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Extensive Problem Solving - Definition, Importance & Example

What is extensive problem solving.

Extensive problem solving is the purchase decision marking in a situation in which the buyer has no information, experience about the products, services and suppliers. In extensive problem solving, lack of information also spreads to the brands for the product and also the criterion that they set for segregating the brands to be small or manageable subsets that help in the purchasing decision later. Consumers usually go for extensive problem solving when they discover that a need is completely new to them which requires significant effort to satisfy it.

The decision making process of a customer includes different levels of purchase decisions, i.e. extensive problem solving, limited problem solving and routinized choice behaviour.

Elements of Extensive Problem Solving

The various parameters which leads to extensive problem solving are:

1. Highly Priced Products: Like a car, house

2. Infrequent Purchases: Purchasing an automobile, HD TV

3. More Customer Participation: Purchasing a laptop with selection of RAM, ROM, display etc

4. Unfamiliar Product Category: Real-estate is a very unexplored category

5. Extensive Research & Time: Locality of buying house, proximity to hospital, station, market etc.

All these parameters or elements leads to extensive problem solving for the customer while taking a decision to make a purchase.

Importance of Extensive Problem Solving

It is very important for marketers to know the process that customers go through before purchasing. They cannot rely upon re-buys and word of mouth all the time for acquiring new customers. The customer in general goes through problem recognition, information search, evaluation, purchase decision and post-purchase evaluation. Closely related to a purchase decision is the problem solving phase. A new product with long term investment leads to extensive problem solving from a customer. This signifies that not all buying situations are same. A rebuy is very much different from a first choice purchase. The recognition that a brand enjoys in a customer’s mind helps the customer to make purchase decisions easily. If the brand has a dedicated marketing communication effort, whenever a consumer feels the need for a new product, they instantly go for it.

To help customers in extensive problem solving, companies must have clear transparent communication. It is thus very important for marketers to use a proper marketing mix so that they can have some cognition from their customers when they think of new products. With the advent of social media, the number of channels for promotion have hugely developed and they require a clear understanding on the segment of customer that each channel serves. The communication channels should lucidly differentiate themselves from other brands so that they are purchased quickly and easily.

Example of Extensive Problem Solving

Let us suppose, that Amber wants to buy a High Definition TV. The problem being, she has no idea regarding it. This is a case of extensive problem solving as the amount of information is low, the risk she is taking is high as she is going with the opinion that she gathers from her peers, the item is expensive and at the same time it also demands huge amount of involvement from the customer. Similarly, buying high price and long-term assets or products like car, motorcycle, house etc leads to extensive problem solving decision for the customers.

Hence, this concludes the definition of Extensive Problem Solving along with its overview.

This article has been researched & authored by the Business Concepts Team . It has been reviewed & published by the MBA Skool Team. The content on MBA Skool has been created for educational & academic purpose only.

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What is Problem Solving? (Steps, Techniques, Examples)

By Status.net Editorial Team on May 7, 2023 — 5 minutes to read

What Is Problem Solving?

Definition and importance.

Problem solving is the process of finding solutions to obstacles or challenges you encounter in your life or work. It is a crucial skill that allows you to tackle complex situations, adapt to changes, and overcome difficulties with ease. Mastering this ability will contribute to both your personal and professional growth, leading to more successful outcomes and better decision-making.

Problem-Solving Steps

The problem-solving process typically includes the following steps:

• Identify the issue : Recognize the problem that needs to be solved.
• Analyze the situation : Examine the issue in depth, gather all relevant information, and consider any limitations or constraints that may be present.
• Generate potential solutions : Brainstorm a list of possible solutions to the issue, without immediately judging or evaluating them.
• Evaluate options : Weigh the pros and cons of each potential solution, considering factors such as feasibility, effectiveness, and potential risks.
• Select the best solution : Choose the option that best addresses the problem and aligns with your objectives.
• Implement the solution : Put the selected solution into action and monitor the results to ensure it resolves the issue.
• Review and learn : Reflect on the problem-solving process, identify any improvements or adjustments that can be made, and apply these learnings to future situations.

Defining the Problem

To start tackling a problem, first, identify and understand it. Analyzing the issue thoroughly helps to clarify its scope and nature. Ask questions to gather information and consider the problem from various angles. Some strategies to define the problem include:

• Brainstorming with others
• Asking the 5 Ws and 1 H (Who, What, When, Where, Why, and How)
• Analyzing cause and effect
• Creating a problem statement

Generating Solutions

Once the problem is clearly understood, brainstorm possible solutions. Think creatively and keep an open mind, as well as considering lessons from past experiences. Consider:

• Creating a list of potential ideas to solve the problem
• Grouping and categorizing similar solutions
• Prioritizing potential solutions based on feasibility, cost, and resources required
• Involving others to share diverse opinions and inputs

Evaluating and Selecting Solutions

Evaluate each potential solution, weighing its pros and cons. To facilitate decision-making, use techniques such as:

• SWOT analysis (Strengths, Weaknesses, Opportunities, Threats)
• Decision-making matrices
• Pros and cons lists
• Risk assessments

After evaluating, choose the most suitable solution based on effectiveness, cost, and time constraints.

Implementing and Monitoring the Solution

Implement the chosen solution and monitor its progress. Key actions include:

• Communicating the solution to relevant parties
• Setting timelines and milestones
• Assigning tasks and responsibilities
• Monitoring the solution and making adjustments as necessary
• Evaluating the effectiveness of the solution after implementation

Utilize feedback from stakeholders and consider potential improvements. Remember that problem-solving is an ongoing process that can always be refined and enhanced.

Problem-Solving Techniques

During each step, you may find it helpful to utilize various problem-solving techniques, such as:

• Brainstorming : A free-flowing, open-minded session where ideas are generated and listed without judgment, to encourage creativity and innovative thinking.
• Root cause analysis : A method that explores the underlying causes of a problem to find the most effective solution rather than addressing superficial symptoms.
• SWOT analysis : A tool used to evaluate the strengths, weaknesses, opportunities, and threats related to a problem or decision, providing a comprehensive view of the situation.
• Mind mapping : A visual technique that uses diagrams to organize and connect ideas, helping to identify patterns, relationships, and possible solutions.

Brainstorming

When facing a problem, start by conducting a brainstorming session. Gather your team and encourage an open discussion where everyone contributes ideas, no matter how outlandish they may seem. This helps you:

• Generate a diverse range of solutions
• Encourage all team members to participate
• Foster creative thinking

When brainstorming, remember to:

• Reserve judgment until the session is over
• Encourage wild ideas
• Combine and improve upon ideas

Root Cause Analysis

For effective problem-solving, identifying the root cause of the issue at hand is crucial. Try these methods:

• 5 Whys : Ask “why” five times to get to the underlying cause.
• Fishbone Diagram : Create a diagram representing the problem and break it down into categories of potential causes.
• Pareto Analysis : Determine the few most significant causes underlying the majority of problems.

SWOT Analysis

SWOT analysis helps you examine the Strengths, Weaknesses, Opportunities, and Threats related to your problem. To perform a SWOT analysis:

• List your problem’s strengths, such as relevant resources or strong partnerships.
• Identify its weaknesses, such as knowledge gaps or limited resources.
• Explore opportunities, like trends or new technologies, that could help solve the problem.
• Recognize potential threats, like competition or regulatory barriers.

SWOT analysis aids in understanding the internal and external factors affecting the problem, which can help guide your solution.

Mind Mapping

A mind map is a visual representation of your problem and potential solutions. It enables you to organize information in a structured and intuitive manner. To create a mind map:

• Write the problem in the center of a blank page.
• Draw branches from the central problem to related sub-problems or contributing factors.
• Add more branches to represent potential solutions or further ideas.

Mind mapping allows you to visually see connections between ideas and promotes creativity in problem-solving.

Examples of Problem Solving in Various Contexts

In the business world, you might encounter problems related to finances, operations, or communication. Applying problem-solving skills in these situations could look like:

• Identifying areas of improvement in your company’s financial performance and implementing cost-saving measures
• Resolving internal conflicts among team members by listening and understanding different perspectives, then proposing and negotiating solutions
• Streamlining a process for better productivity by removing redundancies, automating tasks, or re-allocating resources

In educational contexts, problem-solving can be seen in various aspects, such as:

• Addressing a gap in students’ understanding by employing diverse teaching methods to cater to different learning styles
• Developing a strategy for successful time management to balance academic responsibilities and extracurricular activities
• Seeking resources and support to provide equal opportunities for learners with special needs or disabilities

Everyday life is full of challenges that require problem-solving skills. Some examples include:

• Overcoming a personal obstacle, such as improving your fitness level, by establishing achievable goals, measuring progress, and adjusting your approach accordingly
• Navigating a new environment or city by researching your surroundings, asking for directions, or using technology like GPS to guide you
• Dealing with a sudden change, like a change in your work schedule, by assessing the situation, identifying potential impacts, and adapting your plans to accommodate the change.
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Problem Solving Skills for the Digital Age

Lucid Content

Reading time: about 6 min

Let’s face it: Things don’t always go according to plan. Systems fail, wires get crossed, projects fall apart.

Problems are an inevitable part of life and work. They’re also an opportunity to think critically and find solutions. But knowing how to get to the root of unexpected situations or challenges can mean the difference between moving forward and spinning your wheels.

Here, we’ll break down the key elements of problem solving, some effective problem solving approaches, and a few effective tools to help you arrive at solutions more quickly.

So, what is problem solving?

Broadly defined, problem solving is the process of finding solutions to difficult or complex issues. But you already knew that. Understanding problem solving frameworks, however, requires a deeper dive.

Think about a recent problem you faced. Maybe it was an interpersonal issue. Or it could have been a major creative challenge you needed to solve for a client at work. How did you feel as you approached the issue? Stressed? Confused? Optimistic? Most importantly, which problem solving techniques did you use to tackle the situation head-on? How did you organize thoughts to arrive at the best possible solution?

Solve your problem-solving problem  

Here’s the good news: Good problem solving skills can be learned. By its nature, problem solving doesn’t adhere to a clear set of do’s and don’ts—it requires flexibility, communication, and adaptation. However, most problems you face, at work or in life, can be tackled using four basic steps.

First, you must define the problem . This step sounds obvious, but often, you can notice that something is amiss in a project or process without really knowing where the core problem lies. The most challenging part of the problem solving process is uncovering where the problem originated.

Second, you work to generate alternatives to address the problem directly. This should be a collaborative process to ensure you’re considering every angle of the issue.

Third, you evaluate and test potential solutions to your problem. This step helps you fully understand the complexity of the issue and arrive at the best possible solution.

Finally, fourth, you select and implement the solution that best addresses the problem.

Following this basic four-step process will help you approach every problem you encounter with the same rigorous critical and strategic thinking process, recognize commonalities in new problems, and avoid repeating past mistakes.

In addition to these basic problem solving skills, there are several best practices that you should incorporate. These problem solving approaches can help you think more critically and creatively about any problem:

You may not feel like you have the right expertise to resolve a specific problem. Don’t let that stop you from tackling it. The best problem solvers become students of the problem at hand. Even if you don’t have particular expertise on a topic, your unique experience and perspective can lend itself to creative solutions.

Challenge the status quo

Standard problem solving methodologies and problem solving frameworks are a good starting point. But don’t be afraid to challenge assumptions and push boundaries. Good problem solvers find ways to apply existing best practices into innovative problem solving approaches.

Think broadly about and visualize the issue

Sometimes it’s hard to see a problem, even if it’s right in front of you. Clear answers could be buried in rows of spreadsheet data or lost in miscommunication. Use visualization as a problem solving tool to break down problems to their core elements. Visuals can help you see bottlenecks in the context of the whole process and more clearly organize your thoughts as you define the problem.  

Hypothesize, test, and try again

It might be cliche, but there’s truth in the old adage that 99% of inspiration is perspiration. The best problem solvers ask why, test, fail, and ask why again. Whether it takes one or 1,000 iterations to solve a problem, the important part—and the part that everyone remembers—is the solution.

Consider other viewpoints

Today’s problems are more complex, more difficult to solve, and they often involve multiple disciplines. They require group expertise and knowledge. Being open to others’ expertise increases your ability to be a great problem solver. Great solutions come from integrating your ideas with those of others to find a better solution. Excellent problem solvers build networks and know how to collaborate with other people and teams. They are skilled in bringing people together and sharing knowledge and information.

4 effective problem solving tools

As you work through the problem solving steps, try these tools to better define the issue and find the appropriate solution.

Root cause analysis

Similar to pulling weeds from your garden, if you don’t get to the root of the problem, it’s bound to come back. A root cause analysis helps you figure out the root cause behind any disruption or problem, so you can take steps to correct the problem from recurring. The root cause analysis process involves defining the problem, collecting data, and identifying causal factors to pinpoint root causes and arrive at a solution.

Less structured than other more traditional problem solving methods, the 5 Whys is simply what it sounds like: asking why over and over to get to the root of an obstacle or setback. This technique encourages an open dialogue that can trigger new ideas about a problem, whether done individually or with a group. Each why piggybacks off the answer to the previous why. Get started with the template below—both flowcharts and fishbone diagrams can also help you track your answers to the 5 Whys.

Brainstorming

A meeting of the minds, a brain dump, a mind meld, a jam session. Whatever you call it, collaborative brainstorming can help surface previously unseen issues, root causes, and alternative solutions. Create and share a mind map with your team members to fuel your brainstorming session.

Gap analysis

Sometimes you don’t know where the problem is until you determine where it isn’t. Gap filling helps you analyze inadequacies that are preventing you from reaching an optimized state or end goal. For example, a content gap analysis can help a content marketer determine where holes exist in messaging or the customer experience. Gap analysis is especially helpful when it comes to problem solving because it requires you to find workable solutions. A SWOT analysis chart that looks at a problem through the lens of strengths, opportunities, opportunities, and threats can be a helpful problem solving framework as you start your analysis.

A better way to problem solve

Beyond these practical tips and tools, there are myriad methodical and creative approaches to move a project forward or resolve a conflict. The right approach will depend on the scope of the issue and your desired outcome.

Depending on the problem, Lucidchart offers several templates and diagrams that could help you identify the cause of the issue and map out a plan to resolve it.  Learn more about how Lucidchart can help you take control of your problem solving process .

Lucidchart, a cloud-based intelligent diagramming application, is a core component of Lucid Software's Visual Collaboration Suite. This intuitive, cloud-based solution empowers teams to collaborate in real-time to build flowcharts, mockups, UML diagrams, customer journey maps, and more. Lucidchart propels teams forward to build the future faster. Lucid is proud to serve top businesses around the world, including customers such as Google, GE, and NBC Universal, and 99% of the Fortune 500. Lucid partners with industry leaders, including Google, Atlassian, and Microsoft. Since its founding, Lucid has received numerous awards for its products, business, and workplace culture. For more information, visit lucidchart.com.

Related articles

Sometimes you're faced with challenges that traditional problem solving can't fix. Creative problem solving encourages you to find new, creative ways of thinking that can help you overcome the issue at hand more quickly.

Root cause analysis refers to any problem-solving method used to trace an issue back to its origin. Learn how to complete a root cause analysis—we've even included templates to get you started.

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Problem-Solving Strategies and Obstacles

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

Sean is a fact-checker and researcher with experience in sociology, field research, and data analytics.

JGI / Jamie Grill / Getty Images

• Application
• Improvement

From deciding what to eat for dinner to considering whether it's the right time to buy a house, problem-solving is a large part of our daily lives. Learn some of the problem-solving strategies that exist and how to use them in real life, along with ways to overcome obstacles that are making it harder to resolve the issues you face.

What Is Problem-Solving?

In cognitive psychology , the term 'problem-solving' refers to the mental process that people go through to discover, analyze, and solve problems.

A problem exists when there is a goal that we want to achieve but the process by which we will achieve it is not obvious to us. Put another way, there is something that we want to occur in our life, yet we are not immediately certain how to make it happen.

Maybe you want a better relationship with your spouse or another family member but you're not sure how to improve it. Or you want to start a business but are unsure what steps to take. Problem-solving helps you figure out how to achieve these desires.

The problem-solving process involves:

• Discovery of the problem
• Deciding to tackle the issue
• Seeking to understand the problem more fully
• Researching available options or solutions
• Taking action to resolve the issue

Before problem-solving can occur, it is important to first understand the exact nature of the problem itself. If your understanding of the issue is faulty, your attempts to resolve it will also be incorrect or flawed.

Problem-Solving Mental Processes

Several mental processes are at work during problem-solving. Among them are:

• Perceptually recognizing the problem
• Representing the problem in memory
• Considering relevant information that applies to the problem
• Identifying different aspects of the problem
• Labeling and describing the problem

Problem-Solving Strategies

There are many ways to go about solving a problem. Some of these strategies might be used on their own, or you may decide to employ multiple approaches when working to figure out and fix a problem.

An algorithm is a step-by-step procedure that, by following certain "rules" produces a solution. Algorithms are commonly used in mathematics to solve division or multiplication problems. But they can be used in other fields as well.

In psychology, algorithms can be used to help identify individuals with a greater risk of mental health issues. For instance, research suggests that certain algorithms might help us recognize children with an elevated risk of suicide or self-harm.

One benefit of algorithms is that they guarantee an accurate answer. However, they aren't always the best approach to problem-solving, in part because detecting patterns can be incredibly time-consuming.

There are also concerns when machine learning is involved—also known as artificial intelligence (AI)—such as whether they can accurately predict human behaviors.

Heuristics are shortcut strategies that people can use to solve a problem at hand. These "rule of thumb" approaches allow you to simplify complex problems, reducing the total number of possible solutions to a more manageable set.

If you find yourself sitting in a traffic jam, for example, you may quickly consider other routes, taking one to get moving once again. When shopping for a new car, you might think back to a prior experience when negotiating got you a lower price, then employ the same tactics.

While heuristics may be helpful when facing smaller issues, major decisions shouldn't necessarily be made using a shortcut approach. Heuristics also don't guarantee an effective solution, such as when trying to drive around a traffic jam only to find yourself on an equally crowded route.

Trial and Error

A trial-and-error approach to problem-solving involves trying a number of potential solutions to a particular issue, then ruling out those that do not work. If you're not sure whether to buy a shirt in blue or green, for instance, you may try on each before deciding which one to purchase.

This can be a good strategy to use if you have a limited number of solutions available. But if there are many different choices available, narrowing down the possible options using another problem-solving technique can be helpful before attempting trial and error.

In some cases, the solution to a problem can appear as a sudden insight. You are facing an issue in a relationship or your career when, out of nowhere, the solution appears in your mind and you know exactly what to do.

Insight can occur when the problem in front of you is similar to an issue that you've dealt with in the past. Although, you may not recognize what is occurring since the underlying mental processes that lead to insight often happen outside of conscious awareness .

Research indicates that insight is most likely to occur during times when you are alone—such as when going on a walk by yourself, when you're in the shower, or when lying in bed after waking up.

How to Apply Problem-Solving Strategies in Real Life

If you're facing a problem, you can implement one or more of these strategies to find a potential solution. Here's how to use them in real life:

• Create a flow chart . If you have time, you can take advantage of the algorithm approach to problem-solving by sitting down and making a flow chart of each potential solution, its consequences, and what happens next.
• Recall your past experiences . When a problem needs to be solved fairly quickly, heuristics may be a better approach. Think back to when you faced a similar issue, then use your knowledge and experience to choose the best option possible.
• Start trying potential solutions . If your options are limited, start trying them one by one to see which solution is best for achieving your desired goal. If a particular solution doesn't work, move on to the next.
• Take some time alone . Since insight is often achieved when you're alone, carve out time to be by yourself for a while. The answer to your problem may come to you, seemingly out of the blue, if you spend some time away from others.

Obstacles to Problem-Solving

Problem-solving is not a flawless process as there are a number of obstacles that can interfere with our ability to solve a problem quickly and efficiently. These obstacles include:

• Assumptions: When dealing with a problem, people can make assumptions about the constraints and obstacles that prevent certain solutions. Thus, they may not even try some potential options.
• Functional fixedness : This term refers to the tendency to view problems only in their customary manner. Functional fixedness prevents people from fully seeing all of the different options that might be available to find a solution.
• Irrelevant or misleading information: When trying to solve a problem, it's important to distinguish between information that is relevant to the issue and irrelevant data that can lead to faulty solutions. The more complex the problem, the easier it is to focus on misleading or irrelevant information.
• Mental set: A mental set is a tendency to only use solutions that have worked in the past rather than looking for alternative ideas. A mental set can work as a heuristic, making it a useful problem-solving tool. However, mental sets can also lead to inflexibility, making it more difficult to find effective solutions.

How to Improve Your Problem-Solving Skills

In the end, if your goal is to become a better problem-solver, it's helpful to remember that this is a process. Thus, if you want to improve your problem-solving skills, following these steps can help lead you to your solution:

• Recognize that a problem exists . If you are facing a problem, there are generally signs. For instance, if you have a mental illness , you may experience excessive fear or sadness, mood changes, and changes in sleeping or eating habits. Recognizing these signs can help you realize that an issue exists.
• Decide to solve the problem . Make a conscious decision to solve the issue at hand. Commit to yourself that you will go through the steps necessary to find a solution.
• Seek to fully understand the issue . Analyze the problem you face, looking at it from all sides. If your problem is relationship-related, for instance, ask yourself how the other person may be interpreting the issue. You might also consider how your actions might be contributing to the situation.
• Research potential options . Using the problem-solving strategies mentioned, research potential solutions. Make a list of options, then consider each one individually. What are some pros and cons of taking the available routes? What would you need to do to make them happen?
• Take action . Select the best solution possible and take action. Action is one of the steps required for change . So, go through the motions needed to resolve the issue.
• Try another option, if needed . If the solution you chose didn't work, don't give up. Either go through the problem-solving process again or simply try another option.

You can find a way to solve your problems as long as you keep working toward this goal—even if the best solution is simply to let go because no other good solution exists.

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Stewart SL, Celebre A, Hirdes JP, Poss JW. Risk of suicide and self-harm in kids: The development of an algorithm to identify high-risk individuals within the children's mental health system . Child Psychiat Human Develop . 2020;51:913-924. doi:10.1007/s10578-020-00968-9

Rosenbusch H, Soldner F, Evans AM, Zeelenberg M. Supervised machine learning methods in psychology: A practical introduction with annotated R code . Soc Personal Psychol Compass . 2021;15(2):e12579. doi:10.1111/spc3.12579

Mishra S. Decision-making under risk: Integrating perspectives from biology, economics, and psychology . Personal Soc Psychol Rev . 2014;18(3):280-307. doi:10.1177/1088868314530517

Csikszentmihalyi M, Sawyer K. Creative insight: The social dimension of a solitary moment . In: The Systems Model of Creativity . 2015:73-98. doi:10.1007/978-94-017-9085-7_7

Chrysikou EG, Motyka K, Nigro C, Yang SI, Thompson-Schill SL. Functional fixedness in creative thinking tasks depends on stimulus modality .  Psychol Aesthet Creat Arts . 2016;10(4):425‐435. doi:10.1037/aca0000050

Huang F, Tang S, Hu Z. Unconditional perseveration of the short-term mental set in chunk decomposition .  Front Psychol . 2018;9:2568. doi:10.3389/fpsyg.2018.02568

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

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Consumer Motivation and Involvement

15 Involvement Levels

Depending on a consumer’s experience and knowledge, some consumers may be able to make quick purchase decisions and other consumers may need to get information and be more involved in the decision process before making a purchase. The level of involvement reflects how personally important or interested you are in consuming a product and how much information you need to make a decision. The level of involvement in buying decisions may be considered a continuum from decisions that are fairly routine (consumers are not very involved) to decisions that require extensive thought and a high level of involvement. Whether a decision is low, high, or limited, involvement varies by consumer, not by product.

Low Involvement Consumer Decision Making

At some point in your life you may have considered products you want to own (e.g. luxury or novelty items), but like many of us, you probably didn’t do much more than ponder their relevance or suitability to your life. At other times, you’ve probably looked at dozens of products, compared them, and then decided not to purchase any one of them. When you run out of products such as milk or bread that you buy on a regular basis, you may buy the product as soon as you recognize the need because you do not need to search for information or evaluate alternatives . As Nike would put it, you “just do it.” Low-involvement decisions are, however, typically products that are relatively inexpensive and pose a low risk to the buyer if a mistake is made in purchasing them.

Consumers often engage in routine response behaviour when they make low-involvement decisions — that is, they make automatic purchase decisions based on limited information or information they have gathered in the past. For example, if you always order a Diet Coke at lunch, you’re engaging in routine response behaviour. You may not even think about other drink options at lunch because your routine is to order a Diet Coke, and you simply do it. Similarly, if you run out of Diet Coke at home, you may buy more without any information search.

Some low-involvement purchases are made with no planning or previous thought. These buying decisions are called impulse buying . While you’re waiting to check out at the grocery store, perhaps you see a magazine with a notable celebrity on the cover and buy it on the spot simply because you want it. You might see a roll of tape at a check-out stand and remember you need one or you might see a bag of chips and realize you’re hungry or just want them. These are items that are typically low-involvement decisions. Low involvement decisions aren’t necessarily products purchased on impulse, although they can be.

High Involvement Consumer Decision Making

By contrast, high-involvement decisions carry a higher risk to buyers if they fail. These are often more complex purchases that may carry a high price tag, such as a house, a car, or an insurance policy. These items are not purchased often but are relevant and important to the buyer. Buyers don’t engage in routine response behaviour when purchasing high-involvement products. Instead, consumers engage in what’s called extended problem solving where they spend a lot of time comparing different aspects such as the features of the products, prices, and warranties.

High-involvement decisions can cause buyers a great deal of post-purchase dissonance, also known as cognitive dissonance which is a form of anxiety consumers experience if they are unsure about their purchases or if they had a difficult time deciding between two alternatives. Companies that sell high-involvement products are aware that post purchase dissonance can be a problem. Frequently, marketers try to offer consumers a lot of supporting information about their products, including why they are superior to competing brands and why the consumer won’t be disappointed with their purchase afterwards. Salespeople play a critical role in answering consumer questions and providing extensive support during and after the purchasing stage.

Limited Problem Solving

Limited problem solving falls somewhere between low-involvement (routine) and high-involvement (extended problem solving) decisions. Consumers engage in limited problem solving when they already have some information about a good or service but continue to search for a little more information. Assume you need a new backpack for a hiking trip. While you are familiar with backpacks, you know that new features and materials are available since you purchased your last backpack. You’re going to spend some time looking for one that’s decent because you don’t want it to fall apart while you’re traveling and dump everything you’ve packed on a hiking trail. You might do a little research online and come to a decision relatively quickly. You might consider the choices available at your favourite retail outlet but not look at every backpack at every outlet before making a decision. Or you might rely on the advice of a person you know who’s knowledgeable about backpacks. In some way you shorten or limit your involvement and the decision-making process.

Distinguishing Between Low Involvement and High Involvement

Products, such as chewing gum, which may be low-involvement for many consumers often use advertising such as commercials and sales promotions such as coupons to reach many consumers at once. Companies also try to sell products such as gum in as many locations as possible. Many products that are typically high-involvement such as automobiles may use more personal selling to answer consumers’ questions. Brand names can also be very important regardless of the consumer’s level of purchasing involvement. Consider a low-versus high-involvement decision — say, purchasing a tube of toothpaste versus a new car. You might routinely buy your favorite brand of toothpaste, not thinking much about the purchase (engage in routine response behaviour), but not be willing to switch to another brand either. Having a brand you like saves you “search time” and eliminates the evaluation period because you know what you’re getting.

When it comes to the car, you might engage in extensive problem solving but, again, only be willing to consider a certain brand or brands (e.g. your evoke set for automobiles). For example, in the 1970s, American-made cars had such a poor reputation for quality that buyers joked that a car that’s not foreign is “crap.” The quality of American cars is very good today, but you get the picture. If it’s a high-involvement product you’re purchasing, a good brand name is probably going to be very important to you. That’s why the manufacturers of products that are typically high-involvement decisions can’t become complacent about the value of their brands.

Ways to Increase Involvement Levels

Involvement levels – whether they are low, high, or limited – vary by consumer and less so by product. A consumer’s involvement with a particular product will depend on their experience and knowledge, as well as their general approach to gathering information before making purchasing decisions. In a highly competitive marketplace, however, brands are always vying for consumer preference, loyalty, and affirmation. For this reason, many brands will engage in marketing strategies to increase exposure, attention, and relevance; in other words, brands are constantly seeking ways to motivate consumers with the intention to increase consumer involvement with their products and services.

Some of the different ways marketers increase consumer involvement are: customization; engagement; incentives; appealing to hedonic needs; creating purpose; and, representation.

1. Customization

With Share a Coke, Coca-Cola made a global mass customization implementation that worked for them. The company was able to put the labels on millions of bottles in order to get consumers to notice the changes to the coke bottle in the aisle. People also felt a kinship and moment of recognition once they spotted their names or a friend’s name. Simultaneously this personalization also worked because of the printing equipment that could make it happen and there are not that many first names to begin with. These factors lead the brand to be able to roll this out globally ( Mass Customization #12 , 2017).

2. Engagement

Have you ever heard the expression, “content is king”? Without a doubt, engaging, memorable, and unique marketing content has a lasting impact on consumers. The marketing landscape is a noisy one, polluted with an infinite number of brands advertising extensively to consumers, vying for a fraction of our attention. Savvy marketers recognize the importance of sparking just enough consumer interest so they become motivated to take notice and process their marketing messages. Marketers who create content (that isn’t just about sales and promotion) that inspires, delights, and even serves an audience’s needs are unlocking the secret to engagement. And engagement leads to loyalty.

There is no trick to content marketing, but the brands who do it well know that stepping away – far away – from the usual sales and promotion lines is critical. While content marketing is an effective way to increase sales, grow a brand, and create loyalty, authenticity is at its core.

Bodyform and Old Spice are two brands who very cleverly applied just the right amount of self-deprecating humour to their content marketing that not only engaged consumers, but had them begging for more!

Content as a Key Driver to Consumer Engagement

Engaging customers through content might involve a two-way conversation online, or an entire campaign designed around a single customer comment.

In 2012, Richard Neill posted a message to Bodyform’s Facebook page calling out the brand for lying to and deceiving its customers and audiences for years. Richard went on to say that Bodyform’s advertisements failed to truly depict any sense of reality and that in fact he felt set up by the brand to experience a huge fall. Bodyform, or as Richard addressed the company, “you crafty bugger,” is a UK company that produces and sells feminine protection products to menstruating girls and women (Bodyform, n.d.). Little did Richard know that when he posted his humorous rant to Bodyform that the company would respond by creating a video speaking directly at Richard and coming “clean” on all their deceitful attempts to make having period look like fun. When Bodyform’s video went viral, a brand that would have otherwise continued to blend into the background, captured the attention of a global audience.

Xavier Izaguirre says that, “[a]udience involvement is the process and act of actively involving your target audience in your communication mix, in order to increase their engagement with your message as well as advocacy to your brand.” Bodyform gained global recognition by turning one person’s rant into a viral publicity sensation (even though Richard was not the customer in this case).

Despite being a household name, in the years leading up to Old Spice’s infamous “The Man Your Man Should Smell Like” campaign, sales were flat and the brand had failed to strike a chord in a new generation of consumers. Ad experts at Wieden + Kennedy produced a single 30-second ad (featuring a shirtless and self-deprecating Isaiah Mustafa) that played around the time of the 2010 Super Bowl game. While the ad quickly gained notoriety on YouTube, it was the now infamous, “ Response Campaign ” that made the campaign a leader of its time in audience engagement.

3. Incentives

Customer loyalty and reward programs successfully motivate consumers in the decision making process and reinforce purchasing behaviours ( a feature of instrumental conditioning ). The rationale for loyalty and rewards programs is clear: the cost of acquiring a new customer runs five to 25 times more than selling to an existing one and existing customers spend 67 per cent more than new customers (Bernazzani, n.d.). From the customer perspective, simple and practical reward programs such as Beauty Insider – a point-accumulation model used by Sephora – provides strong incentive for customer loyalty (Bernazzani, n.d.).

4. Appealing to Hedonic Needs

A particularly strong way to motivate consumers to increase involvement levels with a product or service is to appeal to their hedonic needs. Consumers seek to satisfy their need for fun, pleasure, and enjoyment through luxurious and rare purchases. In these cases, consumers are less likely to be price sensitive (“it’s a treat”) and more likely to spend greater processing time on the marketing messages they are presented with when a brand appeals to their greatest desires instead of their basic necessities.

5. Creating Purpose

Millennial and Digital Native consumers are profoundly different than those who came before them. Brands, particularly in the consumer goods category, who demonstrate (and uphold) a commitment to sustainability grow at a faster rate (4 per cent) than those who do not (1 per cent) (“Consumer-Goods…”, 2015). In a 2015 poll, 30,000 consumers were asked how much the environment, packaging, price, marketing, and organic or health and wellness claims had on their consumer-goods’ purchase decisions, and to no surprise, 66 per cent said they would be willing to pay more for sustainable brands. (Nielsen, 2015). A rising trend and important factor to consider in evaluating consumer involvement levels and ways to increase them. So while cruelty-free, fair trade, and locally-sourced may all seem like buzz words to some, they are non-negotiable decision-making factors to a large and growing consumer market.

6. Representation

Celebrity endorsement can have a profound impact on consumers’ overall attitude towards a brand. Consumers who might otherwise have a “neutral” attitude towards a brand (neither positive nor negative) may be more noticed to take notice of a brand’s messages and stimuli if a celebrity they admire is the face of the brand.

When sportswear and sneaker brand Puma signed Rihanna on to not just endorse the brand but design an entire collection, sales soared in all the regions and the brand enjoyed a new “revival” in the U.S. where Under Armour and Nike had been making significant gains (“Rihanna Designs…”, 2017). “Rihanna’s relationship with us makes the brand actual and hot again with young consumers,” said chief executive Bjorn Gulden (“Rihanna Designs…”, 2017).

Media Attributions

• The image of two different coloured sneakers is by Raka Rachgo on Unsplash .
• The image of a coffee card in a wallet is by Rebecca Aldama on Unsplash .
• The image of an island resort in tropical destination is by Ishan @seefromthesky on Unsplash .
• The image of a stack of glossy magazine covers is by Charisse Kenion on Unsplash .

Text Attributions

• The introductory paragraph; sections on “Low Involvement Consumer Decision Making”, “High Involvement Consumer Decision Making”, and “Limited Problem Solving” are adapted from Principles of Marketing which is licensed under CC BY-NC-SA 3.0.

About Us . (n.d.). Body Form. Retrieved February 2, 2019, from https://www.bodyform.co.uk/about-us/.

Kalamut, A. (2010, August 18). Old Spice Video “Case Study” . YouTube [Video]. https://youtu.be/Kg0booW1uOQ.

Bernazzani, S. (n.d.). Customer Loyalty: The Ultimate Guide [Blog post]. https://blog.hubspot.com/service/customer-loyalty.

Bodyform Channel. (2012, October 16). Bodyform Responds: The Truth . YouTube [Video]. https://www.youtube.com/watch?v=Bpy75q2DDow&feature=youtu.be.

Consumer-Goods’ Brands That Demonstrate Commitment to Sustainability Outperform Those That Don’t. (2015, October 12). Nielsen [Press Release]. https://www.nielsen.com/us/en/press-room/2015/consumer-goods-brands-that-demonstrate-commitment-to-sustainability-outperform.html.

Curtin, M. (2018, March 30). 73 Per Cent of Millennials are Willing to Spend More Money on This 1 Type of Product . Inc. https://www.inc.com/melanie-curtin/73-percent-of-millennials-are-willing-to-spend-more-money-on-this-1-type-of-product.html.

Izaguirre, X. (2012, October 17). How are brands using audience involvement to increase reach and engagement?   EConsultancy. https://econsultancy.com/how-are-brands-using-audience-involvement-to-increase-reach-and-engagement/.

Rihanna Designs Help Lift Puma Sportswear Sales . (2017, October 24). Reuters. https://www.businessoffashion.com/articles/news-analysis/rihanna-designs-help-lift-puma-sportswear-sales.

Tarver, E. (2018, October 20). Why the ‘Share a Coke’ Campaign Is So Successful . Investopedia. https://www.investopedia.com/articles/markets/100715/what-makes-share-coke-campaign-so-successful.asp.

Low involvement decision making typically reflects when a consumer who has a low level of interest and attachment to an item. These items may be relatively inexpensive, pose low risk (can be exchanged, returned, or replaced easily), and not require research or comparison shopping.

This concept describes when consumers make low-involvement decisions that are "automatic" in nature and reflect a limited amount of information the consumer has gathered in the past.

A type of purchase that is made with no previous planning or thought.

High involvement decision making typically reflects when a consumer who has a high degree of interest and attachment to an item. These items may be relatively expensive, pose a high risk to the consumer (can't be exchanged or refunded easily or at all), and require some degree of research or comparison shopping.

Also known as "consumer remorse" or "consumer guilt", this is an unsettling feeling consumers may experience post-purchase if they feel their actions are not aligned with their needs.

Consumers engage in limited problem solving when they have some information about an item, but continue to gather more information to inform their purchasing decision. This falls between "low" and "high" involvement on the involvement continuum.

Introduction to Consumer Behaviour Copyright © by Andrea Niosi is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Table of Contents

The problem-solving process, how to solve problems: 5 steps, train to solve problems with lean today, what is problem solving steps, techniques, & best practices explained.

Problem solving is the art of identifying problems and implementing the best possible solutions. Revisiting your problem-solving skills may be the missing piece to leveraging the performance of your business, achieving Lean success, or unlocking your professional potential. 

Ask any colleague if they’re an effective problem-solver and their likely answer will be, “Of course! I solve problems every day.” 

Problem solving is part of most job descriptions, sure. But not everyone can do it consistently. 

Problem solving is the process of defining a problem, identifying its root cause, prioritizing and selecting potential solutions, and implementing the chosen solution.

There’s no one-size-fits-all problem-solving process. Often, it’s a unique methodology that aligns your short- and long-term objectives with the resources at your disposal. Nonetheless, many paradigms center problem solving as a pathway for achieving one’s goals faster and smarter. 

One example is the Six Sigma framework , which emphasizes eliminating errors and refining the customer experience, thereby improving business outcomes. Developed originally by Motorola, the Six Sigma process identifies problems from the perspective of customer satisfaction and improving product delivery. 

Lean management, a similar method, is about streamlining company processes over time so they become “leaner” while producing better outcomes. 

Trendy business management lingo aside, both of these frameworks teach us that investing in your problem solving process for personal and professional arenas will bring better productivity.

1. Precisely Identify Problems

As obvious as it seems, identifying the problem is the first step in the problem-solving process. Pinpointing a problem at the beginning of the process will guide your research, collaboration, and solutions in the right direction. 

At this stage, your task is to identify the scope and substance of the problem. Ask yourself a series of questions: 

• What’s the problem? 
• How many subsets of issues are underneath this problem? 
• What subject areas, departments of work, or functions of business can best define this problem? 

Although some problems are naturally large in scope, precision is key. Write out the problems as statements in planning sheets . Should information or feedback during a later step alter the scope of your problem, revise the statements. 

Framing the problem at this stage will help you stay focused if distractions come up in later stages. Furthermore, how you frame a problem will aid your search for a solution. A strategy of building Lean success, for instance, will emphasize identifying and improving upon inefficient systems. 

2. Collect Information and Plan 

The second step is to collect information and plan the brainstorming process. This is another foundational step to road mapping your problem-solving process. Data, after all, is useful in identifying the scope and substance of your problems. 

Collecting information on the exact details of the problem, however, is done to narrow the brainstorming portion to help you evaluate the outcomes later. Don’t overwhelm yourself with unnecessary information — use the problem statements that you identified in step one as a north star in your research process. 

This stage should also include some planning. Ask yourself:

• What parties will ultimately decide a solution? 
• Whose voices and ideas should be heard in the brainstorming process? 
• What resources are at your disposal for implementing a solution? 

Establish a plan and timeline for steps 3-5. 

3. Brainstorm Solutions

Brainstorming solutions is the bread and butter of the problem-solving process. At this stage, focus on generating creative ideas. As long as the solution directly addresses the problem statements and achieves your goals, don’t immediately rule it out. 

Moreover, solutions are rarely a one-step answer and are more like a roadmap with a set of actions. As you brainstorm ideas, map out these solutions visually and include any relevant factors such as costs involved, action steps, and involved parties. 

With Lean success in mind, stay focused on solutions that minimize waste and improve the flow of business ecosystems. 

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4. Decide and Implement

The most critical stage is selecting a solution. Easier said than done. Consider the criteria that has arisen in previous steps as you decide on a solution that meets your needs. 

Once you select a course of action, implement it. 

Practicing due diligence in earlier stages of the process will ensure that your chosen course of action has been evaluated from all angles. Often, efficient implementation requires us to act correctly and successfully the first time, rather than being hurried and sloppy. Further compilations will create more problems, bringing you back to step 1. 

5. Evaluate

Exercise humility and evaluate your solution honestly. Did you achieve the results you hoped for? What would you do differently next time? 

As some experts note, formulating feedback channels into your evaluation helps solidify future success. A framework like Lean success, for example, will use certain key performance indicators (KPIs) like quality, delivery success, reducing errors, and more. Establish metrics aligned with company goals to assess your solutions.

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35 problem-solving techniques and methods for solving complex problems

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All teams and organizations encounter challenges as they grow. There are problems that might occur for teams when it comes to miscommunication or resolving business-critical issues . You may face challenges around growth , design , user engagement, and even team culture and happiness. In short, problem-solving techniques should be part of every team’s skillset.

Problem-solving methods are primarily designed to help a group or team through a process of first identifying problems and challenges , ideating possible solutions , and then evaluating the most suitable .

Finding effective solutions to complex problems isn’t easy, but by using the right process and techniques, you can help your team be more efficient in the process.

So how do you develop strategies that are engaging, and empower your team to solve problems effectively?

In this blog post, we share a series of problem-solving tools you can use in your next workshop or team meeting. You’ll also find some tips for facilitating the process and how to enable others to solve complex problems.

Let’s get started! 

How do you identify problems?

How do you identify the right solution.

• Tips for more effective problem-solving

Complete problem-solving methods

• Problem-solving techniques to identify and analyze problems
• Problem-solving techniques for developing solutions

Problem-solving warm-up activities

Closing activities for a problem-solving process.

Before you can move towards finding the right solution for a given problem, you first need to identify and define the problem you wish to solve. 

Here, you want to clearly articulate what the problem is and allow your group to do the same. Remember that everyone in a group is likely to have differing perspectives and alignment is necessary in order to help the group move forward. 

Identifying a problem accurately also requires that all members of a group are able to contribute their views in an open and safe manner. It can be scary for people to stand up and contribute, especially if the problems or challenges are emotive or personal in nature. Be sure to try and create a psychologically safe space for these kinds of discussions.

Remember that problem analysis and further discussion are also important. Not taking the time to fully analyze and discuss a challenge can result in the development of solutions that are not fit for purpose or do not address the underlying issue.

Successfully identifying and then analyzing a problem means facilitating a group through activities designed to help them clearly and honestly articulate their thoughts and produce usable insight.

With this data, you might then produce a problem statement that clearly describes the problem you wish to be addressed and also state the goal of any process you undertake to tackle this issue.  

Finding solutions is the end goal of any process. Complex organizational challenges can only be solved with an appropriate solution but discovering them requires using the right problem-solving tool.

After you’ve explored a problem and discussed ideas, you need to help a team discuss and choose the right solution. Consensus tools and methods such as those below help a group explore possible solutions before then voting for the best. They’re a great way to tap into the collective intelligence of the group for great results!

Remember that the process is often iterative. Great problem solvers often roadtest a viable solution in a measured way to see what works too. While you might not get the right solution on your first try, the methods below help teams land on the most likely to succeed solution while also holding space for improvement.

Every effective problem solving process begins with an agenda . A well-structured workshop is one of the best methods for successfully guiding a group from exploring a problem to implementing a solution.

In SessionLab, it’s easy to go from an idea to a complete agenda . Start by dragging and dropping your core problem solving activities into place . Add timings, breaks and necessary materials before sharing your agenda with your colleagues.

The resulting agenda will be your guide to an effective and productive problem solving session that will also help you stay organized on the day!

Tips for more effective problem solving

Problem-solving activities are only one part of the puzzle. While a great method can help unlock your team’s ability to solve problems, without a thoughtful approach and strong facilitation the solutions may not be fit for purpose.

Let’s take a look at some problem-solving tips you can apply to any process to help it be a success!

Clearly define the problem

Jumping straight to solutions can be tempting, though without first clearly articulating a problem, the solution might not be the right one. Many of the problem-solving activities below include sections where the problem is explored and clearly defined before moving on.

This is a vital part of the problem-solving process and taking the time to fully define an issue can save time and effort later. A clear definition helps identify irrelevant information and it also ensures that your team sets off on the right track.

Don’t jump to conclusions

It’s easy for groups to exhibit cognitive bias or have preconceived ideas about both problems and potential solutions. Be sure to back up any problem statements or potential solutions with facts, research, and adequate forethought.

The best techniques ask participants to be methodical and challenge preconceived notions. Make sure you give the group enough time and space to collect relevant information and consider the problem in a new way. By approaching the process with a clear, rational mindset, you’ll often find that better solutions are more forthcoming.  

Try different approaches  

Problems come in all shapes and sizes and so too should the methods you use to solve them. If you find that one approach isn’t yielding results and your team isn’t finding different solutions, try mixing it up. You’ll be surprised at how using a new creative activity can unblock your team and generate great solutions.

Don’t take it personally 

Depending on the nature of your team or organizational problems, it’s easy for conversations to get heated. While it’s good for participants to be engaged in the discussions, ensure that emotions don’t run too high and that blame isn’t thrown around while finding solutions.

You’re all in it together, and even if your team or area is seeing problems, that isn’t necessarily a disparagement of you personally. Using facilitation skills to manage group dynamics is one effective method of helping conversations be more constructive.

Get the right people in the room

Your problem-solving method is often only as effective as the group using it. Getting the right people on the job and managing the number of people present is important too!

If the group is too small, you may not get enough different perspectives to effectively solve a problem. If the group is too large, you can go round and round during the ideation stages.

Creating the right group makeup is also important in ensuring you have the necessary expertise and skillset to both identify and follow up on potential solutions. Carefully consider who to include at each stage to help ensure your problem-solving method is followed and positioned for success.

Document everything

The best solutions can take refinement, iteration, and reflection to come out. Get into a habit of documenting your process in order to keep all the learnings from the session and to allow ideas to mature and develop. Many of the methods below involve the creation of documents or shared resources. Be sure to keep and share these so everyone can benefit from the work done!

Bring a facilitator 

Facilitation is all about making group processes easier. With a subject as potentially emotive and important as problem-solving, having an impartial third party in the form of a facilitator can make all the difference in finding great solutions and keeping the process moving. Consider bringing a facilitator to your problem-solving session to get better results and generate meaningful solutions!

Develop your problem-solving skills

It takes time and practice to be an effective problem solver. While some roles or participants might more naturally gravitate towards problem-solving, it can take development and planning to help everyone create better solutions.

You might develop a training program, run a problem-solving workshop or simply ask your team to practice using the techniques below. Check out our post on problem-solving skills to see how you and your group can develop the right mental process and be more resilient to issues too!

Design a great agenda

Workshops are a great format for solving problems. With the right approach, you can focus a group and help them find the solutions to their own problems. But designing a process can be time-consuming and finding the right activities can be difficult.

Check out our workshop planning guide to level-up your agenda design and start running more effective workshops. Need inspiration? Check out templates designed by expert facilitators to help you kickstart your process!

In this section, we’ll look at in-depth problem-solving methods that provide a complete end-to-end process for developing effective solutions. These will help guide your team from the discovery and definition of a problem through to delivering the right solution.

If you’re looking for an all-encompassing method or problem-solving model, these processes are a great place to start. They’ll ask your team to challenge preconceived ideas and adopt a mindset for solving problems more effectively.

• Six Thinking Hats
• Lightning Decision Jam
• Problem Definition Process
• Discovery & Action Dialogue

Design Sprint 2.0

• Open Space Technology

1. Six Thinking Hats

Individual approaches to solving a problem can be very different based on what team or role an individual holds. It can be easy for existing biases or perspectives to find their way into the mix, or for internal politics to direct a conversation.

Six Thinking Hats is a classic method for identifying the problems that need to be solved and enables your team to consider them from different angles, whether that is by focusing on facts and data, creative solutions, or by considering why a particular solution might not work.

Like all problem-solving frameworks, Six Thinking Hats is effective at helping teams remove roadblocks from a conversation or discussion and come to terms with all the aspects necessary to solve complex problems.

2. Lightning Decision Jam

Featured courtesy of Jonathan Courtney of AJ&Smart Berlin, Lightning Decision Jam is one of those strategies that should be in every facilitation toolbox. Exploring problems and finding solutions is often creative in nature, though as with any creative process, there is the potential to lose focus and get lost.

Unstructured discussions might get you there in the end, but it’s much more effective to use a method that creates a clear process and team focus.

In Lightning Decision Jam, participants are invited to begin by writing challenges, concerns, or mistakes on post-its without discussing them before then being invited by the moderator to present them to the group.

From there, the team vote on which problems to solve and are guided through steps that will allow them to reframe those problems, create solutions and then decide what to execute on. 

By deciding the problems that need to be solved as a team before moving on, this group process is great for ensuring the whole team is aligned and can take ownership over the next stages. 

Lightning Decision Jam (LDJ)   #action   #decision making   #problem solving   #issue analysis   #innovation   #design   #remote-friendly   The problem with anything that requires creative thinking is that it’s easy to get lost—lose focus and fall into the trap of having useless, open-ended, unstructured discussions. Here’s the most effective solution I’ve found: Replace all open, unstructured discussion with a clear process. What to use this exercise for: Anything which requires a group of people to make decisions, solve problems or discuss challenges. It’s always good to frame an LDJ session with a broad topic, here are some examples: The conversion flow of our checkout Our internal design process How we organise events Keeping up with our competition Improving sales flow

3. Problem Definition Process

While problems can be complex, the problem-solving methods you use to identify and solve those problems can often be simple in design. 

By taking the time to truly identify and define a problem before asking the group to reframe the challenge as an opportunity, this method is a great way to enable change.

Begin by identifying a focus question and exploring the ways in which it manifests before splitting into five teams who will each consider the problem using a different method: escape, reversal, exaggeration, distortion or wishful. Teams develop a problem objective and create ideas in line with their method before then feeding them back to the group.

This method is great for enabling in-depth discussions while also creating space for finding creative solutions too!

Problem Definition   #problem solving   #idea generation   #creativity   #online   #remote-friendly   A problem solving technique to define a problem, challenge or opportunity and to generate ideas.

4. The 5 Whys 

Sometimes, a group needs to go further with their strategies and analyze the root cause at the heart of organizational issues. An RCA or root cause analysis is the process of identifying what is at the heart of business problems or recurring challenges. 

The 5 Whys is a simple and effective method of helping a group go find the root cause of any problem or challenge and conduct analysis that will deliver results. 

By beginning with the creation of a problem statement and going through five stages to refine it, The 5 Whys provides everything you need to truly discover the cause of an issue.

The 5 Whys   #hyperisland   #innovation   This simple and powerful method is useful for getting to the core of a problem or challenge. As the title suggests, the group defines a problems, then asks the question “why” five times, often using the resulting explanation as a starting point for creative problem solving.

5. World Cafe

World Cafe is a simple but powerful facilitation technique to help bigger groups to focus their energy and attention on solving complex problems.

World Cafe enables this approach by creating a relaxed atmosphere where participants are able to self-organize and explore topics relevant and important to them which are themed around a central problem-solving purpose. Create the right atmosphere by modeling your space after a cafe and after guiding the group through the method, let them take the lead!

Making problem-solving a part of your organization’s culture in the long term can be a difficult undertaking. More approachable formats like World Cafe can be especially effective in bringing people unfamiliar with workshops into the fold. 

World Cafe   #hyperisland   #innovation   #issue analysis   World Café is a simple yet powerful method, originated by Juanita Brown, for enabling meaningful conversations driven completely by participants and the topics that are relevant and important to them. Facilitators create a cafe-style space and provide simple guidelines. Participants then self-organize and explore a set of relevant topics or questions for conversation.

6. Discovery & Action Dialogue (DAD)

One of the best approaches is to create a safe space for a group to share and discover practices and behaviors that can help them find their own solutions.

With DAD, you can help a group choose which problems they wish to solve and which approaches they will take to do so. It’s great at helping remove resistance to change and can help get buy-in at every level too!

This process of enabling frontline ownership is great in ensuring follow-through and is one of the methods you will want in your toolbox as a facilitator.

Discovery & Action Dialogue (DAD)   #idea generation   #liberating structures   #action   #issue analysis   #remote-friendly   DADs make it easy for a group or community to discover practices and behaviors that enable some individuals (without access to special resources and facing the same constraints) to find better solutions than their peers to common problems. These are called positive deviant (PD) behaviors and practices. DADs make it possible for people in the group, unit, or community to discover by themselves these PD practices. DADs also create favorable conditions for stimulating participants’ creativity in spaces where they can feel safe to invent new and more effective practices. Resistance to change evaporates as participants are unleashed to choose freely which practices they will adopt or try and which problems they will tackle. DADs make it possible to achieve frontline ownership of solutions.

7. Design Sprint 2.0

Want to see how a team can solve big problems and move forward with prototyping and testing solutions in a few days? The Design Sprint 2.0 template from Jake Knapp, author of Sprint, is a complete agenda for a with proven results.

Developing the right agenda can involve difficult but necessary planning. Ensuring all the correct steps are followed can also be stressful or time-consuming depending on your level of experience.

Use this complete 4-day workshop template if you are finding there is no obvious solution to your challenge and want to focus your team around a specific problem that might require a shortcut to launching a minimum viable product or waiting for the organization-wide implementation of a solution.

8. Open space technology

Open space technology- developed by Harrison Owen – creates a space where large groups are invited to take ownership of their problem solving and lead individual sessions. Open space technology is a great format when you have a great deal of expertise and insight in the room and want to allow for different takes and approaches on a particular theme or problem you need to be solved.

Start by bringing your participants together to align around a central theme and focus their efforts. Explain the ground rules to help guide the problem-solving process and then invite members to identify any issue connecting to the central theme that they are interested in and are prepared to take responsibility for.

Once participants have decided on their approach to the core theme, they write their issue on a piece of paper, announce it to the group, pick a session time and place, and post the paper on the wall. As the wall fills up with sessions, the group is then invited to join the sessions that interest them the most and which they can contribute to, then you’re ready to begin!

Everyone joins the problem-solving group they’ve signed up to, record the discussion and if appropriate, findings can then be shared with the rest of the group afterward.

Open Space Technology   #action plan   #idea generation   #problem solving   #issue analysis   #large group   #online   #remote-friendly   Open Space is a methodology for large groups to create their agenda discerning important topics for discussion, suitable for conferences, community gatherings and whole system facilitation

Techniques to identify and analyze problems

Using a problem-solving method to help a team identify and analyze a problem can be a quick and effective addition to any workshop or meeting.

While further actions are always necessary, you can generate momentum and alignment easily, and these activities are a great place to get started.

We’ve put together this list of techniques to help you and your team with problem identification, analysis, and discussion that sets the foundation for developing effective solutions.

Let’s take a look!

• The Creativity Dice
• Fishbone Analysis
• Problem Tree
• SWOT Analysis
• Agreement-Certainty Matrix
• The Journalistic Six
• LEGO Challenge
• What, So What, Now What?
• Journalists

Individual and group perspectives are incredibly important, but what happens if people are set in their minds and need a change of perspective in order to approach a problem more effectively?

Flip It is a method we love because it is both simple to understand and run, and allows groups to understand how their perspectives and biases are formed. 

Participants in Flip It are first invited to consider concerns, issues, or problems from a perspective of fear and write them on a flip chart. Then, the group is asked to consider those same issues from a perspective of hope and flip their understanding.  

No problem and solution is free from existing bias and by changing perspectives with Flip It, you can then develop a problem solving model quickly and effectively.

Flip It!   #gamestorming   #problem solving   #action   Often, a change in a problem or situation comes simply from a change in our perspectives. Flip It! is a quick game designed to show players that perspectives are made, not born.

10. The Creativity Dice

One of the most useful problem solving skills you can teach your team is of approaching challenges with creativity, flexibility, and openness. Games like The Creativity Dice allow teams to overcome the potential hurdle of too much linear thinking and approach the process with a sense of fun and speed. 

In The Creativity Dice, participants are organized around a topic and roll a dice to determine what they will work on for a period of 3 minutes at a time. They might roll a 3 and work on investigating factual information on the chosen topic. They might roll a 1 and work on identifying the specific goals, standards, or criteria for the session.

Encouraging rapid work and iteration while asking participants to be flexible are great skills to cultivate. Having a stage for idea incubation in this game is also important. Moments of pause can help ensure the ideas that are put forward are the most suitable. 

The Creativity Dice   #creativity   #problem solving   #thiagi   #issue analysis   Too much linear thinking is hazardous to creative problem solving. To be creative, you should approach the problem (or the opportunity) from different points of view. You should leave a thought hanging in mid-air and move to another. This skipping around prevents premature closure and lets your brain incubate one line of thought while you consciously pursue another.

11. Fishbone Analysis

Organizational or team challenges are rarely simple, and it’s important to remember that one problem can be an indication of something that goes deeper and may require further consideration to be solved.

Fishbone Analysis helps groups to dig deeper and understand the origins of a problem. It’s a great example of a root cause analysis method that is simple for everyone on a team to get their head around. 

Participants in this activity are asked to annotate a diagram of a fish, first adding the problem or issue to be worked on at the head of a fish before then brainstorming the root causes of the problem and adding them as bones on the fish. 

Using abstractions such as a diagram of a fish can really help a team break out of their regular thinking and develop a creative approach.

Fishbone Analysis   #problem solving   ##root cause analysis   #decision making   #online facilitation   A process to help identify and understand the origins of problems, issues or observations.

12. Problem Tree 

Encouraging visual thinking can be an essential part of many strategies. By simply reframing and clarifying problems, a group can move towards developing a problem solving model that works for them. 

In Problem Tree, groups are asked to first brainstorm a list of problems – these can be design problems, team problems or larger business problems – and then organize them into a hierarchy. The hierarchy could be from most important to least important or abstract to practical, though the key thing with problem solving games that involve this aspect is that your group has some way of managing and sorting all the issues that are raised.

Once you have a list of problems that need to be solved and have organized them accordingly, you’re then well-positioned for the next problem solving steps.

Problem tree   #define intentions   #create   #design   #issue analysis   A problem tree is a tool to clarify the hierarchy of problems addressed by the team within a design project; it represents high level problems or related sublevel problems.

13. SWOT Analysis

Chances are you’ve heard of the SWOT Analysis before. This problem-solving method focuses on identifying strengths, weaknesses, opportunities, and threats is a tried and tested method for both individuals and teams.

Start by creating a desired end state or outcome and bare this in mind – any process solving model is made more effective by knowing what you are moving towards. Create a quadrant made up of the four categories of a SWOT analysis and ask participants to generate ideas based on each of those quadrants.

Once you have those ideas assembled in their quadrants, cluster them together based on their affinity with other ideas. These clusters are then used to facilitate group conversations and move things forward. 

SWOT analysis   #gamestorming   #problem solving   #action   #meeting facilitation   The SWOT Analysis is a long-standing technique of looking at what we have, with respect to the desired end state, as well as what we could improve on. It gives us an opportunity to gauge approaching opportunities and dangers, and assess the seriousness of the conditions that affect our future. When we understand those conditions, we can influence what comes next.

14. Agreement-Certainty Matrix

Not every problem-solving approach is right for every challenge, and deciding on the right method for the challenge at hand is a key part of being an effective team.

The Agreement Certainty matrix helps teams align on the nature of the challenges facing them. By sorting problems from simple to chaotic, your team can understand what methods are suitable for each problem and what they can do to ensure effective results. 

If you are already using Liberating Structures techniques as part of your problem-solving strategy, the Agreement-Certainty Matrix can be an invaluable addition to your process. We’ve found it particularly if you are having issues with recurring problems in your organization and want to go deeper in understanding the root cause. 

Agreement-Certainty Matrix   #issue analysis   #liberating structures   #problem solving   You can help individuals or groups avoid the frequent mistake of trying to solve a problem with methods that are not adapted to the nature of their challenge. The combination of two questions makes it possible to easily sort challenges into four categories: simple, complicated, complex , and chaotic .  A problem is simple when it can be solved reliably with practices that are easy to duplicate.  It is complicated when experts are required to devise a sophisticated solution that will yield the desired results predictably.  A problem is complex when there are several valid ways to proceed but outcomes are not predictable in detail.  Chaotic is when the context is too turbulent to identify a path forward.  A loose analogy may be used to describe these differences: simple is like following a recipe, complicated like sending a rocket to the moon, complex like raising a child, and chaotic is like the game “Pin the Tail on the Donkey.”  The Liberating Structures Matching Matrix in Chapter 5 can be used as the first step to clarify the nature of a challenge and avoid the mismatches between problems and solutions that are frequently at the root of chronic, recurring problems.

Organizing and charting a team’s progress can be important in ensuring its success. SQUID (Sequential Question and Insight Diagram) is a great model that allows a team to effectively switch between giving questions and answers and develop the skills they need to stay on track throughout the process. 

Begin with two different colored sticky notes – one for questions and one for answers – and with your central topic (the head of the squid) on the board. Ask the group to first come up with a series of questions connected to their best guess of how to approach the topic. Ask the group to come up with answers to those questions, fix them to the board and connect them with a line. After some discussion, go back to question mode by responding to the generated answers or other points on the board.

It’s rewarding to see a diagram grow throughout the exercise, and a completed SQUID can provide a visual resource for future effort and as an example for other teams.

SQUID   #gamestorming   #project planning   #issue analysis   #problem solving   When exploring an information space, it’s important for a group to know where they are at any given time. By using SQUID, a group charts out the territory as they go and can navigate accordingly. SQUID stands for Sequential Question and Insight Diagram.

16. Speed Boat

To continue with our nautical theme, Speed Boat is a short and sweet activity that can help a team quickly identify what employees, clients or service users might have a problem with and analyze what might be standing in the way of achieving a solution.

Methods that allow for a group to make observations, have insights and obtain those eureka moments quickly are invaluable when trying to solve complex problems.

In Speed Boat, the approach is to first consider what anchors and challenges might be holding an organization (or boat) back. Bonus points if you are able to identify any sharks in the water and develop ideas that can also deal with competitors!   

Speed Boat   #gamestorming   #problem solving   #action   Speedboat is a short and sweet way to identify what your employees or clients don’t like about your product/service or what’s standing in the way of a desired goal.

17. The Journalistic Six

Some of the most effective ways of solving problems is by encouraging teams to be more inclusive and diverse in their thinking.

Based on the six key questions journalism students are taught to answer in articles and news stories, The Journalistic Six helps create teams to see the whole picture. By using who, what, when, where, why, and how to facilitate the conversation and encourage creative thinking, your team can make sure that the problem identification and problem analysis stages of the are covered exhaustively and thoughtfully. Reporter’s notebook and dictaphone optional.

The Journalistic Six – Who What When Where Why How   #idea generation   #issue analysis   #problem solving   #online   #creative thinking   #remote-friendly   A questioning method for generating, explaining, investigating ideas.

18. LEGO Challenge

Now for an activity that is a little out of the (toy) box. LEGO Serious Play is a facilitation methodology that can be used to improve creative thinking and problem-solving skills. 

The LEGO Challenge includes giving each member of the team an assignment that is hidden from the rest of the group while they create a structure without speaking.

What the LEGO challenge brings to the table is a fun working example of working with stakeholders who might not be on the same page to solve problems. Also, it’s LEGO! Who doesn’t love LEGO! 

LEGO Challenge   #hyperisland   #team   A team-building activity in which groups must work together to build a structure out of LEGO, but each individual has a secret “assignment” which makes the collaborative process more challenging. It emphasizes group communication, leadership dynamics, conflict, cooperation, patience and problem solving strategy.

19. What, So What, Now What?

If not carefully managed, the problem identification and problem analysis stages of the problem-solving process can actually create more problems and misunderstandings.

The What, So What, Now What? problem-solving activity is designed to help collect insights and move forward while also eliminating the possibility of disagreement when it comes to identifying, clarifying, and analyzing organizational or work problems. 

Facilitation is all about bringing groups together so that might work on a shared goal and the best problem-solving strategies ensure that teams are aligned in purpose, if not initially in opinion or insight.

Throughout the three steps of this game, you give everyone on a team to reflect on a problem by asking what happened, why it is important, and what actions should then be taken. 

This can be a great activity for bringing our individual perceptions about a problem or challenge and contextualizing it in a larger group setting. This is one of the most important problem-solving skills you can bring to your organization.

W³ – What, So What, Now What?   #issue analysis   #innovation   #liberating structures   You can help groups reflect on a shared experience in a way that builds understanding and spurs coordinated action while avoiding unproductive conflict. It is possible for every voice to be heard while simultaneously sifting for insights and shaping new direction. Progressing in stages makes this practical—from collecting facts about What Happened to making sense of these facts with So What and finally to what actions logically follow with Now What . The shared progression eliminates most of the misunderstandings that otherwise fuel disagreements about what to do. Voila!

20. Journalists  

Problem analysis can be one of the most important and decisive stages of all problem-solving tools. Sometimes, a team can become bogged down in the details and are unable to move forward.

Journalists is an activity that can avoid a group from getting stuck in the problem identification or problem analysis stages of the process.

In Journalists, the group is invited to draft the front page of a fictional newspaper and figure out what stories deserve to be on the cover and what headlines those stories will have. By reframing how your problems and challenges are approached, you can help a team move productively through the process and be better prepared for the steps to follow.

Journalists   #vision   #big picture   #issue analysis   #remote-friendly   This is an exercise to use when the group gets stuck in details and struggles to see the big picture. Also good for defining a vision.

Problem-solving techniques for developing solutions 

The success of any problem-solving process can be measured by the solutions it produces. After you’ve defined the issue, explored existing ideas, and ideated, it’s time to narrow down to the correct solution.

Use these problem-solving techniques when you want to help your team find consensus, compare possible solutions, and move towards taking action on a particular problem.

• Improved Solutions
• Four-Step Sketch
• 15% Solutions
• How-Now-Wow matrix
• Impact Effort Matrix

21. Mindspin  

Brainstorming is part of the bread and butter of the problem-solving process and all problem-solving strategies benefit from getting ideas out and challenging a team to generate solutions quickly. 

With Mindspin, participants are encouraged not only to generate ideas but to do so under time constraints and by slamming down cards and passing them on. By doing multiple rounds, your team can begin with a free generation of possible solutions before moving on to developing those solutions and encouraging further ideation. 

This is one of our favorite problem-solving activities and can be great for keeping the energy up throughout the workshop. Remember the importance of helping people become engaged in the process – energizing problem-solving techniques like Mindspin can help ensure your team stays engaged and happy, even when the problems they’re coming together to solve are complex. 

MindSpin   #teampedia   #idea generation   #problem solving   #action   A fast and loud method to enhance brainstorming within a team. Since this activity has more than round ideas that are repetitive can be ruled out leaving more creative and innovative answers to the challenge.

22. Improved Solutions

After a team has successfully identified a problem and come up with a few solutions, it can be tempting to call the work of the problem-solving process complete. That said, the first solution is not necessarily the best, and by including a further review and reflection activity into your problem-solving model, you can ensure your group reaches the best possible result. 

One of a number of problem-solving games from Thiagi Group, Improved Solutions helps you go the extra mile and develop suggested solutions with close consideration and peer review. By supporting the discussion of several problems at once and by shifting team roles throughout, this problem-solving technique is a dynamic way of finding the best solution. 

Improved Solutions   #creativity   #thiagi   #problem solving   #action   #team   You can improve any solution by objectively reviewing its strengths and weaknesses and making suitable adjustments. In this creativity framegame, you improve the solutions to several problems. To maintain objective detachment, you deal with a different problem during each of six rounds and assume different roles (problem owner, consultant, basher, booster, enhancer, and evaluator) during each round. At the conclusion of the activity, each player ends up with two solutions to her problem.

23. Four Step Sketch

Creative thinking and visual ideation does not need to be confined to the opening stages of your problem-solving strategies. Exercises that include sketching and prototyping on paper can be effective at the solution finding and development stage of the process, and can be great for keeping a team engaged. 

By going from simple notes to a crazy 8s round that involves rapidly sketching 8 variations on their ideas before then producing a final solution sketch, the group is able to iterate quickly and visually. Problem-solving techniques like Four-Step Sketch are great if you have a group of different thinkers and want to change things up from a more textual or discussion-based approach.

Four-Step Sketch   #design sprint   #innovation   #idea generation   #remote-friendly   The four-step sketch is an exercise that helps people to create well-formed concepts through a structured process that includes: Review key information Start design work on paper,  Consider multiple variations , Create a detailed solution . This exercise is preceded by a set of other activities allowing the group to clarify the challenge they want to solve. See how the Four Step Sketch exercise fits into a Design Sprint

24. 15% Solutions

Some problems are simpler than others and with the right problem-solving activities, you can empower people to take immediate actions that can help create organizational change. 

Part of the liberating structures toolkit, 15% solutions is a problem-solving technique that focuses on finding and implementing solutions quickly. A process of iterating and making small changes quickly can help generate momentum and an appetite for solving complex problems.

Problem-solving strategies can live and die on whether people are onboard. Getting some quick wins is a great way of getting people behind the process.   

It can be extremely empowering for a team to realize that problem-solving techniques can be deployed quickly and easily and delineate between things they can positively impact and those things they cannot change. 

15% Solutions   #action   #liberating structures   #remote-friendly   You can reveal the actions, however small, that everyone can do immediately. At a minimum, these will create momentum, and that may make a BIG difference.  15% Solutions show that there is no reason to wait around, feel powerless, or fearful. They help people pick it up a level. They get individuals and the group to focus on what is within their discretion instead of what they cannot change.  With a very simple question, you can flip the conversation to what can be done and find solutions to big problems that are often distributed widely in places not known in advance. Shifting a few grains of sand may trigger a landslide and change the whole landscape.

25. How-Now-Wow Matrix

The problem-solving process is often creative, as complex problems usually require a change of thinking and creative response in order to find the best solutions. While it’s common for the first stages to encourage creative thinking, groups can often gravitate to familiar solutions when it comes to the end of the process. 

When selecting solutions, you don’t want to lose your creative energy! The How-Now-Wow Matrix from Gamestorming is a great problem-solving activity that enables a group to stay creative and think out of the box when it comes to selecting the right solution for a given problem.

Problem-solving techniques that encourage creative thinking and the ideation and selection of new solutions can be the most effective in organisational change. Give the How-Now-Wow Matrix a go, and not just for how pleasant it is to say out loud. 

How-Now-Wow Matrix   #gamestorming   #idea generation   #remote-friendly   When people want to develop new ideas, they most often think out of the box in the brainstorming or divergent phase. However, when it comes to convergence, people often end up picking ideas that are most familiar to them. This is called a ‘creative paradox’ or a ‘creadox’. The How-Now-Wow matrix is an idea selection tool that breaks the creadox by forcing people to weigh each idea on 2 parameters.

26. Impact and Effort Matrix

All problem-solving techniques hope to not only find solutions to a given problem or challenge but to find the best solution. When it comes to finding a solution, groups are invited to put on their decision-making hats and really think about how a proposed idea would work in practice. 

The Impact and Effort Matrix is one of the problem-solving techniques that fall into this camp, empowering participants to first generate ideas and then categorize them into a 2×2 matrix based on impact and effort.

Activities that invite critical thinking while remaining simple are invaluable. Use the Impact and Effort Matrix to move from ideation and towards evaluating potential solutions before then committing to them. 

Impact and Effort Matrix   #gamestorming   #decision making   #action   #remote-friendly   In this decision-making exercise, possible actions are mapped based on two factors: effort required to implement and potential impact. Categorizing ideas along these lines is a useful technique in decision making, as it obliges contributors to balance and evaluate suggested actions before committing to them.

27. Dotmocracy

If you’ve followed each of the problem-solving steps with your group successfully, you should move towards the end of your process with heaps of possible solutions developed with a specific problem in mind. But how do you help a group go from ideation to putting a solution into action? 

Dotmocracy – or Dot Voting -is a tried and tested method of helping a team in the problem-solving process make decisions and put actions in place with a degree of oversight and consensus. 

One of the problem-solving techniques that should be in every facilitator’s toolbox, Dot Voting is fast and effective and can help identify the most popular and best solutions and help bring a group to a decision effectively. 

Dotmocracy   #action   #decision making   #group prioritization   #hyperisland   #remote-friendly   Dotmocracy is a simple method for group prioritization or decision-making. It is not an activity on its own, but a method to use in processes where prioritization or decision-making is the aim. The method supports a group to quickly see which options are most popular or relevant. The options or ideas are written on post-its and stuck up on a wall for the whole group to see. Each person votes for the options they think are the strongest, and that information is used to inform a decision.

All facilitators know that warm-ups and icebreakers are useful for any workshop or group process. Problem-solving workshops are no different.

Use these problem-solving techniques to warm up a group and prepare them for the rest of the process. Activating your group by tapping into some of the top problem-solving skills can be one of the best ways to see great outcomes from your session.

• Check-in/Check-out
• Doodling Together
• Show and Tell
• Constellations
• Draw a Tree

28. Check-in / Check-out

Solid processes are planned from beginning to end, and the best facilitators know that setting the tone and establishing a safe, open environment can be integral to a successful problem-solving process.

Check-in / Check-out is a great way to begin and/or bookend a problem-solving workshop. Checking in to a session emphasizes that everyone will be seen, heard, and expected to contribute. 

If you are running a series of meetings, setting a consistent pattern of checking in and checking out can really help your team get into a groove. We recommend this opening-closing activity for small to medium-sized groups though it can work with large groups if they’re disciplined!

Check-in / Check-out   #team   #opening   #closing   #hyperisland   #remote-friendly   Either checking-in or checking-out is a simple way for a team to open or close a process, symbolically and in a collaborative way. Checking-in/out invites each member in a group to be present, seen and heard, and to express a reflection or a feeling. Checking-in emphasizes presence, focus and group commitment; checking-out emphasizes reflection and symbolic closure.

29. Doodling Together  

Thinking creatively and not being afraid to make suggestions are important problem-solving skills for any group or team, and warming up by encouraging these behaviors is a great way to start. 

Doodling Together is one of our favorite creative ice breaker games – it’s quick, effective, and fun and can make all following problem-solving steps easier by encouraging a group to collaborate visually. By passing cards and adding additional items as they go, the workshop group gets into a groove of co-creation and idea development that is crucial to finding solutions to problems. 

Doodling Together   #collaboration   #creativity   #teamwork   #fun   #team   #visual methods   #energiser   #icebreaker   #remote-friendly   Create wild, weird and often funny postcards together & establish a group’s creative confidence.

30. Show and Tell

You might remember some version of Show and Tell from being a kid in school and it’s a great problem-solving activity to kick off a session.

Asking participants to prepare a little something before a workshop by bringing an object for show and tell can help them warm up before the session has even begun! Games that include a physical object can also help encourage early engagement before moving onto more big-picture thinking.

By asking your participants to tell stories about why they chose to bring a particular item to the group, you can help teams see things from new perspectives and see both differences and similarities in the way they approach a topic. Great groundwork for approaching a problem-solving process as a team! 

Show and Tell   #gamestorming   #action   #opening   #meeting facilitation   Show and Tell taps into the power of metaphors to reveal players’ underlying assumptions and associations around a topic The aim of the game is to get a deeper understanding of stakeholders’ perspectives on anything—a new project, an organizational restructuring, a shift in the company’s vision or team dynamic.

31. Constellations

Who doesn’t love stars? Constellations is a great warm-up activity for any workshop as it gets people up off their feet, energized, and ready to engage in new ways with established topics. It’s also great for showing existing beliefs, biases, and patterns that can come into play as part of your session.

Using warm-up games that help build trust and connection while also allowing for non-verbal responses can be great for easing people into the problem-solving process and encouraging engagement from everyone in the group. Constellations is great in large spaces that allow for movement and is definitely a practical exercise to allow the group to see patterns that are otherwise invisible. 

Constellations   #trust   #connection   #opening   #coaching   #patterns   #system   Individuals express their response to a statement or idea by standing closer or further from a central object. Used with teams to reveal system, hidden patterns, perspectives.

32. Draw a Tree

Problem-solving games that help raise group awareness through a central, unifying metaphor can be effective ways to warm-up a group in any problem-solving model.

Draw a Tree is a simple warm-up activity you can use in any group and which can provide a quick jolt of energy. Start by asking your participants to draw a tree in just 45 seconds – they can choose whether it will be abstract or realistic. 

Once the timer is up, ask the group how many people included the roots of the tree and use this as a means to discuss how we can ignore important parts of any system simply because they are not visible.

All problem-solving strategies are made more effective by thinking of problems critically and by exposing things that may not normally come to light. Warm-up games like Draw a Tree are great in that they quickly demonstrate some key problem-solving skills in an accessible and effective way.

Draw a Tree   #thiagi   #opening   #perspectives   #remote-friendly   With this game you can raise awarness about being more mindful, and aware of the environment we live in.

Each step of the problem-solving workshop benefits from an intelligent deployment of activities, games, and techniques. Bringing your session to an effective close helps ensure that solutions are followed through on and that you also celebrate what has been achieved.

Here are some problem-solving activities you can use to effectively close a workshop or meeting and ensure the great work you’ve done can continue afterward.

• One Breath Feedback
• Who What When Matrix
• Response Cards

How do I conclude a problem-solving process?

All good things must come to an end. With the bulk of the work done, it can be tempting to conclude your workshop swiftly and without a moment to debrief and align. This can be problematic in that it doesn’t allow your team to fully process the results or reflect on the process.

At the end of an effective session, your team will have gone through a process that, while productive, can be exhausting. It’s important to give your group a moment to take a breath, ensure that they are clear on future actions, and provide short feedback before leaving the space. 

The primary purpose of any problem-solving method is to generate solutions and then implement them. Be sure to take the opportunity to ensure everyone is aligned and ready to effectively implement the solutions you produced in the workshop.

Remember that every process can be improved and by giving a short moment to collect feedback in the session, you can further refine your problem-solving methods and see further success in the future too.

33. One Breath Feedback

Maintaining attention and focus during the closing stages of a problem-solving workshop can be tricky and so being concise when giving feedback can be important. It’s easy to incur “death by feedback” should some team members go on for too long sharing their perspectives in a quick feedback round. 

One Breath Feedback is a great closing activity for workshops. You give everyone an opportunity to provide feedback on what they’ve done but only in the space of a single breath. This keeps feedback short and to the point and means that everyone is encouraged to provide the most important piece of feedback to them. 

One breath feedback   #closing   #feedback   #action   This is a feedback round in just one breath that excels in maintaining attention: each participants is able to speak during just one breath … for most people that’s around 20 to 25 seconds … unless of course you’ve been a deep sea diver in which case you’ll be able to do it for longer.

34. Who What When Matrix 

Matrices feature as part of many effective problem-solving strategies and with good reason. They are easily recognizable, simple to use, and generate results.

The Who What When Matrix is a great tool to use when closing your problem-solving session by attributing a who, what and when to the actions and solutions you have decided upon. The resulting matrix is a simple, easy-to-follow way of ensuring your team can move forward. 

Great solutions can’t be enacted without action and ownership. Your problem-solving process should include a stage for allocating tasks to individuals or teams and creating a realistic timeframe for those solutions to be implemented or checked out. Use this method to keep the solution implementation process clear and simple for all involved. 

Who/What/When Matrix   #gamestorming   #action   #project planning   With Who/What/When matrix, you can connect people with clear actions they have defined and have committed to.

35. Response cards

Group discussion can comprise the bulk of most problem-solving activities and by the end of the process, you might find that your team is talked out! 

Providing a means for your team to give feedback with short written notes can ensure everyone is head and can contribute without the need to stand up and talk. Depending on the needs of the group, giving an alternative can help ensure everyone can contribute to your problem-solving model in the way that makes the most sense for them.

Response Cards is a great way to close a workshop if you are looking for a gentle warm-down and want to get some swift discussion around some of the feedback that is raised. 

Response Cards   #debriefing   #closing   #structured sharing   #questions and answers   #thiagi   #action   It can be hard to involve everyone during a closing of a session. Some might stay in the background or get unheard because of louder participants. However, with the use of Response Cards, everyone will be involved in providing feedback or clarify questions at the end of a session.

Save time and effort discovering the right solutions

A structured problem solving process is a surefire way of solving tough problems, discovering creative solutions and driving organizational change. But how can you design for successful outcomes?

With SessionLab, it’s easy to design engaging workshops that deliver results. Drag, drop and reorder blocks  to build your agenda. When you make changes or update your agenda, your session  timing   adjusts automatically , saving you time on manual adjustments.

Collaborating with stakeholders or clients? Share your agenda with a single click and collaborate in real-time. No more sending documents back and forth over email.

Explore  how to use SessionLab  to design effective problem solving workshops or  watch this five minute video  to see the planner in action!

Over to you

The problem-solving process can often be as complicated and multifaceted as the problems they are set-up to solve. With the right problem-solving techniques and a mix of creative exercises designed to guide discussion and generate purposeful ideas, we hope we’ve given you the tools to find the best solutions as simply and easily as possible.

Is there a problem-solving technique that you are missing here? Do you have a favorite activity or method you use when facilitating? Let us know in the comments below, we’d love to hear from you! 

thank you very much for these excellent techniques

Certainly wonderful article, very detailed. Shared!

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48 Problem Solving

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

• Published: 03 June 2013
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Problem solving refers to cognitive processing directed at achieving a goal when the problem solver does not initially know a solution method. A problem exists when someone has a goal but does not know how to achieve it. Problems can be classified as routine or nonroutine, and as well defined or ill defined. The major cognitive processes in problem solving are representing, planning, executing, and monitoring. The major kinds of knowledge required for problem solving are facts, concepts, procedures, strategies, and beliefs. Classic theoretical approaches to the study of problem solving are associationism, Gestalt, and information processing. Current issues and suggested future issues include decision making, intelligence and creativity, teaching of thinking skills, expert problem solving, analogical reasoning, mathematical and scientific thinking, everyday thinking, and the cognitive neuroscience of problem solving. Common themes concern the domain specificity of problem solving and a focus on problem solving in authentic contexts.

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

Definition of Problem Solving

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

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

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

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

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

Definition of Problem

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

Types of Problems

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

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

Cognitive Processes in Problem Solving

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

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

Knowledge for Problem Solving

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

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

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

Historical Approaches to Problem Solving

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

Early Conceptions

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

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

Associationism

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

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

Gestalt Psychology

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

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

Information Processing

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

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

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

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

Classic Issues in Problem Solving

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

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

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

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

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

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

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

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

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

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

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

Current and Future Issues in Problem Solving

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

Decision Making

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

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

Intelligence and Creativity

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

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

Teaching of Thinking Skills

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

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

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

Expert Problem Solving

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

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

Analogical Reasoning

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

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

Mathematical and Scientific Problem Solving

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

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

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

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

Everyday Thinking

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

Cognitive Neuroscience of Problem Solving

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

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

Future Directions

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

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Further Reading

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

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

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

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

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

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

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Problem solving techniques: Steps and methods

Posted on May 29, 2019

Constant disruption has become a hallmark of the modern workforce and organisations want problem solving skills to combat this. Employers need people who can respond to change – be that evolving technology, new competitors, different models for doing business, or any of the other transformations that have taken place in recent years.

In addition, problem solving techniques encompass many of the other top skills employers seek . For example, LinkedIn’s list of the most in-demand soft skills of 2019 includes creativity, collaboration and adaptability, all of which fall under the problem-solving umbrella.

Despite its importance, many employees misunderstand what the problem solving method really involves.

What constitutes effective problem solving?

Effective problem solving doesn’t mean going away and coming up with an answer immediately. In fact, this isn’t good problem solving at all, because you’ll be running with the first solution that comes into your mind, which often isn’t the best.

Instead, you should look at problem solving more as a process with several steps involved that will help you reach the best outcome. Those steps are:

• Define the problem
• List all the possible solutions
• Evaluate the options
• Select the best solution
• Create an implementation plan
• Communicate your solution

Let’s look at each step in a little more detail.

1. Define the problem

The first step to solving a problem is defining what the problem actually is – sounds simple, right? Well no. An effective problem solver will take the thoughts of everyone involved into account, but different people might have different ideas on what the root cause of the issue really is. It’s up to you to actively listen to everyone without bringing any of your own preconceived notions to the conversation. Learning to differentiate facts from opinion is an essential part of this process.

An effective problem solver will take the opinions of everyone involved into account

The same can be said of data. Depending on what the problem is, there will be varying amounts of information available that will help you work out what’s gone wrong. There should be at least some data involved in any problem, and it’s up to you to gather as much as possible and analyse it objectively.

2. List all the possible solutions

Once you’ve identified what the real issue is, it’s time to think of solutions. Brainstorming as many solutions as possible will help you arrive at the best answer because you’ll be considering all potential options and scenarios. You should take everyone’s thoughts into account when you’re brainstorming these ideas, as well as all the insights you’ve gleaned from your data analysis. It also helps to seek input from others at this stage, as they may come up with solutions you haven’t thought of.

Depending on the type of problem, it can be useful to think of both short-term and long-term solutions, as some of your options may take a while to implement.

3. Evaluate the options

Each option will have pros and cons, and it’s important you list all of these, as well as how each solution could impact key stakeholders. Once you’ve narrowed down your options to three or four, it’s often a good idea to go to other employees for feedback just in case you’ve missed something. You should also work out how each option ties in with the broader goals of the business.

There may be a way to merge two options together in order to satisfy more people.

4. Select an option

Only now should you choose which solution you’re going to go with. What you decide should be whatever solves the problem most effectively while also taking the interests of everyone involved into account. There may be a way to merge two options together in order to satisfy more people.

5. Create an implementation plan

At this point you might be thinking it’s time to sit back and relax – problem solved, right? There are actually two more steps involved if you want your problem solving method to be truly effective. The first is to create an implementation plan. After all, if you don’t carry out your solution effectively, you’re not really solving the problem at all. 

Create an implementation plan on how you will put your solution into practice. One problem solving technique that many use here is to introduce a testing and feedback phase just to make sure the option you’ve selected really is the most viable. You’ll also want to include any changes to your solution that may occur in your implementation plan, as well as how you’ll monitor compliance and success.

6. Communicate your solution

There’s one last step to consider as part of the problem solving methodology, and that’s communicating your solution . Without this crucial part of the process, how is anyone going to know what you’ve decided? Make sure you communicate your decision to all the people who might be impacted by it. Not everyone is going to be 100 per cent happy with it, so when you communicate you must give them context. Explain exactly why you’ve made that decision and how the pros mean it’s better than any of the other options you came up with.

Prove your problem solving skills with Deakin

Employers are increasingly seeking soft skills, but unfortunately, while you can show that you’ve got a degree in a subject, it’s much harder to prove you’ve got proficiency in things like problem solving skills. But this is changing thanks to Deakin’s micro-credentials. These are university-level micro-credentials that provide an authoritative and third-party assessment of your capabilities in a range of areas, including problem solving. Reach out today for more information .

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The Problem-Solving Process

Looking at the basic problem-solving process to help keep you on the right track.

By the Mind Tools Content Team

Problem-solving is an important part of planning and decision-making. The process has much in common with the decision-making process, and in the case of complex decisions, can form part of the process itself.

We face and solve problems every day, in a variety of guises and of differing complexity. Some, such as the resolution of a serious complaint, require a significant amount of time, thought and investigation. Others, such as a printer running out of paper, are so quickly resolved they barely register as a problem at all.

Despite the everyday occurrence of problems, many people lack confidence when it comes to solving them, and as a result may chose to stay with the status quo rather than tackle the issue. Broken down into steps, however, the problem-solving process is very simple. While there are many tools and techniques available to help us solve problems, the outline process remains the same.

The main stages of problem-solving are outlined below, though not all are required for every problem that needs to be solved.

1. Define the Problem

Clarify the problem before trying to solve it. A common mistake with problem-solving is to react to what the problem appears to be, rather than what it actually is. Write down a simple statement of the problem, and then underline the key words. Be certain there are no hidden assumptions in the key words you have underlined. One way of doing this is to use a synonym to replace the key words. For example, ‘We need to encourage higher productivity ’ might become ‘We need to promote superior output ’ which has a different meaning.

2. Analyze the Problem

Ask yourself, and others, the following questions.

• Where is the problem occurring?
• When is it occurring?
• Why is it happening?

Be careful not to jump to ‘who is causing the problem?’. When stressed and faced with a problem it is all too easy to assign blame. This, however, can cause negative feeling and does not help to solve the problem. As an example, if an employee is underperforming, the root of the problem might lie in a number of areas, such as lack of training, workplace bullying or management style. To assign immediate blame to the employee would not therefore resolve the underlying issue.

Once the answers to the where, when and why have been determined, the following questions should also be asked:

• Where can further information be found?
• Is this information correct, up-to-date and unbiased?
• What does this information mean in terms of the available options?

3. Generate Potential Solutions

When generating potential solutions it can be a good idea to have a mixture of ‘right brain’ and ‘left brain’ thinkers. In other words, some people who think laterally and some who think logically. This provides a balance in terms of generating the widest possible variety of solutions while also being realistic about what can be achieved. There are many tools and techniques which can help produce solutions, including thinking about the problem from a number of different perspectives, and brainstorming, where a team or individual write as many possibilities as they can think of to encourage lateral thinking and generate a broad range of potential solutions.

4. Select Best Solution

When selecting the best solution, consider:

• Is this a long-term solution, or a ‘quick fix’?
• Is the solution achievable in terms of available resources and time?
• Are there any risks associated with the chosen solution?
• Could the solution, in itself, lead to other problems?

This stage in particular demonstrates why problem-solving and decision-making are so closely related.

5. Take Action

In order to implement the chosen solution effectively, consider the following:

• What will the situation look like when the problem is resolved?
• What needs to be done to implement the solution? Are there systems or processes that need to be adjusted?
• What will be the success indicators?
• What are the timescales for the implementation? Does the scale of the problem/implementation require a project plan?
• Who is responsible?

Once the answers to all the above questions are written down, they can form the basis of an action plan.

6. Monitor and Review

One of the most important factors in successful problem-solving is continual observation and feedback. Use the success indicators in the action plan to monitor progress on a regular basis. Is everything as expected? Is everything on schedule? Keep an eye on priorities and timelines to prevent them from slipping.

If the indicators are not being met, or if timescales are slipping, consider what can be done. Was the plan realistic? If so, are sufficient resources being made available? Are these resources targeting the correct part of the plan? Or does the plan need to be amended? Regular review and discussion of the action plan is important so small adjustments can be made on a regular basis to help keep everything on track.

Once all the indicators have been met and the problem has been resolved, consider what steps can now be taken to prevent this type of problem recurring? It may be that the chosen solution already prevents a recurrence, however if an interim or partial solution has been chosen it is important not to lose momentum.

Problems, by their very nature, will not always fit neatly into a structured problem-solving process. This process, therefore, is designed as a framework which can be adapted to individual needs and nature.

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• Open access
• Published: 12 November 2021

Interleaved practice enhances memory and problem-solving ability in undergraduate physics

• Joshua Samani   ORCID: orcid.org/0000-0001-8774-6646 1 &
• Steven C. Pan   ORCID: orcid.org/0000-0001-9080-5651 2  

npj Science of Learning volume  6 , Article number:  32 ( 2021 ) Cite this article

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• Human behaviour

We investigated whether continuously alternating between topics during practice, or interleaved practice, improves memory and the ability to solve problems in undergraduate physics. Over 8 weeks, students in two lecture sections of a university-level introductory physics course completed thrice-weekly homework assignments, each containing problems that were interleaved (i.e., alternating topics) or conventionally arranged (i.e., one topic practiced at a time). On two surprise criterial tests containing novel and more challenging problems, students recalled more relevant information and more frequently produced correct solutions after having engaged in interleaved practice (with observed median improvements of 50% on test 1 and 125% on test 2). Despite benefiting more from interleaved practice, students tended to rate the technique as more difficult and incorrectly believed that they learned less from it. Thus, in a domain that entails considerable amounts of problem-solving, replacing conventionally arranged with interleaved homework can (despite perceptions to the contrary) foster longer lasting and more generalizable learning.

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Introduction

In virtually all learning domains, different topics or skills need to be mastered. Examples include derivatives and integrals in calculus, body systems in physiology, and the forehand, backhand, and serve in tennis. An intuitive approach to achieving mastery in such cases is to focus on learning one topic or skill at a time, which cognitive scientists refer to as blocking or massing (e.g., given concepts A, B, and C, studying three examples of each concept according to an “A 1 A 2 A 3 B 1 B 2 B 3 C 1 C 2 C 3 ” schedule). Blocking is ubiquitous throughout education, including in mathematics, science, and language curricula 1 , 2 , 3 . Its use is consistent with the common assumptions that human beings learn best when topics are introduced in isolation 4 , the learning of concepts is facilitated by exposure to successive examples of the same concept 5 , and that repetition practice fosters the development of expertize 6 (although there are varying perspectives as to the veracity of these assumptions). In contrast, researchers have recently begun investigating an alternative approach known as interleaved practice (henceforth, interleaving ). Interleaving involves switching between topics (or skills, concepts, categories, etc.) during learning (e.g., studying concepts A, B, and C using an “A 1 B 1 C 1 A 2 B 2 C 2 A 3 B 3 C 3 ” schedule) 7 . Consequently, to-be-learned materials are learned in juxtaposition to one another, rather than one at a time. Interleaving may improve attention 8 , induce memory retrieval processes 9 , prompt mental comparison processes 10 , foster relational processing 3 , and simulate the unpredictability of real-world situations 9 , all of which may be beneficial for learning. However, the benefits of interleaving have not yet been extensively explored in authentic educational contexts 11 , and the technique is not generally well known as an effective learning technique among students or instructors 9 . Hence, interleaving is currently rarely used in pedagogical settings 1 , 2 , 3 .

To date, most research on interleaving involves laboratory studies wherein perceptual categories such as artists’ painting styles 12 , 13 , 14 , biological taxonomic classifications 15 , 16 , 17 , or artificial shapes 18 , 19 , 20 are learned. In these studies, example images of to-be-learned categories are studied in blocked or interleaved fashion, followed by a classification test wherein new images that were drawn from the previously learned categories are shown. Typically, categories that were interleaved are classified more accurately than categories that were blocked 7 , 20 . A recent meta-analysis found that the typical benefit of interleaving for perceptual category learning is Hedges’ g (effect size) = 0.67, 95% confidence interval (CI) [0.57, 0.77] for artists’ paintings and g  = 0.31, 95% CI [0.17, 0.54] for artificial shapes 8 . The largest interleaving benefits have usually been observed for groups of categories that are perceptually similar (e.g., evolutionarily-related bird families), which implies that interleaving is more effective when to-be-learned materials are confusable with one another 8 , 21 . Mechanistically, benefits of interleaving for perceptual category learning have been attributed to the temporal spacing between category exemplars that occurs during such interleaving, which constitutes a form of distributed practice (which over a century of research has established can improve memory 22 ), as well as learners’ attention being focused on differences between categories (i.e., the attention bias and discriminative contrast framework, wherein interleaving-induced focused attention may yield improvements in the ability to discriminate between perceptually similar categories) 12 , 13 , 23 , 24 .

Based on the aforementioned research, recent reviews have defined the “interleaving effect” as improved inductive learning — that is, the mental process of acquiring conceptual knowledge from the study of exemplars—that stems from interleaving exemplars of visual or other perceptual categories 8 , 11 , 25 . A question left largely unanswered, however, is whether the interleaving effect extends beyond inductive learning tasks wherein the only determination of category membership is needed. In particular, it has yet to be fully established (a) whether interleaving enhances memory for to-be-learned facts as opposed to perceptual categories, (b) whether interleaving is effective for tasks that require substantial problem-solving, and (c) whether interleaving is effective in authentic educational settings and across extended time intervals 3 , 9 , 21 . These questions pertain to many contexts wherein interleaving could be used. As one example, an instructor might choose to interleave a series of different homework problems that require factual knowledge and the execution of stepwise procedures. Initial efforts to address these questions have involved interleaving in such domains as mathematics 21 , 26 , 27 , second language instruction 2 , 28 , 29 , and other areas 30 .

Thus far, the emerging literature on such uses of interleaving has yielded promising results and especially in the domain of middle-school mathematics. For example, in a 2014 classroom study, the use of interleaved homework assignments to practice algebra and graphing problems (e.g., solving for x in an equation; graphing an equation in the form of y  =  mx  +  b ) yielded subsequent surprise test performance that was nearly double that relative to a condition using blocked homework assignments 21 . Such benefits occurred even for materials that were not necessarily confusable with one another (as featured in most studies of interleaving and perceptual category learning). Even more impressively, a recent randomized controlled trial of interleaved algebra and graphing homework assignments in 54 classrooms (constituting the largest-ever investigation of interleaving to date) reported improvements of Cohen’s d (effect size) = 0.83, 95% CI [0.68, 0.97] on surprise delayed tests 31 . These and other results 27 , 32 , 33 raise the prospect that the interleaving effect encompasses more than inductive learning, with potentially broad implications for theories of learning, skill acquisition, and curriculum design.

To further explore the different types of learning that interleaving may promote, the present study examined the effects of interleaving on factual knowledge and problem-solving ability in a previously unexplored domain, namely undergraduate physics. Physics is one of the most popular academic subjects (in the United States alone, ~350,000 undergraduate students take introductory physics courses and over 280,000 high school students take Advanced Placement Physics exams each year) 34 , 35 . Physics is required not just for physics majors, but also for aspiring professionals in such fields as engineering, medicine, and other areas. Due to the extensive problem-solving skills that are needed, physics is a difficult subject to master, and owing to that difficulty, physics test scores are often among the lowest of all science subjects 34 (which can cause students to abandon the pursuit of science, technology, engineering, and math (STEM) careers) 36 . Accordingly, there is a pressing need to develop and investigate learning techniques that can be highly effective in physics courses.

The present study addressed that need by conducting a real-world, reasonably well-controlled test of interleaving in undergraduate physics. This test took the form of a preregistered experiment in two large lecture sections of an introductory-level undergraduate physics course (“Physics for Life Science Majors”) at a major US public university. The experiment spanned the first 8 weeks of the 10-week course, during which conventionally blocked homework assignments (wherein, only one problem type is practiced at a time) were replaced with interleaved assignments (involving switching between problem types). Importantly, rather than constructing or selecting materials specifically for research purposes, only the arrangement of homework problems during the course of normal instruction was manipulated and no other aspects of the course were altered. Hence, this test of interleaving occurred in an otherwise “business-as-usual” learning environment, which should increase confidence in its generalizability to real-world settings.

Across both lecture sections, 350 students participated in a counterbalanced, within-subjects design. During weeks 1–4 (Stage 1), students in the first and second sections (henceforth, Lecture 1 and Lecture 2) received blocked and interleaved homework assignments, respectively, whereas during weeks 5–8 (Stage 2), the assignment types were reversed (see Fig. 1 ). In other words, Lecture 1 students experienced blocking during Stage 1 and interleaving during Stage 2, whereas Lecture 2 students experienced the reverse. This arrangement ensured that each student in each section ultimately experienced both practice types.

In each of the two stages of the course, students completed 84 practice problems across 10 homework assignments. Blocked assignments typically featured three successive problems for each of three topics, whereas interleaved assignments typically featured only one problem per topic. In the figure, letters represent topics and subscripts represent the problem number for a given topic (1, 2, or 3). Different topics are also assigned different colors so that it is easier to visually tell them apart. Reflecting the relative simplicity of practicing one topic at a time, topics in each row of the blocked condition correspond perfectly to the assignment subject labeling that row, but this is not the case for the interleaved condition. Topics addressed on the criterial tests are also listed. Due to course time constraints, the last two blocked assignments of each stage include only two problems per topic instead of three. Topics from these assignments were not included in criterial tests.

During the course, each of the three weekly lectures was accompanied by a homework assignment. With blocked assignments, each topic was repeatedly practiced in succession with no intervening topics, whereas with interleaved assignments, each successive problem involved a change in the topic (for a list of topics, see Table 1 ). Of the nine problems per assignment, blocked assignments had three successive isomorphic problems per topic (i.e., having the same underlying problem-solving structure with contrasting surface features), which resembles the arrangement of practice exercises that occurs in many educational contexts 1 , whereas interleaved assignments had only one problem per topic, thus requiring students to engage in switching between topics (with the second and third problems per topic appearing on subsequent assignments). Crucially, within each stage, all students completed the same 84 total problems, with only the arrangement of those problems differing.

To measure the potential effects of interleaving, we administered an in-class surprise criterial test at the conclusion of each stage. These tests followed the approach taken in recent studies of interleaving and mathematics 31 , 33 and avoided contaminating effects of cramming, study group activities, and other events that can occur with increasing frequency in the period leading up to pre-announced exams. Both tests featured three novel problems that were more difficult than those included in the homework assignments. The first two problems required integrating concepts and procedures from two separate topics, whereas the third problem required applying a single topic in a new scenario. All three problems required recall and application of factual content conveyed in formulas (see Fig. 1 ). To derive answers, students had to correctly recognize the topics involved, all of which were last encountered more than 1 week prior; recall relevant formulas, rules, and principles; and in two of three problems, integrate and apply that information to devise a new solution strategy 37 (which could be viewed as requiring higher-order reasoning, integration, and constructive thought processes as opposed to simply recalling and repeating previously learned information) 38 , 39 .

As an example, one criterial test problem required recognizing the relevance of both Faraday’s Law and torque on a current loop in a magnetic field, recalling corresponding relevant formulas, and combining them in a novel way to compute the torque on a current loop in the magnetic field of an magnetic resonance imaging machine. Importantly, this combination of problem-solving processes was not included in any of the homework assignments and had not been specifically taught in the course. This type of problem also differed from the isomorphic problems commonly used in prior research on interleaving and problem-solving skills 26 , 31 , 32 , 33 , 40 .

How did students perform on interleaved versus blocked homework assignments—and how did they perceive both practice types?

Across both lecture sections, 290 students in stage 1 (83% of the total enrolled) and 286 students in Stage 2 (82% of total enrolled) experienced the experimental manipulation in its entirety by completing and turning in all of the homework assignments. Per our preregistered inclusion criteria, only data from those students were analyzed. Although that analysis revealed disparities between interleaving and blocking in terms of student performance, judgments of difficulty, and judgments of pedagogical effectiveness, there was no advance indication of any interleaving benefit.

With respect to overall performance, students correctly solved more blocked than interleaved homework problems (Table 2 ), with a mean deficit on interleaved assignments of 0.05 and 0.09 proportion correct in Stages 1 and 2, respectively. When interpreting these results, it is important to consider that there were nine different problem types on most interleaved assignments, with each type requiring a different problem-solving strategy, whereas, with most blocked assignments, there were only three problem types. Hence, the expectation that the blocked assignments would be easier was confirmed by student performance.

When asked at the end of each assignment to make metacognitive judgments—that is, to evaluate their own process of learning—students tended to rate interleaved assignments as more challenging and yielding less mastery (Table 2 ). For both practice types, the largest proportion of students’ judgments of difficulty spanned from the “medium” to “difficult” categories, but a higher proportion of those ratings occurred at the conclusion of interleaved assignments. Correspondingly, for both practice types, the largest proportion of students’ judgments of learning spanned from “well” to “extremely well,” but a higher proportion of those ratings occurred at the conclusion of blocked assignments. Thus, on interleaved assignments, students performed more poorly, experienced greater difficulty, and perceived fewer learning benefits. On the basis of these findings, one might predict that student performance on a delayed test of the practiced topics would suffer.

How did interleaving and blocking affect learning as measured on the criterial tests?

Belying the patterns observed on the homework assignments, however, students who had completed interleaved assignments well outperformed those who had completed blocked assignments on the surprise criterial tests. Interleaving yielded higher criterial test scores than blocking in Stage 1, d  = 0.40, 95% CI [0.17, 0.65], t (288) = 3.41, p  = 0.0008, and in Stage 2, d  = 0.91, 95% CI [0.66, 1.20], t (284) = 7.68, p  < 0.0001. Thus, interleaving improved the ability to correctly recall and use prior knowledge in an attempt to generate solutions to novel problems. Inspection of the full distributions of test scores further confirms the occurrence of strong interleaving benefits (see Fig. 2 ). Specifically, interleaving improved median test scores over-blocking by 50% and 125% in Stages 1 and 2, respectively (i.e., interleaving improved learning across both halves of the course and in both counterbalanced groups). In Stage 2, when students had twice as much course content to draw upon (including topics that were arguably more difficult than those that were presented during Stage 1), the effect size of the interleaving advantage was larger.

Each histogram displays the distributions of criterial test scores in a given stage, with green representing performance in the interleaved condition and purple representing performance in the blocked condition. The median score in each condition is included as a vertical bar of the corresponding color. Histograms are normalized so that in each condition, the sums of values of all bins equals 1. Mean performance in Stages 1 and 2, respectively, was 0.43 and 0.27 in the blocked condition and 0.54 and 0.47 in the interleaved condition.

For additional insights into the effects of interleaving, we examined two distinct sub-measures of test performance: (a) whether students were able to correctly recall necessary formulas, which relies on long-term memory, and (b) whether students’ solution strategies yielded an exact match to the correct answer both in numerical value and in units, which is a more stringent measure of problem-solving ability (as it necessitated devising a multi-step problem-solving strategy and executing its associated computations without making a single error). It should be noted, however, that producing precisely correct answers is uncommon in many introductory-level physics courses due to the inherent conceptual difficulty and computational complexity of the material; in line with that expectation, the mean rate of correct answers, across both conditions, was no >0.34 proportion correct. Sub-measure analyses revealed that interleaving improved long-term memory in Stage 1, d  = 0.41, 95% CI [0.17, 0.66], t (288) = 3.49, p  = 0.006, and in Stage 2, d  = 0.96, 95% CI [0.70, 1.24], t (284) = 8.05, p  < 0.0001. Further, interleaving improved the correctness of answers in Stage 1, d  = 0.25, 95% CI [0.02, 0.48], t (288) = 2.17, p  = 0.0311, and in Stage 2, d  = 0.40, 95% CI [0.16, 0.64], t (284) = 3.32, p  = 0.0010. Thus, interleaving enhanced both memory and problem-solving accuracy.

Results at the level of individual problems (Table 3 ) also showed the advantages of interleaving. These advantages were the most consistent (i.e., across both sub-measures) for the easiest problem in each stage (which addressed one as opposed to two topics). Overall, interleaving yielded at least a numerical advantage on both sub-measures for all three problems on both criterial tests.

How did interleaving and blocking affect learning and study behaviors in the remainder of the course?

On high-stakes midterm exams occurring 3 days after each criterial test, scores did not significantly differ between the blocked and interleaved conditions (post-Stage 1 midterm, d  = 0.20, 95% CI [−0.04, 0.43], t (288) = 1.68, p  = 0.0944), and post-Stage 2 midterm, d  = 0.02, 95% CI [−0.21, 0.25], t (284) = 0.16, p  = 0.8758). Only in Stage 1 was there a hint of an interleaving benefit on the high-stakes exams (as most students did not complete the final exam due to a pandemic-induced campus closure, that exam was not analyzed). Although these patterns suggest a possible limitation on the efficacy of interleaving, there were factors that called into question the diagnosticity of the midterm exams, and these factors led us to include surprise criterial tests as our primary outcome measures. Specifically, exit surveys confirmed that most students engaged in extensive cramming prior to the midterms, but not before the criterial tests (Table 4 ). Further, the criterial tests were a potentially powerful learning event that previewed the problem format and scope on the midterms and likely influenced students’ study behaviors. These observations are consistent with the fact that the mean proportion correct on midterms (0.74) was high compared with the criterial tests (0.42). Thus, although the benefits of interleaving were not detected on midterm exams, any such benefits may have been occluded by cramming and practice testing.

With respect to the potential effects of interleaving and blocking on study behaviors, there were no significant self-reported study time differences between the two conditions (Table 3 ). Rather, the most common pattern across both conditions involved minimal studying prior to the criterial test (≤3 h over 4 weeks) and intense studying between the criterial tests and midterms (≥10 h over 3 days). Such cramming is almost universal among student study behaviors 41 . These patterns suggest that the benefits of interleaving on the criterial tests cannot be attributed to interleaving-induced changes in the volume of studying, but rather to qualitative changes in the learning that occurred during the completion of the homework assignments.

The present results reveal that interleaving can indeed enhance memory and problem-solving ability in the domain of undergraduate physics. Specifically, the use of homework assignments wherein problem types were interleaved, as opposed to conventionally blocked, generated learning improvements on two surprise criterial tests that were comprised of novel and more challenging problems. Such improvements were, in effect size terms, relatively large compared with other pedagogical techniques 42 , 43 (despite some variation across stages and across problems) and comparable to interleaving-induced improvements in such domains as middle-school mathematics 31 , 33 and second language learning 2 , 28 . Further, learning benefits were observed (a) for the case of long-term memory for factual content, (b) for the correctness of answers, (c) after retention intervals of at least one to several weeks, and (d) on surprise criterial tests but not on subsequent high-stakes exams. From the perspective of the literature on interleaving and related techniques (e.g., variability during practice) 44 , 45 , 46 , the present results bolster the conclusion that the benefits of alternating between topics or skills during learning extend well beyond the ability to classify perceptual category exemplars; these benefits can also encompass certain problem-solving skills. Moreover, the present results suggest that the avoidance of supposed preconditions for effective learning—including learning topics in isolation 4 , successive exposures to the same concept 5 , and single-session repetition practice 9 —may not be detrimental for learning. Rather, in line with pedagogical perspectives that encourage variability of practice 1 , 2 , violating those preconditions may in fact enhance learning. That tentative conclusion may validate the practices of instructors that already incorporate some form of interleaving in their homework assignments, but may not necessarily be aware of it as an evidence-supported learning technique.

Several theoretical mechanisms may account for the observed benefits of interleaving. Here, we summarize five candidates. These explanatory accounts are not necessarily mutually exclusive and have been largely drawn from the literature on interleaving, with some adaptations to problem-solving in introductory physics.

First, interleaving may have facilitated inductive learning of problem categories defined by specific physical concepts or principles. These categories, whose correct identification was necessary to solve criterial test problems, are often easily confusable to novice physics learners, who tend to base their problem representations on literal features instead of abstract principles 47 . The course progressed in a hierarchical manner whereby problems across topics commonly shared literal features, but problem classification was never explicitly discussed; hence, any inductive learning of problem categories would most likely have occurred during practice on homework sets. As has been repeatedly demonstrated in the literature (e.g., the attention bias and discriminative contrast framework), inductive learning of confusable perceptual categories is a context wherein interleaving can excel relative to blocking 12 , 13 , 23 , 24 . It is plausible that the interleaved homework sets, which provided more opportunities to compare non-isomorphic problem categories than the blocked homework sets, yielded similar benefits. However, it is important to note that the criterial tests required additional problem-solving steps, including memory retrieval of formulas. As such, inductive learning of problem categories alone might not be sufficient to explain the observed results.

Second, as previously noted, interleaving incorporates distributed practice (i.e., learning spread out over multiple sessions), which is known to improve long-term memory 10 . According to the study-phase retrieval account of the spacing effect, distributed practice during homework sets may have forced students to engage in repeated long-term memory retrieval processes, which are known to enhance the durability and accessibility of memories 3 . In contrast, with blocking, every successive set of three homework problems involved the same topic, thus allowing students to bypass memory retrieval in favor of knowledge temporarily held in working memory (i.e., repeatedly reusing the same solutions). Hence, productive memory retrieval processes may have been attenuated in the blocked condition, potentially reducing the rate of successfully recalling correct formulas on criterial tests, even in the case that the problem solver had achieved a correct conceptual classification of the problem. Other cognitive processes that distributed practice may engage, such as increased encoding of varied contextual cues, may have also had a facilitative effect on learning 48 .

Relatedly, there is evidence in the interleaving literature to support both minimal and major roles of distributed practice depending on the learning context. In the case of perceptual category learning, conditions that feature extensive amounts of distributed practice in the absence of interleaving have failed to yield similar learning benefits 13 , 15 , which suggests a minimal role, whereas, in studies involving mathematics or second language learning, interleaving schedules that incorporate substantial amounts of distributed practice have yielded larger benefits, which suggests a major role 2 , 24 . It is important to note, however, that differences in experimental and task design across studies may have also been factors.

A third explanation involves reduced lag-to-test—that is, elapsed time from practice to assessment—in the interleaved versus blocked conditions. In the present study, each interleaved topic was practiced across a 1-week period following its introduction, whereas each blocked topic was practiced only shortly after its introduction. The interleaved condition, therefore, had more recent exposure (by up to 1 week) on at least one topic per problem at the time of the criterial test, although the lags in both conditions were still at least 1–3 weeks long. It should be noted, however, that having students review to-be-tested topics shortly before a criterial test, which might be expected to attenuate differences in lag-to-test, has not eliminated the interleaving benefit in recent math learning studies 33 .

Fourth, by allowing students to mentally compare different types of problems, interleaving may have fostered more relational processing 3 , potentially improving the ability to integrate concepts from superficially distinct problem categories in order to solve criterial test problems that combined non-isomorphic problem types (see Fig. 1 ). These problem types were merged through shared concepts, such as emitted radiation power, and not recognizing these connections would have rendered the problems unsolvable. Recognition of common concepts may have been more likely in the interleaved condition due to the inclusion of non-isomorphic problem types on each homework assignment, whereas in the blocked condition, students would have had to deliberately juxtapose different homework sets in order to find the relevant connections. The potential for increased relational processing in the interleaved condition might also be described as an instance of material-appropriate processing — that is, cognitive processes that match that needed to perform well on a criterial test 49 (in the present case, integrating non-isomorphic problem types via specific, connecting concepts) and are not redundant with other processes that may already be occurring.

Finally, given that every successive problem on the interleaved homework assignments involved a different topic, interleaving may have given students practice in strategy selection—that is, choosing the correct solution for a given problem from a range of possible options 3 , 21 , 50 . In contrast, the predictability of blocked assignments obviated any need to engage in strategy selection (as students could repeatedly use the same solutions with a high degree of success). Proficiency in strategy selection was crucial for all criterial test problems.

It should be reiterated, however, that none of the accounts presented here are mutually exclusive (e.g., improvements in inductive learning of problem categories and/or relational processing may have facilitated better strategy selection), nor was it the purpose of the present study to adjudicate between them. Any or all of these mechanisms may have jointly contributed to the efficacy of interleaving.

Although the present results are quite clear with respect to an interleaving benefit for memory, the results for “far” transfer of learning 37 —which in the present case involved combining information across topics in order to devise new solution strategies—are more equivocal. If such transfer is to be judged based on numerical and unit correctness, then there was, in effect size terms, a smaller benefit of interleaving relative to the recall of relevant formulas and principles. However, a high level of correct responding was not expected, and the correctness sub-measure could not fully capture the degree to which students were able to successfully transfer their learning (i.e., that measure could not account for better, but imperfect, solution strategies). In our view, further research using more fine-grained measures of problem-solving ability (e.g., having students delineate each solution step, which would have required longer test sessions, and then subjecting those steps to analysis) is needed to clarify the potential of interleaving for far transfer and whether the technique is competitive with other transfer-enhancing approaches 47 , 51 .

The disparity between homework and criterial test data—wherein interleaving initially yielded poorer performance and lower difficulty and efficacy ratings, yet better criterial test performance—illustrates a metacognitive illusion 52 that may complicate student acceptance of interleaving. That illusion reflects the tendency of human beings to be inaccurate at judging the progress of their own learning and the relative utility of contrasting pedagogical activities (with more effective techniques being judged as less beneficial and vice versa) 53 . In response, instructors might consider additional measures, such as explaining the long-term benefits of interleaving prior to administering homework assignments 54 . Fortunately, there did not seem to be an overtly hostile reception towards interleaving, at least as conveyed to the course instructor, and student evaluations of the course were also relatively unchanged versus prior iterations of the course taught by the same instructor.

From an application standpoint, it is promising that the methods used in the present study were relatively simple and could be adapted to other contexts wherein multiple topics are learned using blocked homework assignments. Simply interleaving those assignments in a similar fashion may greatly enhance their effectiveness. We wish to caution, however, that instructors and researchers will need to be careful in generalizing the present results to cases wherein assignments do not contain multiple isomorphic or nearly isomorphic problems for each topic, and it is unclear whether such interleaving benefits will be apparent on high-stakes exams after extensive cramming (especially when considering the tendency of some laboratory-developed learning interventions to “wash out” in classroom contexts) and practice exams 55 . If no such benefits reliably occur, then that would constitute a notable limitation, particularly if enhancing exam performance was the sole objective. However, it remains to be determined whether a larger interleaving benefit would be observed in cases where practice exams were more substantially different than subsequent high-stakes exams, as well as after high-stakes exams, during which any benefits of cramming may have dissipated. Finally, implementation issues 56 such as the relative predictability of interleaving schedules 28 and the point during the learning process that interleaving is introduced 2 , 21 remain to be resolved. Given the incipient state of the classroom-focused interleaving literature, real-world uses of interleaving will inevitably involve a certain amount of trial-and-error.

From the perspective of undergraduate physics education and other forms of STEM learning, the present results serve as a proof-of-concept for a relatively low-cost learning intervention (in terms of time required and necessary equipment) that has the potential to yield sizeable learning benefits. The finding that interleaving benefits learning for one of the most challenging subjects that college students have to master, and does so for the case of relatively difficult problem-solving materials, invites a reevaluation of conventional instructional approaches and a greater appreciation for the influence of practice schedules in the development of skills and expertise. Indeed, it is becoming increasingly apparent that there are a variety of educationally authentic contexts in which human learners benefit more from practicing multiple topics from a given domain at one time, rather than practicing one topic at one time.

Preregistration

The study design and analysis plan were preregistered prior to data collection at: https://osf.io/8t4e5/ . Of the analyses described in the main text, the preregistered analysis plan contains the only comparison of overall criterial test and midterm exam performance across conditions. All other analyses, including performance on course assignments, accompanying judgments of learning, and exit survey analysis, were planned after preregistration but before data collection and should be regarded as exploratory.

Participants

Participants were 350 undergraduate students enrolled in either of two back-to-back lecture sections of Physics 5 C (“Physics for Life Sciences Majors: Electricity, Magnetism, and Modern Physics”) at the University of California, Los Angeles (UCLA) in Winter 2020, which began on 6 January 2020 and ended on 20 March 2020. Per the preregistered inclusion criteria, any student that did not complete any homework assignment during Stage 1 (weeks 1–4) or Stage 2 (weeks 5–8) or that did not take the associated criterial test was removed from the data analyses for the corresponding stage of the study. Consequently, in Stage 1, analyses were performed using data from 139 students in the first lecture section and 151 students in the second lecture section (henceforth, referred to as Lecture 1 and Lecture 2, respectively). In Stage 2, 137 students in Lecture 1 and 149 students in Lecture 2 were included in the analyses. Demographic information for all students included in the data analyses is listed in Supplementary Table 1 . It should be noted that there was no significant difference in mean GPA between students in Lecture 1 and Lecture 2. Thus, despite the fact that students enrolled in the lecture section of their choice (often based on their schedule of availability and preference for time-of-day), any potential differences in academic aptitude between the students in the two lecture sections were likely to have been negligible.

The study was approved by the UCLA Human Research Protection Program as exempt from formal review. No written informed consent was required for data collected during the course of normal instruction and reported in a fully anonymous and summary fashion as occurs in this manuscript. Informed consent was obtained for any individually identifiable reporting of data, of which there are none in this manuscript.

Course description

Physics 5 C is a 10-week lower-division course that is the third in a sequence of required physics courses for life sciences majors at UCLA. The official description of the course states that it addresses: “Electrostatics in vacuum and in water. Electricity, circuits, magnetism, quantum, atomic and nuclear physics, radioactivity, with applications to biological and biochemical systems.” In Winter 2020, the course involved thrice-weekly lecture sections of 50 min each (Lecture 1 from 10 to 10:50 AM and Lecture 2 from 11 to 11:50 AM; each student was enrolled in either of those sections), a weekly discussion section with a duration of 50 min, and a weekly laboratory section with a duration of 110 min. Both lecture sections were taught by the first author of this manuscript (J.S.), a faculty member in the Department of Physics and Astronomy at UCLA, on Mondays, Wednesdays, and Fridays. The discussion and laboratory sections, of which there were multiple sections available each week, were taught by graduate teaching assistants and collaborative problem-solving therein was further facilitated by undergraduate learning assistants.

Grading in Physics 5 C during Winter 2020 was determined via participation questions administered during the lecture sections (5%), discussion section assignments (5%), thrice-weekly homework assignments (20%), laboratory activities (15%), and two midterm exams (22.5% each). Participation questions and homework assignments were completed individually, whereas the remaining graded components were completed entirely or partly in groups. A cumulative final exam was originally scheduled and intended to be the most heavily-weighted aspect of the course (30%); however, that exam was removed from the required list of graded components and was made optional due to COVID-19 pandemic-induced suspension of all in-person instruction at UCLA on 11 March 2020. Importantly, the experimental manipulation and all primary measures of interest (i.e., the criterial tests) had been completed and were unaffected by the time in-person instruction was suspended.

Study materials are archived at the Open Science Framework (OSF): https://osf.io/8t4e5/ . Course materials were drawn from the assigned textbook (University Physics for the Life Sciences by Knight, Jones and Field), which is a common textbook for undergraduate physics courses in the United States. A list of topics covered during weeks 1–8 of the course is presented in Table 1 . There were 30 topics per experimental stage. Each lecture covered topics that roughly corresponded to between 1 and 3 sections of the course textbook. Each lecture began with an outline of what was to be learned followed by explanations of key concepts, worked examples, and clicker questions that were often accompanied by peer instruction. Discussion sections consisted of a short review of relevant topics from that week followed by a group exercise involving a single, reasonably challenging corresponding problem on a worksheet. Students were given credit for attending discussion sections and for demonstrating a reasonable level of effort and completion on the weekly problem as judged by their teaching assistant, but discussion worksheets were not scored for correctness. Weekly labs gave students hands-on experience applying course concepts to real physical systems and typically involved materials that had already been covered a week or two beforehand in lecture and on homework assignments.

Both experimental stages featured 10 homework assignments each spread across 4 weeks. There were nine problems per assignment (exceptions included the last two assignments of the blocked condition as well as the first two and last three assignments of the interleaved condition), for a total of 84 homework problems (see Fig. 1 and the main text). There were three isomorphic problems for a given topic (excepting six topics per experimental stage, for which there were two isomorphic problems). It should be noted that given the constraints used to define blocking and interleaving, the interleaved condition had fewer problems on the first two assignments per cycle (given the number of topics introduced to date), and on the final week of a given cycle, the interleaved condition had one additional problem per assignment and up to two problems per topic (but not presented adjacent to one another), with the blocked condition also having fewer than nine problems each. Given the proximity to the end of each cycle and variations in assignment length, topics that appeared on the final week of assignments were not included on the criterial tests.

Each assignment took the form of a multi-page PDF uploaded to Gradescope (a web application for turning in and scoring assignments) on a Monday, Wednesday, or Friday of a given week. Each assignment contained instructions reminding students to complete each assignment on their own, avoid skipping problems, always show their work in the provided spaces (so as to receive completion credit), and clearly indicate their final answers in provided boxes. Each problem type consisted of using a concept and related formulas to compute the values of one or more physical quantities. Isomorphs for each problem type was generated by varying superficial features that left the underlying computational and conceptual structure invariant, such as by changing values for given physical quantities or changing the context in which the given information was presented.

The final page of each assignment contained three multiple-choice survey questions: (a) How difficult did you find the questions on this assignment?; (b) Over how many days did you complete this assignment?; and (c) How well do you think you have learned the concepts and procedures addressed by these problems?

There were three assignments each week except in weeks 3 and 7, during which there was no class on Monday owing to a holiday. This holiday fell on precisely the same day in the practice schedule during each stage, so the two stages had identical problem set schedules despite the holidays.

Both criterial tests were intended to be completed within a 50-min lecture period and contained three questions each. The formatting of the tests, which were administered in pen (or pencil)-and-paper form, mirrored the homework assignments in that there were provided spaces and boxes to show work and to indicate final answers. Critically, however, the criterial test problems required integrating knowledge from two separately-learned topics, or applying knowledge regarding a previously learned topic in a new way (as described in the main text). The topics addressed on the criterial tests are noted in Fig. 1 of the main text. Given the deviations in the number of problems per assignment in the final week of each cycle, as well as the proximity in time between instruction and the criterial test, all topics addressed in that week were not covered on the criterial tests.

Two midterm exams were administered (both occurring on the first Monday after the end of an experimental stage and ~72 h after the criterial test). Each midterm exam contained five problems that were of a similar type as those presented on the criterial tests.

At the end of the course, students were asked to complete an online exit survey in exchange for extra credit. The survey contained questions addressing (a) how the homework assignments were completed; (b) study activities that occurred prior to the surprise and midterm exams; (c) level of surprise in the surprise exams, and (d) prior physics courses. Questions addressing (a–c) were posed separately for Stages 1 and 2. A complete copy of the exit survey is archived at the aforementioned OSF link.

Design and procedure

A 2 × 2 counterbalanced design was used with within-subjects factors of condition (blocked vs. interleaved) and Stage (1 vs. 2). Blocking versus interleaving was manipulated by having one lecture section experience blocking and interleaving during Stages 1 and 2, respectively, whereas the other section experienced the reverse of that arrangement. The experiment was implemented as part of regular course activities as follows. On the first day of class, the instructor outlined course expectations as described in the syllabus. The substantial contribution of homework assignments to the course grade was emphasized (and to further incentivize completion of homework assignments, an additional 1% extra credit bonus was promised to all students that completed every single homework assignment). Homework assignments were then released regularly online on each Monday, Wednesday, and Friday (during weeks 1–4 and 5–8, and excepting the Friday of weeks 4 and 8). Each assignment was to be completed within 72 h of it being made available, and finished assignments were to be scanned and uploaded to Gradescope for grading. Fully worked solutions and answers for each assignment were posted each Sunday evening. Grades, rubrics, and answer keys for each assignment were posted on Gradescope within roughly 1 week of the due date. All other course activities, including the lectures, discussion sections, and lab sections, proceeded as per standard practice. The course instructor delivered identical lecture content to both sections throughout the entire course.

During the lecture sections on the Fridays of weeks 4 and 8, the surprise criterial test was administered. That lecture had been billed as a “review session” addressing the content covered over the preceding 4 weeks, with students incentivized to attend by a promise of 1% extra credit. In place of a review session, however, the test was handed out, students were told that they would get up to 1% extra credit according to their performance on the test (although during the actual assignment of grades, all students were given the full 1% extra credit), and students were then given the full 50-minute lecture period to complete the test. Aside from increasing every student’s final grade by 1%, the criterial tests did not impact student grades. The test was proctored by the course instructor and teaching assistants. Survey data revealed that the majority of students were surprised that the “review session” actually entailed a criterial test (see Table 4 ).

Performance on the blocked and interleaved homework assignments was analyzed to provide insights into the relative difficulty of the two learning schedules used. To facilitate analysis, each students’ intended answers, as indicated by entry into provided answer boxes, were transcribed into an electronic spreadsheet, and the answers were then computer-scored against a correct answer list. In all cases, the transcription of homework data was conducted by research assistants that were blind to the condition. In addition, the answers to the three multiple-choice survey questions on each assignment were also transcribed by hand.

Performance on the criterial tests was the primary outcome of interest given that the criterial tests were the purest measures of the effects of the experimental manipulation (i.e., uncontaminated by any additional study or review activities, or foreknowledge of the question types). Every problem on the criterial tests required (a) recognizing which mathematical relationships (often equations) were relevant for solving that problem, (b) writing those relationships down, and (c) appropriately combining them with given values of physical quantities to compute a single final numerical answer with a corresponding physical unit. A rubric based on that employed throughout lower-division physics courses at UCLA was used to score the criterial tests and allowed for inferring whether steps (a–c) were successfully completed. The rubric items per problem fell into two mutually exclusive, exhaustive categories: In the first, “memory” category, each item indicated whether or not one of the necessary equations was recalled and written down correctly; in the second, “correctness” category, each item indicated whether or not the final numerical answer and unit were correct. Criterial tests were each scored by at least two trained raters that were blind to the condition. Each rubric item for each problem was first scored independently by two scorers, after which a third scorer independently scored only those items on which the original two scorers differed. For each rubric item, inter-rater reliability (IRR) between the original two raters was assessed. In Stages 1 and 2, the mean IRR across all rubric items on the criterial test was Cohen’s κ  = 0.81 and 0.83, respectively.

Null hypothesis significance testing of criterial test data was conducted using t tests as per our preregistered analysis plan. All tests were two-tailed. Effect sizes were reported in terms of Cohen’s d as defined in prior work 57 . As a supplement to the t tests, permutation tests (which do not require the assumption of normality of underlying population distributions) were also conducted. The permutation tests yielded negligibly different p values relative to the t tests and are not detailed further for simplicity.

Performance on the midterm and final exams were originally to be analyzed separately. Performance on these exams would have reflected the effects of the experimental manipulation as well as review and study activities, including cramming, prior to the exams. However, as the final exam was made optional (and switched to take-home format) due to the COVID-19 pandemic, data for that exam were not available for the vast majority of students. Hence, the analysis of that exam was dropped. Per procedures that the instructor had used in prior physics courses, the midterm exams—which were completed at separate exam periods outside of normal lecture hours—were completed in individual and group stages (i.e., students first attempted the questions on their own, they were organized into groups to share ideas and revise their answers). The results reported in the main text reflect data from the individual stages. The midterm exams were scored by teaching assistants that were also blind to condition.

The exit surveys, which provided additional context for interpreting the study results, were transcribed by research assistants that were blind to condition.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

Data and materials are archived at the OSF: https://osf.io/8t4e5/ .

Code availability

Analysis code is available upon request.

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Acknowledgements

Thanks to the UCLA Teaching and Learning Lab for helpful discussions and Casey Shapiro for helpful advice. Thanks to Shirley Zhang, Quynh Tran, Chester Li, and Nam Phuong Nguyen for assisting with the scoring of criterial tests, and to Jeana Wei and other members of the UCLA Bjork Lab for assisting with transcription of homework assignments. This research was supported by the UCLA Division of Physical Sciences.

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Joshua Samani

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Samani, J., Pan, S.C. Interleaved practice enhances memory and problem-solving ability in undergraduate physics. npj Sci. Learn. 6 , 32 (2021). https://doi.org/10.1038/s41539-021-00110-x

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Received : 07 April 2021

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Published : 12 November 2021

DOI : https://doi.org/10.1038/s41539-021-00110-x

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