endless opportunities for retrying and revising in simulation-based learning environments.

With respect to CDAs, we suggest refining the perspective on the quality of CDAs and consider revising the CDR model by summarizing CDAs as information elicitation and information sharing, with the former being less transactive, and thus, less demanding than the latter. Adequate performance in both types of CDA is presumed to result in a high-quality shared problem representation, resulting in good diagnostic outcome. Collaborative problem-solving skills are highly relevant in professional practice of knowledge-rich domains, highlighting the need to strengthen these skills in students engaged in CDR and to provide learning opportunities accordingly. Further, the ability to effectively collaborate and construct shared problem representations is important, not only in CDR but also in collaborative problem-solving and computer-supported collaborative learning more in general, highlighting the need for integrating such skills into curricula and instructional design.

By emphasizing these aspects, we can improve the diagnostic skills of individuals in collaborative settings. Through advancing our understanding of CDR, we are taking a key step forward in optimizing collaborative problem-solving and ultimately contributing to improved diagnostic outcomes in various professional domains beyond CDR in medical education. In particular, integrating collaboration knowledge and skills into computer-supported collaborative learning environments can enrich learning experiences and outcomes in various knowledge-rich domains.

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Please note that the data employed in this study have been used in previous publications (e.g., Brandl et al., 2021; Radkowitsch, et al., 2021; Richters et al., 2022 ). However, the research question and the results reported in this study are completely unique to this study. An initial version of this article is presented as a poster at ISLS 2024.

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Brandl, L., Stadler, M., Richters, C. et al. Collaborative Problem-Solving in Knowledge-Rich Domains: A Multi-Study Structural Equation Model. Intern. J. Comput.-Support. Collab. Learn (2024). https://doi.org/10.1007/s11412-024-09425-4

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