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Strategies to redefine the problem exploration space for design innovation

• September 2018
• Conference: International Conference on Engineering and Product Design Education
• At: London, UK

• Iowa State University
• This person is not on ResearchGate, or hasn't claimed this research yet.

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The 5 Stages in the Design Thinking Process

Design thinking is a methodology which provides a solution-based approach to solving problems. It’s extremely useful when used to tackle complex problems that are ill-defined or unknown—because it serves to understand the human needs involved, reframe the problem in human-centric ways, create numerous ideas in brainstorming sessions and adopt a hands-on approach to prototyping and testing. When you know how to apply the five stages of design thinking you will be impowered because you can apply the methodology to solve complex problems that occur in our companies, our countries, and across the world.

Design thinking is a non-linear, iterative process that can have anywhere from three to seven phases, depending on whom you talk to. We focus on the five-stage design thinking model proposed by the Hasso Plattner Institute of Design at Stanford (the d.school) because they are world-renowned for the way they teach and apply design thinking.

What are the 5 Stages of the Design Thinking Process

The five stages of design thinking, according to the d.school, are:

Empathize : research your users' needs .

Define : state your users' needs and problems.

Ideate : challenge assumptions and create ideas.

Prototype : start to create solutions.

Test : try your solutions out.

Let’s dive into each stage of the design thinking process.

• Transcript loading…

Hasso-Platner Institute Panorama

Ludwig Wilhelm Wall, CC BY-SA 3.0 <https://creativecommons.org/licenses/by-sa/3.0>, via Wikimedia Commons

Stage 1: Empathize—Research Your Users' Needs

Empathize: the first phase of design thinking, where you gain real insight into users and their needs.

© Teo Yu Siang and the Interaction Design Foundation, CC BY-NC-SA 3.0.

The first stage of the design thinking process focuses on user-centric research . You want to gain an empathic understanding of the problem you are trying to solve. Consult experts to find out more about the area of concern and conduct observations to engage and empathize with your users. You may also want to immerse yourself in your users’ physical environment to gain a deeper, personal understanding of the issues involved—as well as their experiences and motivations . Empathy is crucial to problem solving and a human-centered design process as it allows design thinkers to set aside their own assumptions about the world and gain real insight into users and their needs.

Depending on time constraints, you will gather a substantial amount of information to use during the next stage. The main aim of the Empathize stage is to develop the best possible understanding of your users, their needs and the problems that underlie the development of the product or service you want to create.

Stage 2: Define—State Your Users' Needs and Problems

Define: the second phase of design thinking, where you define the problem statement in a human-centered manner.

In the Define stage, you will organize the information you have gathered during the Empathize stage. You’ll analyze your observations to define the core problems you and your team have identified up to this point. Defining the problem and problem statement must be done in a human-centered manner .

For example, you should not define the problem as your own wish or need of the company: “We need to increase our food-product market share among young teenage girls by 5%.”

You should pitch the problem statement from your perception of the users’ needs: “Teenage girls need to eat nutritious food in order to thrive, be healthy and grow.”

The Define stage will help the design team collect great ideas to establish features, functions and other elements to solve the problem at hand—or, at the very least, allow real users to resolve issues themselves with minimal difficulty. In this stage, you will start to progress to the third stage, the ideation phase, where you ask questions to help you look for solutions: “How might we encourage teenage girls to perform an action that benefits them and also involves your company’s food-related product or service?” for instance.

Stage 3: Ideate—Challenge Assumptions and Create Ideas

Ideate: the third phase of design thinking, where you identify innovative solutions to the problem statement you’ve created.

During the third stage of the design thinking process, designers are ready to generate ideas. You’ve grown to understand your users and their needs in the Empathize stage, and you’ve analyzed your observations in the Define stage to create a user centric problem statement. With this solid background, you and your team members can start to look at the problem from different perspectives and ideate innovative solutions to your problem statement .

There are hundreds of ideation techniques you can use—such as Brainstorm, Brainwrite , Worst Possible Idea and SCAMPER . Brainstorm and Worst Possible Idea techniques are typically used at the start of the ideation stage to stimulate free thinking and expand the problem space. This allows you to generate as many ideas as possible at the start of ideation. You should pick other ideation techniques towards the end of this stage to help you investigate and test your ideas, and choose the best ones to move forward with—either because they seem to solve the problem or provide the elements required to circumvent it.

Stage 4: Prototype—Start to Create Solutions

Prototype: the fourth phase of design thinking, where you identify the best possible solution.

The design team will now produce a number of inexpensive, scaled down versions of the product (or specific features found within the product) to investigate the key solutions generated in the ideation phase. These prototypes can be shared and tested within the team itself, in other departments or on a small group of people outside the design team.

This is an experimental phase, and the aim is to identify the best possible solution for each of the problems identified during the first three stages . The solutions are implemented within the prototypes and, one by one, they are investigated and then accepted, improved or rejected based on the users’ experiences.

By the end of the Prototype stage, the design team will have a better idea of the product’s limitations and the problems it faces. They’ll also have a clearer view of how real users would behave, think and feel when they interact with the end product.

Stage 5: Test—Try Your Solutions Out

Test: the fifth and final phase of the design thinking process, where you test solutions to derive a deep understanding of the product and its users.

Designers or evaluators rigorously test the complete product using the best solutions identified in the Prototype stage. This is the final stage of the five-stage model; however, in an iterative process such as design thinking, the results generated are often used to redefine one or more further problems. This increased level of understanding may help you investigate the conditions of use and how people think, behave and feel towards the product, and even lead you to loop back to a previous stage in the design thinking process. You can then proceed with further iterations and make alterations and refinements to rule out alternative solutions. The ultimate goal is to get as deep an understanding of the product and its users as possible.

Did You Know Design Thinking is a Non-Linear Process?

We’ve outlined a direct and linear design thinking process here, in which one stage seemingly leads to the next with a logical conclusion at user testing . However, in practice, the process is carried out in a more flexible and non-linear fashion . For example, different groups within the design team may conduct more than one stage concurrently, or designers may collect information and prototype throughout each stage of the project to bring their ideas to life and visualize the problem solutions as they go. What’s more, results from the Test stage may reveal new insights about users which lead to another brainstorming session (Ideate) or the development of new prototypes (Prototype).

It is important to note the five stages of design thinking are not always sequential. They do not have to follow a specific order, and they can often occur in parallel or be repeated iteratively. The stages should be understood as different modes which contribute to the entire design project, rather than sequential steps.

The design thinking process should not be seen as a concrete and inflexible approach to design; the component stages identified should serve as a guide to the activities you carry out. The stages might be switched, conducted concurrently or repeated several times to gain the most informative insights about your users, expand the solution space and hone in on innovative solutions.

This is one of the main benefits of the five-stage model. Knowledge acquired in the latter stages of the process can inform repeats of earlier stages . Information is continually used to inform the understanding of the problem and solution spaces, and to redefine the problem itself. This creates a perpetual loop, in which the designers continue to gain new insights, develop new ways to view the product (or service) and its possible uses and develop a far more profound understanding of their real users and the problems they face.

The Take Away

Design thinking is an iterative, non-linear process which focuses on a collaboration between designers and users. It brings innovative solutions to life based on how real users think, feel and behave.

This human-centered design process consists of five core stages Empathize, Define, Ideate, Prototype and Test.

It’s important to note that these stages are a guide. The iterative, non-linear nature of design thinking means you and your design team can carry these stages out simultaneously, repeat them and even circle back to previous stages at any point in the design thinking process.

References & Where to Learn More

Take our Design Thinking course which is the ultimate guide when you want to learn how to you can apply design thinking methods throughout a design thinking process. Herbert Simon, The Sciences of the Artificial (3rd Edition), 1996.

d.school, An Introduction to Design Thinking PROCESS GUIDE , 2010.

Gerd Waloszek, Introduction to Design Thinking , 2012.

Hero Image: © the Interaction Design Foundation, CC BY-NC-SA 3.0.

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Exploratory Methods and Techniques for Space Technology Development and Space Mission Concept Development

Oct. 12, 2020

• Lizbeth B. De La Torre Former Research Assistant
• Danielle Wood Assistant Professor of Media Arts and Sciences; Assistant Professor (Joint) of Aeronautics and Astronautics

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De La Torre, Lizbeth B., Danielle Wood. "Exploratory Methods and Techniques for Space Technology Development and Space Mission Concept Development," IAC 2020, October 2020.

This paper hopes to fill a gap in literature by framing the current state of exploratory design methods and techniques within space mission development and laying the groundwork to begin utilizing a wider variety of these methods and accompanying techniques. The purpose of this paper is to review the ways in which design methods and techniques used in other fields may be used in support of the space mission concept development process and space technology development. Designers are almost synonymous with the consumer product, automotive and entertainment industries. Fields such as Product Design, Transportation Design and Entertainment emphasize finding solutions to problems using exploratory design methods and techniques. Often, they are leaders in their organizations. However, there is not a direct appreciation or understanding of how to utilize these methods and techniques within aerospace. These methods have been shown to support mission concept development, however may also directly support technology development, as is seen in the consumer product industry. Evidence shows that these methods have sporadically been utilized by NASA for habitat design, software development and astronaut wearables. This paper explores opportunities within the space mission concept development process where these techniques are currently used and develops a design library of methods and techniques used outside of Aerospace that may be supportive of technology development. The current Pre-Phase A concept development process is mapped along with exploratory design methods used in other industries. Design Thinking is a heuristic problem solving method that can be applied to many fields. Human Centered Design and User Centered Design have been utilized for architecture and software development; these same tools could also be used to help inform the design of long term human habitation system on planetary surfaces. The Imagineering process is instrumental in theme park development; this paper argues it should also inform design of robotic science missions such as Mars Sciences. Science Fiction Thinking is a method of extrapolating future technology. How can this type of thinking inform the design of systems that aim to detect life in locations such as the liquid oceans on Europa and Titan? Techniques that are instrumental throughout these methods, such as storyboarding, sketching and prototyping are also defined. Interviews with employees within aerospace, consumer products and entertainment may shed light on opportunities and barriers to utilizing these techniques. 

Exploratory design methods and techniques in support of space mission concept development

B. De La Torre, Lizbeth(Barrios De La Torre). "Exploratory design methods and techniques in support of space mission concept development," September 2020.

Meet Lizbeth B. De La Torre

I specialize in Creative Technology for space. I use inspiration from sci-fi, and creative processes from film and animation to create....

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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!

Your list of techniques for problem solving can be helpfully extended by adding TRIZ to the list of techniques. TRIZ has 40 problem solving techniques derived from methods inventros and patent holders used to get new patents. About 10-12 are general approaches. many organization sponsor classes in TRIZ that are used to solve business problems or general organiztational problems. You can take a look at TRIZ and dwonload a free internet booklet to see if you feel it shound be included per your selection process.

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Going from a mere idea to a workshop that delivers results for your clients can feel like a daunting task. In this piece, we will shine a light on all the work behind the scenes and help you learn how to plan a workshop from start to finish. On a good day, facilitation can feel like effortless magic, but that is mostly the result of backstage work, foresight, and a lot of careful planning. Read on to learn a step-by-step approach to breaking the process of planning a workshop into small, manageable chunks.  The flow starts with the first meeting with a client to define the purposes of a workshop.…

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Please note you do not have access to teaching notes, creative problem-solving techniques, paradigm shift and team performance.

Team Performance Management

ISSN : 1352-7592

Article publication date: 6 October 2020

Issue publication date: 6 October 2020

This paper aims to consider why creative problem-solving techniques may not always produce useful results and sets out to explain why this might be and what steps should be taken to avoid it happening. The paper provides an understanding of how different creative problem-solving techniques are best suited to gaining insights into problems requiring different degrees of paradigm shift. It argues that team members’ personalities and thinking styles and team composition should be taken into account when using the techniques. It examines the role the facilitator plays in planning and conducting the ideation process.

Design/methodology/approach

The paper provides simple illustrations of some of the creative problem-solving techniques. It reviews relevant literature and argues how individual differences of team members along with team composition can influence team performance in using the creative problem-solving techniques.

Personality, thinking styles and learning styles are relevant to the effective use of creative problem-solving techniques. Team composition, team motivation and mood factors should also be taken into account. The facilitator is key in ensuring the efficacy of the problem-solving process.

Originality/value

This paper will be helpful to academics who study creative problem-solving as well as informing management practitioners and trainers about the procedures and potential pitfalls to avoid.

• Team performance
• Personality
• Problem-solving
• Team composition
• Thinking styles

Acknowledgements

The author wishes to thank the reviewers for then comments on the drafts of the article.

Proctor, T. (2020), "Creative problem-solving techniques, paradigm shift and team performance", Team Performance Management , Vol. 26 No. 7/8, pp. 451-466. https://doi.org/10.1108/TPM-06-2020-0049

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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Twelve tips to stimulate creative problem-solving with design thinking

Affiliations.

• 1 University of North Carolina Adams School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
• 2 University of North Carolina Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
• 3 Joint Department of Biomedical Engineering of the University of North Carolina at Chapel Hill and North Carolina State University, Raleigh, NC, USA.
• 4 North Carolina State University College of Design, North Carolina State University, Raleigh, NC, USA.
• PMID: 32847450
• DOI: 10.1080/0142159X.2020.1807483

Design thinking is increasingly applied in healthcare and health professions education to generate innovative solutions to difficult problems. The design thinking framework helps individuals approach problems with a user-centered focus; the emphasis is on understanding the user experience, their challenges, and possible design solutions that are aligned with their needs. In this twelve tips paper, we describe strategies that health professions educators can use to prepare for, conduct, and support design thinking. These strategies may also be useful to learners, practitioners, and organizations to address complex problems.

Keywords: Design thinking; creativity; innovation; problem-solving; user-centered design.

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9 Problem Solving, Planning, and Decision-Making

• Published: July 2014
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This chapter identifies how the event horizon model offers potential leverage points for theories of problem solving. It considers the role in problem solving of three aspects of event cognition: event segmentation, causal structure, and interactions of facilitation and interference between event representations in long-term memory. In terms of event segmentation, he model helps conceptualize how problem solvers understand a problem. In terms of causal structure, the model provides insight into how a person understands how the components of a problem would interact. Finally, the model gives some insight into how a problem solver could call upon memories of prior problems encountered that might help with the current one.

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Technological problem solving: an investigation of differences associated with levels of task success

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• Published: 02 June 2021
• Volume 32 , pages 1725–1753, ( 2022 )

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• David Morrison-Love   ORCID: orcid.org/0000-0002-9009-4738 1  

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Research into technological problem solving has shown it to exist in a range of forms and draw upon different processes and knowledge types. This paper adds to this understanding by identifying procedural and epistemic differences in relation to task performance for pupils solving a well-defined technological problem. The study is theoretically grounded in a transformative epistemology of technology education. 50 pupils in small groups worked through a cantilever problem, the most and least successful solutions to which were identified using a Delphi technique. Time-interval photography, verbal interactions, observations and supplementary data formed a composite representation of activity which was analysed with successively less contrasting groups to isolate sustained differences. Analyses revealed key differences in three areas. First, more successful groups used better and more proactive process-management strategies including use of planning, role and task allocation with lower levels of group tension. Second, they made greater use of reflection in which knowledge associated with the technological solution was explicitly verblised. This was defined as ‘analytical reflection’ and reveals aspects of pupils’ qualitative technical knowledge. Third, higher-performing groups exhibited greater levels of tacit-procedural knowledge within their solutions. There was also evidence that less successful groups were less affected by competition and not as comprehensive in translating prior conceptual learning into their tangible technological solutions. Overall findings suggest that proactive management, and making contextual and technical connections, are important for pupils solving well-defined technological problems. This understanding can be used to support classroom pedagogies that help pupils learn to problem solve more effectively.

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Introduction

Problem solving is an activity, a context and a dominant pedagogical frame for Technology Education. It constitutes a central method and a critical skill through which school pupils learn about and become proficient in technology (Custer et al., 2001 ). Research has, among other things, been able to identify and investigate sets of intellectual and cognitive processes (Buckley et al., 2019 ; Haupt, 2018 ; Johnson, 1997 ; Sung & Kelly, 2019 ) and shown there to be conceptual, procedural, relational and harder-to-get-to forms of ‘technological knowledge’ involved when pupils develop technological solutions (de Vries, 2005 ; McCormick, 1997 , 2004 ; Rauscher, 2011 ). Some authors argue that technological problem solving (and design) is a situated activity (Jackson & Strimel, 2018 ; Murphy & McCormick, 1997 ; Liddament, 1996 ), but with social and context-independent processes also playing an important role (e.g. Jones, 1997 ; Winkelmann & Hacker, 2011 ). Within and across this vista, there has been strong interest in more open-ended, creative and design-based problem-solving (Lewis, 2005 , 2009 ), which Xu et al. ( 2019 ) notes became particularly prominent after 2006. These studies have helped to understand some of the challenges and pedagogies of design (Gómez Puente et al., 2013 ; Lavonen et al., 2002 ; Mioduser & Dagan, 2007 ; Mawson, 2003 ) including those that mitigate effects such as cognitive fixation (e.g. McLellan & Nicholl, 2011 ). Problem solving, it seems, is a pervasive idea in technology education research and policy. Middleton ( 2009 ) notes that problem solving is found in almost all international technology education curricula.

The pace, nature and complexity of contemporary societal challenges make it more critical than ever that technology classrooms prepare people who can think through and respond to technological problems effectively. It requires that we strengthen our understanding in ways that will ultimately be powerful for shaping classroom learning. One way of contributing to this is to learn more about the differences between learners who are more and less successful at technological problem solving. Studies that share a comparative perspective and/or a focus upon task success are relatively few. Doornekamp ( 2001 ) compared pupils (circa 13 years old) who solved technological problems using weakly structured instructional materials with those using strongly structured materials. It was shown that the latter led to statistically significant improvements in the quality of the technical solutions. More recently, Bartholomew & Strimel ( 2018 ) were able to show that, for open-ended problem solving, there was no significant relationship between prior experience and folio creation, but that more in-school school experience of open-ended problem solving corresponded to higher ranked solutions.

This paper contributes to this work by reporting on a study that compares groups of pupils during technological problem solving in order to identify areas of difference and the factors associated with more successful outcomes. Specifically, it addresses the question: ‘In terms of intellectual processes and knowledge, what are the differences in the modi operandi between groups of pupils that produced more and less successful technological solutions to a well-defined problem?’ Theoretically grounded in a transformative epistemology of technology education (Morrison-Love, 2017 ), the study identifies prominent procedural and epistemic differences in pupils’ thinking and technical solutions. Groups of pupils engaged with a structures problem requiring them to develop a cantilever bridge system which would facilitate safe travel across a body of water.

The paper begins by setting out the theoretical basis and conceptual framework for investigation before describing the comparative methodological and analytical approaches that were adopted. Following an analysis and presentation of key findings, conclusion and implications are discussed.

A theoretical basis for the study of technological problem solving

Despite there being no single comprehensive paradigm for technological problem solving, a theoretical grounding and conceptual framework necessary for this study are presented. At the theoretical level, this study is based upon a ‘transformative epistemology’ for technology education (Morrison-Love, 2017 ). From this, a ternary conceptual framework based upon mode, epistemology and process is developed to support study design and initiate data analysis.

A transformative epistemology for technology education (Morrison-Love, ibid) proposes that pupils’ technological knowledge and capability arises from the ontological transformation of their technical solution from ‘perdurant’ (more conceptual, mutable, less well-defined, partial) in the early stages, to ‘endurant’ (comprehensive, tangible, stable over time) upon completion. It proposes that technical outcomes exist in material and tangible forms and that to be technological (rather than, for example, social, cultural or aesthetic) these must somehow enhance human capabilities in their intended systems of use. For this study, the ideas of transformative epistemology support problem solving in which pupils build technological knowledge by iteratively moving from concept to tangible, material solution. Moreover, it means pupils are successful in this when their solutions or prototypes: (1) enhance existing human capabilities in some way, and (2) are sufficiently developed to be stable over time, beyond the problem-solving activity that created it.

A conceptual framework for technological problem solving

A ternary conceptual framework (Fig. 1 ) of mode, process and epistemology was developed from the literature in which the knowledge and cognitive/intellectual processes used by pupils are enacted in the ‘process application block’. This is like the ‘problem space’ described in a model proposed by Mioduser ( 1998 ). Collectively, the goal of creating a physical artefact, the solution itself, the epistemic and procedural dimensions reflect the four dimensions of technology identified by Custer ( 1995 ).

‘A conceptual framework for technological problem solving’

Mode and forms dimension

Although problem solving may be ‘technological’, several classifications of both problem type and problem solving are found in the literature. Ill-defined and well-defined problems build upon the earlier work of information processing and cognitive psychology (see Jonassen, 1997 ). Typically, these two forms reflect different extents to which the outcome is specified to the solver at the outset. Ill-defined problems are strongly associated with design and creativity, and Twyford and Järvinen ( 2000 ) suggest that these more open briefs promote greater social interaction and use by pupils of prior knowledge and experience. Additionally, two forms of troubleshooting were identified in the literature: emergent troubleshooting and discrete troubleshooting. MacPherson ( 1998 ) argues that ‘troubleshooting’ constitutes a particular subset of technological problem solving—something earlier recognised by McCade ( 1990 ), who views it as the identification and overcoming of problems encountered during the production or use of a technical solution. In this study, emergent troubleshooting occurs in the process of developing solutions in response to emergent problems (McCormick, 1994 ). Discrete troubleshooting is a process in which significant technical understanding is applied in a structured way (Schaafstal et al., 2000 ) to resolve something about an existing artefact.

Intellectual and cognitive process dimension

Studies often conceptualise cognitive processes discretely rather than hierarchically, and different studies employ different process sets. Williams ( 2000 ), identifies evaluation, communication, modelling, generating ideas, research and investigation, producing and documenting as important to technological problem solving, while DeLuca ( 1991 ) identifies troubleshooting, the scientific process, the design process, research and development, and project management. There are also studies that employ specific, or more established, coding schemes for sets of intellectual and cognitive processes. A detailed analysis of these is given Grubbs et al. ( 2018 ), although the extent to which a particular process remains discrete or could form a sub-process of another remains problematic. In DeLuca’s ( 1991 ) break down for example, to what extent are research and investigation part of design and does this depend on the scale at which we conceptualise different processes?

Regardless of the processes a study defines, it is typically understood that pupils apply them in iterative or cyclic fashion. This is reflected across several models from Argyle’s ( 1972 ) ‘Motor Skill Process Model’ (perception-translation-motor response) through to those of Miodusre and Kipperman ( 2002 ) and Scrivener et al. ( 2002 ) (evaluation-modification cycles) which pertain specifically to technology education. All these models bridge pupils’ conceptual-internal representations with their practical-external representations as they move towards an ontologically endurant solution and this is captured by the ‘Re-Application/Transformation Loop’ of the conceptual framework. Given that little is known about where differences might lie, the process set identified by Halfin ( 1973 ) was adopted due to its rigour and the breadth of thinking it encompasses. This set was validated for technology classrooms by Hill and Wicklein ( 1999 ) and used successfully by other studies of pupils technological thinking including Hill ( 1997 ), Kelley ( 2008 ) and Strimel ( 2014 ).

Epistemology dimension

The nature and sources of knowledge play a critical role for pupils when solving technological problems, but these remain far from straightforward to conceptualise. McCormick ( 1997 ) observes that the activity of technology education, and its body of content, can be thought of as ‘procedural knowledge’ and ‘conceptual knowledge’ respectively. Vincenti ( 1990 ), in the context of Engineering, makes the case for descriptive knowledge (things as they currently are) and prescriptive knowledge (of that with is required to meet a desired state) but also recognises knowledge can take on implicit, or tacit forms relating to an individual’s skill, judgement, and practice (Polanyi, 1967 ; Schön, 1992 ; Sternberg, 1999 ; Welch, 1998 ). Arguably, moving from concept to physical solution will demand from pupils a certain level of practical skill and judgement, and Morgan ( 2008 ) observes that procedural knowledge which is explicit in the early stages becomes increasingly implicit with mastery. Notably, in addition to conceptual, procedural and tacit forms of knowledge, there is also evidence that knowledge of principles plays a role. Distinct from impoverished notions of technology as ‘applied science’, Rophol ( 1997 ) shows that it is often technological principles, laws and maxims that are applied during problem solving rather than scientific ones. Frey ( 1989 ) makes similar observations and sees this form of knowledge arising largely from practice. In this study, knowledge of principles involves knowledge of a relationship between things. It is not constrained to those that are represented scientifically.

The conceptual framework finally accounts for pupils’ sources of knowledge during problem solving, building principally on a design knowledge framework of media, community and domain presented by Erkip et al. ( 1997 ). In this study, media includes task information, representations and materials; community includes teachers and peers, and domain relates to prior technological knowledge from within technology lessons and prior personal knowledge from out with technology lessons. Finally, the developing solution is itself recognised a source of knowledge that pupils iteratively engage with and reflect upon, even when it appears that limited progress in being made (Hamel & Elshout, 2000 ).

Methodology

The research question in this study is concerned with differences in the knowledge and intellectual processes used by pupils in moving from a perdurant to an endurant technical solution. From an exploratory stance, this elicits a dualistic activity system involving pupils’ subjective constructions of reality as well as the resultant tangible and more objective material solution. The study does not aim to investigate pupils’ own subjective constructions from an emic perspective, but rather seeks to determine the nature and occurrences of any differences during observable real-time problem-solving activity. As such, content rather than thematic analysis was used (Elo & Kyngäs, 2008 ; Vaismoradi et al., 2013 ) with concurrent data collection to build a composite representation of reality (Gall et al., 2003 , p.14). Complementary data provided insights into study effects, the classrooms and contexts within which problem-solving took place.

This study assumes that should differences exist, these will be discernible in the inferred cognitive processes, external material transformations, interactions and verbalisation (even though this tends to diminish as activity becomes more practical). Absolute and objective observation is not possible. This study also accepts that data gathering and analysis are influenced by theory, researcher fallibility and bias which will be explicitly accounted for as far as possible. Finally, while the conceptual framework provides an analytical starting point, it should not preclude the capture of differences that may lie elsewhere in the data including, for example, process that lie out with those identified by Halfin ( 1973 ).

Participants, selection and grouping

To support transferability, a representative spread of pupils from low, medium and high socio-economic backgrounds took part in this study. Purposeful, four-stage criterion sampling was used (Gall et al., 2003 , p.179). Stage one identified six schools at each socio-economic level from all Scottish secondary schools that presented pupils for one or more technology subjects with the Scottish Qualifications Authority. This was done using socio-economic data from the Scottish Area Deprivation Index, the Carstairs Index and pupil eligibility for subsidised meals. Secondary school catchment areas were used to account for pupil demographics as accurately as possible. All eighteen schools were subsequently ranked with one median drawn from low, medium and high bands of socio-economic deprivation (School 1: Low, School 2: Medium, School 3: High).

One class in each school was then selected from the second year of study prior to pupils making specific subject choices to minimise variations in curricular experience. In total, 3 class teachers and 50 pupils (20 female, 30 male) aged between 12 and 13 years old took part in the study. The group rather than the individual was defined as unit of study to centralise verbal interaction.

None of the pupils participating in this study had experience of group approaches such as co-operative learning and it was likely that groups might experience participation effects including inter-group conflict and interaction effects (Harkins, 1987 ; Sherif et al., 1961 ), social loafing (Salomon & Globerson, 1989 ), free-rider (Strong & Anderson, 1990 ) and status differential effects (Rowell, 2002 ). Relevant also to this study is evidence suggesting that gender effects can take place in untrained groups undertaking practical/material manipulation activities. To maximise interaction between group members and the material solution, thirteen single sex groups averaging four pupils were formed in order to: (1) minimise the marginalisation of girls with boys’ tendency to monopolise materials and apparatus in groups (Conwell et al., 1993 ; Whyte, 1984 ); (2) recognise boys’ tendency to respond more readily to other boys (Webb, 1984 ) and, (3) maximise girls’ opportunities to interact which is seen to erode in mixed groups (Parker & Rennie, 2002 ; Rennie & Parker, 1987 ). Hong et al. ( 2012 ) examines such gender differences in detail specifically within the context of technological problem solving. Teacher participation in group allocation minimised inter-group conflict and interaction effects although groups still experienced naturally fluctuating attrition from pupil absences (School 1 = 17.6%; School 2 = 2.5% and School 3 = 8.8%).

Identification of most and least successful solutions

The research question requires differences to be identified in terms of levels of success. The overall trustworthiness of any differences therefore depends upon the credible identification of the most and least successful solutions from the thirteen produced. Wholly objective assessment of the pupils’ solutions is not possible, and material imperfections in different solutions negated reliable physical testing across the three classes. Moreover, because the researcher earlier observed pupils while problem solving, neutrality of researcher judgement in establishing a rank order of group solutions was equally problematic. Everton and Green ( 1986 ) identify this biasing risk between and early and later stages of research as a form of contamination.

To address these limitations, a Delphi technique was design using the work of Gordon ( 1994 ), Rowe and Wright ( 1999 ) and Yousuf ( 2007 ). This was undertaken anonymously prior to any analysis and, in conjunction with the results of physical testing, enabled the four most successful and four least successful solutions to be confidently identified independently of the researcher. A panel of eight secondary school teachers was convened from schools out with the study. All panel members had expertise in teaching structures with no dependent relationships or conflicts of interest. Following Delphi training, and a threshold level of 75%, the four most and four least successful solutions on outcome alone were identified after two rounds. Qualitative content validity checks confirmed that panel judgements fell within the scope of the accessible information. 37/43 reasons given were ‘High’, with six considered ‘Medium’ because the reasoning was partially speculative. When triangulated with additional evidence from physical testing, two cohorts of four groups were identified and paired to form four dyads (Table 1 ).

Study design

As noted, ‘Structures’ was chosen as a topic area and was new to all participants. It was appropriate for setting well-defined problems and allowed pupils to draw upon a sufficiently wide range of processes and knowledge types in developing a tangible, endurant solution. In discussion with the researcher, teachers did not alter their teaching style and adopted pedagogy and formative interactions that would support independent thinking, reasoning and problem solving. This study involved a learning phase, followed by a problem-solving phase.

In the learning phase, groups engaged over three fifty-minute periods with a unit of work on structures which was developed collaboratively with, and delivered by, the three classroom teachers. This allowed pupils to interact with materials and develop a qualitative understanding of key structural concepts including strength, tension and compression, triangulation, and turning moments. During this time, pupils also acclimatised to the presence of the researcher and recording equipment which helped to reduce any potential Hawthorne effect (Gall et al., 2003 ). Structured observations, teacher de-briefs and questionnaires were used in this phase to capture study effects, unit content coverage and environmental consistency between the three classrooms. Content coverage and environmental consistency were shown to be extremely high. Scores from the unit activity sheets that pupils completed were used to gauge group understanding of key concepts.

The problem-solving phase took place over two circa 50-minute periods (range: 40–52 m) in which pupils responded to a well-defined problem brief. This required them to develop a cantilever bridge enabling travel across a body of water. This bridge would enhance people’s ability to traverse terrain (conditions for being ‘technological’) with maximal span rigidity and minimal deflection (conditions for an ontologically ‘endurant’ solution). All groups had access to the same range and number of materials and resources and were issued with a base board showing water and land on which to develop their solutions.

While video capture was explored in depth (Lomax & Casey, 1998 ), challenges in reliably capturing solution detail resulted in group verbalisation being recorded as audio. This was synchronised with time interval photography and supplemented with structured observer-participant observation that focused on a sub-set of observable processes from the conceptual framework (Halfin, 1973 ). The developing technical solutions were viewed as manifestations of the knowledge and intellectual processes used by pupils at different points in time through their cognitive and material interactions. Photographs captured the results of these interactions in group solutions every 3–4 min but did not capture interactions between pupils. The structured observational approach adopted continuous coding similar to that found in the Flanders System of Interaction analysis (Amatari, 2015 ) and was refined through two pilot studies. During each problem-solving session, groups were observed at least twice between photographs and, following each session, pupil questionnaires, teacher de-briefs and solution videos (360° panoramic pivot about the solution) were completed to support future analysis. Reflexive accounts by the researcher also captured critical events, observer and study effects.

Analytical approach

All data were prepared, time-synchronised and analysed in three stages. Core verbal data (apx. 12h) and photographic data (n = 206) were triangulated with observational and other data against time. The problem-solving phase for each class was broken into a series of 3–4 min samples labelled S = 1, S = 2, S = 3…with durations in each recorded in minutes and seconds. Verbal data were analysed using NVivo software using digital waveforms rather than transcribed files to preserve immediacy, accuracy and minimise levels of interpretation (Wainwright & Russell, 2010 ; Zamawe, 2015 ). Photographic data were coded for the physical developments of the solutions (e.g. adding/removing materials in particular places) allowing solution development to be mapped for different groups over time. Triangulation of data also allowed coding to capture whether individual developments enhanced or detracted from the overall function efficacy of the solution.

The first stage of analysis was immersive, beginning with an initial codebook derived from the conceptual framework. In response to the data this iteratively shifted to a more inductive mode. To sensitise the analysis to differences, the most successful and the least successful groups were compared first as is discussed by Strauss 1987 (Miles & Huberman, 1994 , p.58). Three frameworks of differences emerged from this: (1) epistemic differences, (2) process differences, and (3) social and extrinsic differences. These were then applied to dyads of decreasing contrast and successively  refined in response to how these differences were reflected in the wider data set. Seven complete passes allowed non-profitable codes to be omitted and frameworks to be finalised. A final stage summarised differences across all groups.

Analysis and findings

The analysis and findings are presented in two main parts: (1) findings from the learning phase, and (2) findings from the problem-solving phase. Verbal data forms a core data source throughout and coding includes both counts and durations (in minutes and seconds). Direct quotations are used from verbal data, although the pupils involved in the study were from regions of Scotland with differing and often very strong local dialects. Quotations are therefore presented with dialect effects removed:

Example data excerpt reflecting dialect: “See instead-e all-e-us watchin’, we could all be doin’ su-hum instead-o watchin’ Leanne..” Example data excerpt with dialect removed: “See instead of all of us watching, we could all be doing something instead of watching Leanne..”

Part 1: Findings from the Learning Phase

Both teacher and researcher observation confirmed that pupils in all three classes engaged well with the unit of work (50 pupils across 13 groups) with all 40 content indicators covered by each class. Teachers of classes 1 and 3 commented that the lesson pace was slightly faster than pupils were used to. As expected, different teaching styles and examples were between classes, but all pupils completed the same unit activity sheets. The teacher of class 2, for example, used man-made structures and insect wings to explore triangulation; and the teacher in class 3 talked about the improved stability pupils get by standing with their feet apart. The understanding reflected in activity sheets was very good overall and Table 2 illustrates the percentage of correct responses for each class in relation to each of the three core concept areas.

Though unit activity sheets are not standardised tests, the conditions of administration, scoring, standards for interpretation, fairness and concept validity discussed by Gall et al. ( 2003 , p.xx) were maintained as far as possible. Evidence did not show that representational/stylistic variations by teachers had any discernible effect on pupil understanding and was seen to maintain normality from the pupils’ perspective. Class 3 scored consistently highly across all conceptual areas, although the qualitative understanding of turning moments was least secure for all three classes. Non-completion of selected questions in the task sheets partially explains lower numerical attainment for this concept in class 1 and 2, however, it is unknown if omissions resulted from a lack of understanding. The figures in Table 2 are absence corrected to account for fluctuating pupil attendance at sessions: (17.6% pupil absence across sessions for class 1, compared with 8.8% and 2.5% for classes 3 and 3 respectively). Table 3 illustrates the percentage scores for activity sheets completed by groups in the more and less successful cohorts.

Observational and reflexive data highlighted evidence of some researcher and recorder effects. These were typically associated with pupils’ interest in understanding the roles of the researcher and class teacher, and discussion around what they could say while being recorded. These subsided over time for all but two groups in Class 1, but with no substantive effect on pupils’ technological thinking.

In summary, findings from the learning phase show that: (1) Pupils engagement was high, and all classes covered the core structural concepts in the unit; (2) pupil knowledge and understanding, as measured by activity sheet responses, was very good overall but scores for turning moments were comparatively lower, and (3) study effect subsided quite quickly for all but two groups and there was no evidence showing these to be detrimental to technological thinking. These differences are considered epistemic and are captured in the framework of difference in Fig. 5 .

Part 2: findings from the problem-solving phase

Part 2 begins by describing the differences from comparing the material solutions produced by the most and least successful groups (dyad 1). Subsequent sections report upon the three areas in which difference were found: epistemic differences, process differences and social and extrinsic differences. Each of these sections lead with the analysis from the most contrasting groups (dyad 1) before presenting the resultant framework of difference. They conclude by reporting on how the differences in these frameworks are reflected across the wider data set. As with findings across all sections, findings only account for areas of the conceptual framework in which differences were identified. For processes such as measuring and testing, no difference was found and other processes, such as computing, did not feature for any of the groups.

Differences in the solutions produced by the most & least successful groups (dyad 1)

Group 5′s solution was identified as the most successful and Group7′s solution was identified as the least successful. Overall, both of these groups engaged well with the task and produced cantilevers that are shown in Figs. 2 and 3 . The order in which different parts of the solutions were developed is indicated by colour with the lighter parts appearing earlier in problem solving than the darker parts. Figure 4 shows this cumulative physical development of each solution over time. Both groups shared a similar conceptual basis and employed triangulation above and below the road surface. Figure 4 shows that Group 5′s solution evolved through 36 developments, while Group 7 undertook 23 developments and chose to strip down and restart their solution at the beginning of the second problem solving session. Similarly, groups 6, 11 and 13 removed or rebuilt significant sections of their solution. Neither group 5 or 7 undertook any developments under the rear of the road surface, and the greatest percentage of developments applied to the road surface itself (Group 7: 30.6%; Group 5: 47.8%). For Group 5, it was only developments 5 and 6 (Fig. 2 ) which offered little to no functional structural advantage. All other developments contributed to either triangulation, rigidity or strength through configuration and material choice with no evidence of misconception, which was also noted by the Delphi panel. The orientation, configuration and choice of materials by Group 7 share similarities with Group 5 insofar as each reflected knowledge of a cognate concept or principle (e.g. triangulation). Delphi Panel Member 8 described Group 7′s solution as having a good conceptual basis. Key differences, however, lay in the overall structural integrity of the solution and the underdevelopment of the road surface (Fig. 3 , Dev.1 and Dev.5) which mean that Group 5 achieved a more ontologically endurant solution than Group 7 did. Evidence from Group 7′s discussion (S = 3, 3.34–3.37; S = 3, 3.38–3.39; S = 16, 3.26–3.30) suggests this is partly because of misconception and deficits in knowledge about materials and the task/cantilever requirements. This was also reflected in the group’s activity responses during structures unit in the learning phase. Alongside the photographic evidence and reflexive notes of the researcher, this suggest that there was  some difficultly in translating concepts and ideas into a practical form. This constitutes a difference in tacit-procedural knowledge between Group 5 and Group 7.

‘Group 5 solution schematic’

‘Group 7 solution schematic’

‘Cumulative development of tangible solutions’

Epistemic differences during problem solving

As well as the knowledge differences in the learning phase and the physical solutions, analysis of the most and least successful groups revealed epistemic differences in problem solving activity related to ‘task knowledge’ and ‘knowledge of concepts and principles’. The extent to which ‘knowledge’ can be reliably coded for in this context is limited because it rapidly becomes inseparable from process. Skills are processes which, in turn, are forms of enacted knowledge. Consequently, although Halfin ( 1973 ) defines idea generation as a knowledge generating process using all the senses, attempts to code for this were unsuccessful because it was not possible to ascertain with any confidence where one idea ended, and another began. Coding was possible, however, for ‘prior personal knowledge’, ‘task knowledge’ and ‘prior technological knowledge’. The analysis of these is present along with the resulting framework of epistemic difference with prior personal knowledge omitted on the basis that no differences between groups was found. The final section looks at how epistemic differences are reflected in the activity of the remaining groups.

Epistemic differences between the most & least successful groups (dyad 1)

Task knowledge is the knowledge pupils have of the problem statement and includes relatively objective parameters, conditions, and constraints. One key difference was the extent to which groups explicitly used this to support decision making. Group 5 spent considerably more time than Group 7 discussing what they knew and understood of the task prior to construction (1m10s vs. 8 s) but during construction, had more instances where their knowledge of the task appeared uncertain or was questioned (n = 6 for Group 5 vs. n = 2 for Group 7). Differences were also found in the prior technological knowledge used by groups. This knowledge includes core structural concepts and principles explored in the learning phase. As with task knowledge, Group 5 verbalised this category of knowledge to a far greater extent than Group 7, both apart from, and as part of, formative discussions with the class teacher (18:59 s vs. 14:43 s). In only one instance was the prior technological knowledge of Group 5 incorrect or uncertain compared with four instances for Group 7. These included misconceptions about triangulation and strength despite performing well with these in the learning phase. Furthermore, some instances of erroneous knowledge impacted directly upon solution development. In response to a discussion about rigidity and the physical performance of the road surface, one pupil stated: “Yes, but it is supposed to be able to bend in the middle..” (Group 7, S = 3, 3.34–3.37) meaning that the group did not sufficient attend to this point of structural weakness which resulted in a less endurant solution. No such occurrences took place with Group 5. More prominent and accurate use of this type of knowledge supports stronger application of learning into the problem-solving context and appeared to accompany greater solution integrity.

From these findings, and those from the learning phase, the framework of difference shown in Fig. 5 was developed:

‘Framework of epistemic differences from comparative analysis of Group 5 and 7’

Epistemic differences across all groups (dyads 1–4)

As with dyad 1, the more successful groups in dyads 3 and 4 scored higher (+ 14% and + 20.7%, respectively) in the learning phase compared with their less successful partner groups. This, however, was not seen with dyad 2. The less successful group achieved a higher average score of 86.3% compared with 71% and, despite greater fluctuations in pupil attendance, scored 100% for turning moments compared with 58% for the more successful group. Although comparatively minimal across all groups, more successful groups in each dyad tended to explicitly verbalise technological and task knowledge more than less successful groups. Furthermore, it was more often correct or certain for more successful groups. This was particularly true for dyad 2, although there was some uncertainty about the strongest shapes for given materials in, for example, Group 12 which was the more successful group of dyad 3. The greatest similarity in verbalised task knowledge was observed with the least contrasting dyad, although evidence from concept sketching (Figs. 6 , 7 ) illustrated a shared misunderstanding between both groups of the cantilever and task requirements.

‘Group 2 concept sketch’

‘Group 8 concept sketch’

The differences in tacit-procedural knowledge between Group 5 and 7 were reflected quite consistently across other dyads, with more successful groups showing greater accuracy, skill and judgement in solution construction. The more successful groups in dyads 2 and 3 undertook three material developments that offered little to no functional advantage, and each of the developments these groups undertook correctly embodied knowledge of cognate structural concepts and principles. Notably, Group 8 of dyad 4 was able to achieved this with no structural redundancy at all. Less successful groups, however, were not as secure in their grasp of the functional dependencies and interrelationships between different parts of their structural systems. The starkest example of this was with Group 4 of dyad 3, who explicitly used triangulation but their failure to physically connect it with other parts of the structure rendered the triangulation redundant. Group 2 of dyad 4 were the only group not to triangulate the underside of the road surface. Less successful groups tended to focus slightly more of their material developments in areas of the bridge other than the road surface, whereas the opposite tended to be true for the other groups. Significantly, while all groups in the study included developments that offered little to no functional advantage, it was only in the case of less successful groups that these impaired the overall functional performance of solutions in some way. Table 4 summarises the sustained epistemic difference across all four dyads.

Process differences

Analysis of the most contrasting dyad yielded process differences in: (1) managing (Halfin, 1973 ), (2) planning, and (3) reflection. Groups managed role and task allocation differently, as well as engaging in different approaches to planning aspects of solution development. Reflection, as a process of drawing meaning or conclusions from past events, is not explicitly identified by Halfin or the conceptual framework. Two new forms of reflection for well-defined technological problem solving (declarative reflection and analytical reflection) were therefor developed to account for the differences found. The analysis of the process differences is presented with the resulting framework for this dyad. The final section presents sustained process differences across all groups.

Difference in managing—role & task allocation & adoption (dyad 1)

The autonomous creation of roles and allocation of tasks featured heavily in the activity of Group 5. These typically clustered around agreed tasks such as sketching (S = 2, 1.46), and points where group members were not directly engaged in construction. In total, Group 5 allocated or adopted roles or task on 31 occasions during problem solving compared with only 7 for Group 7. Both groups did so to assist other members (Group 5, S = 16, 3.33–3.38; Group 7, S = 3, 0.37–0.41), to take advantage of certain skills that group members were perceived to possess (Group 5, S = 2, 1.47- 1.49; Group 7, S = 2, 2.03–2.06) and, for one instance in Group 7, to prevent one group member from executing something incorrectly (S = 16, 2.11–2.13). There was evidence, however, that Group 5 moved beyond these quite pragmatic drivers. Member often had more of a choice and, as shown in Excerpt 5, allocation and adoption is mediated by sense of ownership and fairness.

Excerpt 5: Idea Ownership (Sketching) Pupil ?: “You can’t draw on them..” Pupil 1: “You draw Chloe, I can’t draw..” Pupil 2: “I know I can’t draw on them, that’s why I doing them; no, because you, you had the ideas… because you had…” Pupil ?: “(unclear)” Pupil 3: “Just draw your own ideas, right, you can share with mine right…. Right, you draw the thread one, I’ll do the straw thing…” (Group 5, S  =  2, 1.46–1.59)

The effective use of role and task allocation appeared to play an important role in realising an effective technical solution, however, negative managerial traits were perhaps more significant.

Difference in managing—negative managerial traits (dyad 1)

Evidence of differences between Group 5 and 7 were found in relation to: (1) group involvement, and (2) fragmentation of group vision, which were found to be highly interrelated. Negative group involvement accounted for traits of dominance and dismissiveness. For Group 7, this was more prevalent earlier in the problem-solving activity where one group member tended to dominate the process. This pupil tabled 9 out of 11 proposals prior to working with physical materials and, at times, readily dismissed suggestions by other group members (See Excerpt 1). Moreover, ideas and proposals within the group were sometimes poorly communicated (Excerpt 2), which led to a growing level of disenfranchisement for some group members and a fragmented group vision for solution development.

Excerpt 1 Pupil 1:“We could do it that way…” (Pupils continue discussion without acknowledgement) Pupil 1:“You could do that..” Pupil 2:“Shut up, how are we going to do that?” Pupil 1:“Well you’re allowed glue, and you’re allowed scissors..” Several group members: “Shut-up!” (Group 7, S = 1, 2.07–2.28) Excerpt 2 “(Loud inhalation) Watch my brilliant idea… I need scissors.. Are you allowed scissors?” (Group 7, S = 1, 1.36–1.41)

The was some evidence of dismissiveness present with Group 5 also (e.g. S = 9, 1.32–1.46), however, group members were able to voice their ideas which appeared to support a better shared understanding among group members. Notably, Group 5 reached a degree of consensus about what they would do prior to constructing anything, whilst Group 7 did not. Even in these early stages, two of the four members of Group 7 made it very clear that they did not know what was happening (Excerpt 3).

Excerpt 3 Pupil 1: “What are you all up to?” Pupil 2: “Move you” Pupil 4: “No idea” Pupil 2: “You’re allowed to say hell are you not?” Pupil ?: “Helli-yeh” Pupil 2: “Hellilouya” (slight laughter) Pupil 3: “Right so were going to..(unclear) and do that..” Pupil 1: “What are you all up to?” Pupil 2: “Just… I know what he’s thinking of..” Pupil 4: “I don’t have a clue what you’re thinking of..” Pupil 3: “Neither do I..” (Group 7, S = 2, 0.15–0.33)

Occurrence like these contributed to a growing sense of fragmentation in the group. Verbal and observational data show this to have been picked up by the class teacher who tried to encourage and support the group to share and discussed ideas more fully. Despite this, the group lost their sense of shared vision about how to approach a solution and, part way through the first session, two group members attempted to begin developing a separate solution of their own (S-3, 2.52).

The final managerial difference between Group 5 and 7 was the way in which efforts were made to increase the efficiency of solution development. Seen as a positive managerial trait, both groups did this, but it was more frequent and more developed with Group 5. There were four examples of this with Group 7 in the form of simple prompts to speed the process up (E.g. S = 5:3.02–3.04; S = 6:2.22–2.23; S = 11: 1.34–1.35) and 25 examples with Group 5 involving prompts and orchestrating parallel rather than successive activity.

Differences in planning (dyad 1)

Differences emerged in how Group 5 and 7 thought about and prepared for future problem-solving activity. While the complexity of the pupils’ problem-solving prevented cause and effect from being attributed to planning decisions, four areas of difference were identified: (1) determining use of/amount of materials/resources, (2) sequencing, ordering or prioritising, (3) identification of global solution requirements, and (4) working through how an idea should be practically executed. Across both problem-solving sessions, Group 5 spent over three times as long as Group 7 did, engaging in these forms of planning (8m17s vs. 2.23 s), but Group 7 planned on almost twice as many occasions (n = 98 vs. n = 56). Both groups considered the availability of materials for, and matching of materials to, given ideas (e.g. Group 5, S = 5:3.38–3.48; Group 7, S = 4:2.20–2.34; S = 12:1.53–2.00) and both identified global solution requirements. At the start, Group 5 engaged in 12 min of planning in which they read task instructions (S = 1, 0.49–1.49), explored, tested, and compared the available materials (S = 1, 1.49–2.10), and agreed on a starting point. As shown in Excerpt 4, these discussions attempted to integrate thinking on materials, joining methods, placement. As the class teacher observed, Group 7 were eager to begin construction after 4m45s and did so without an agreed starting point. Pupils in this group explored materials in a more reactive way in response to construction.

Excerpt 4 “..a tiny bit of cardboard, right, this is the cardboard, right.. (picks up part) put glue on it so that’s on that, right.. (modelling part orientation) then put glue on it there so it sticks down.. something to stick it down, do you know what I mean?” (Group 5, S = 9, 2.10–2.20)

Despite similar types of planning processes, the planning discourse of Group 5 was more proactive, and this may have minimised inefficiencies and avoidable errors. For Group 7, two group members unintentionally drew the same idea (S = 2, 3.19–3.26), parts were taped in the wrong place (S = 17, 1.26–1.40) and others glued in the wrong order (S = 5, 1.28–1.30 and 1.48–1.56). Such occurrences, however, notably reduced after the group re-started their solution in the second session which also mirrored a 73% drop in poor group involvement. Communication played an important role in planning and there was no evidence of avoidable errors with Group 5.

Differences in reflection (dyad 1)

The most prevent differences in this study were found in how Group 5 and Group 7 reflected upon their developing solutions. Analysis revealed two main forms of reflection that were used differently by groups. ‘Declarative reflection’ lies close to observation and is defined by this study as reflection that does not explicitly reveal anything of a pupil’s knowledge of technical relationships within their solution, e.g.: “that’s not going to be strong…” (Group 7, S = 2, 0.49–0.51). This form of reflection was critical for both groups who used it heuristically to quality assure material developments, but it was used slightly more often by Group 7 (n = 164:4m30s vs. n = 145:4m07s). By contrast, ‘analytical reflection’ is defined as that which does reveal something of a pupil’s knowledge of technical relationships between two or more parts of a solution. Examples of this are shown in Excerpts 5 and 6 where pupils are reflecting upon an attempt made to support the underside of the road surface.

Excerpt 5: “It’s not going to work because it’s in compression and straws bend..” (Group 5, S = 9, 2.3–2.35) Excerpt 6: “no, that’ll be… oh, aye, because that would weight it down and it would go into the water.” (Group 5, S = 14, 3.35–3.38)

Looking across verbal and observational data, there was no consistent pattern to the use of declarative reflection but analytical reflection for both groups was almost exclusively anchored around, and promoted by, the practical enactment of an idea and could be associated with predictions about the future performance of their solution. Overall, both Group 5 and 7 reflected a similar number of times (n = 216 and n = 209, respectively) although the total amount of time spent reflecting was 17% longer for Group 5. This difference in time was accounted for by comparatively more analytical reflection in Group 5 (n = 75:3m47s vs. n = 45:2m10s for Group 7), particularly during the first half of problem solving. It was also interesting that Group 7 engaged with no analytical reflection at all prior to construction.

Findings from process management, planning and reflection led to the framework of difference in Fig. 8 . This also accounts for differences in the amount of time each group reflected upon the task detail, but this was extremely limited (Group 5: n = 7, 26 s; Group 7: n = 5, 10 s).

‘Framework of process differences from comparative analysis of Group 5 and 7’

Process differences across all groups (dyads 1–4)

Task reflection, attempts at increasing efficiency and differences of fragmented vision found with the most contrasting dyad were not sustained across remaining groups. The only sufficiently consistent difference in patterns of solution development was that more successful groups, on average, spent 18% longer in planning and discussion before beginning to construct anything.

Overall, the nature and patterns of good and poor group involvement from dyad 1 were reflected more widely, with some instances of deviation. The more successful group in dyad 4 had more significant and numerous examples of poor group involvement than did the less successful group (n = 16 vs. n = 10), although they made more effective use of roles and task allocation and spent longer engaged in planning processes. Dyad 2 deviated also insofar as the less successful group (13) actually had fewer avoidable errors than Group 6 who accidentally cut the incorrect parts (e.g. S = 15, 2.44–2.47), undertook developments that were not required (e.g. S = 6, 2.11–2.16) and integrated the wrong parts into their solution (e.g. S = 7, 1.10–1.13).

Differences in the nature and use of reflection was one of the most consistently sustained findings between the most and least successful cohorts. All four of the more successful groups engaged more heavily in reflective processes and more of this reflection was analytical in nature. This shows that reflection which explicitly integrates knowledge of technical relationships between different aspects of a solution plays an important role in more successful technical outcomes. Whilst declarative reflection remained important for all groups, it was also less prominent for groups in the less successful cohort. Table 5 summarises the sustained process difference across dyads 1, 2, 3 and 4.

Social & extrinsic differences (dyad 1)

Differences reported in this section lie out with the formal conceptual framework of the study but, nonetheless, were shown to play a role in the technological problem-solving activity of dyad 1. Differences between Group 5 and 7 emerged in three areas: (1) group tension, (2) effects of the classroom competitive dynamic, and (3) study effects. Group tension, which relates to aspects of interaction such as argumentative discourse, raised voices and exasperation, were negligible for Group 5 (n = 4, 0m24s) when compared with Group 7 (n = 38, 2m38s) and related exclusively to pupils having their voiced heard. For group 7, tension was evident during both sessions, but was more significant in the first session before re-starting the solution in session 2 and purposeful attempts to work more collaboratively with the support of the teacher (Group 7, S = 10, 0.36–1.29). Observations revealed that tension was typically caused by pupils failing to carry out practical processes to the standard of other group members, or breaking parts such as the thread supporting the road surface in the 36 th minute of Session 2.

Despite collaborative efforts within groups, there was a sense of competitive dynamic which appeared either to positively bias, negatively bias, or to not affect group activity. This competitive dynamic was present in groups comparing themselves to other groups in the class. Group 7 had 3.7 times as many instances of this as Group 5 with 73% of these negatively affecting the group. These included interference from and with other groups (S = 7, 0.07–0.12), attempting to copy other groups (S = 7, 1.14–1.22) and comparing the solutions of other groups to their own (S = 8, 2.55–2.59). In contrast, Group 5 appeared to be far less affected by perceptions of competition. Around a third of instances were coded as neutral, however, Group 7 experienced more instances of positive competitive effects than Group 5 did (n = 5 vs. n = 1).

Study effects were present for both groups often triggered by the arrival of the researcher at their table to observe or take photographs. The biggest difference in study effects was associated with the audio recorder. Recorder effects for Group 7 were three and half times that of Group 5 involving discussion about how it worked (Group 7, S = 10, 3.04–3.17), or about what was caught or not caught on tape (Group 7, S = 14, 1.01–1.45). Although questionnaire data showed that pupils in Group 5 felt that they talked less in the presence of the recorder, this was not supported by observations, verbal data, or the class teacher. From these findings, the framework of social and extrinsic difference in Fig. 9 was developed.

‘Framework of social & extrinsic differences from comparative analysis of Group 5 and 7’

Social & extrinsic differences across all groups (dyads 1–4)

Most of the social and extrinsic differences identified with Groups 5 and 7 were reflected to greater or lesser extents in other dyads. In addition to less successful groups being more susceptible to researcher and recorder effects, two specific points of interest emerged. Firstly, group tension was considerably more prominent for less successful groups than it was for more successful groups. Although no evidence of a direct relationship was established, tension appeared to accompany poor managerial traits and the changing of group composition (e.g. Group 8, Group 13). The most significant differences in tension were found with dyad 3. No occurrences were found for the most successful group and 29 were seen with the least successful group including aggressive and abrupt communication between pupils involving blame for substandard construction (S = 10, 2.28–2.38), through to name calling (S = 12, 0.20–0.22), arguing (S = 6, 1.46–2.10) and threats of physical violence (S = 11, 3.25–3.29).

Secondly, the more successful groups were influenced by the competitive class dynamic more than the less successful groups were. This is the only sustained finding that directly opposes what was found with dyad 1. These took the form of neutral or negative inter-group effects involving comparing and judging other groups (e.g. Group 6), espionage, copying or suspicion thereof (e.g. Group 6, 8 and 12). Table 6 summarises the sustained social and extrinsic differences across the more and less successful cohorts.

Discussion and Conclusions

This study established and applied three frameworks to capture the epistemic, procedural, and social and extrinsic differences between groups of pupils as they developed solutions to a well-defined technological problem. Social & extrinsic findings revealed higher levels of group tension for the less successful cohort, but that more successful groups elicited more negative responses to the competitive class dynamic created by different groups solving the same problem. Major findings about differences in knowledge and process are discussed. Thereafter, a three-part characterisation of thinking for well-defined technological problem solving is presented in support of pedagogy for Design & Technology classrooms.

The most important of those knowledge differences uncovered were found in: (1) the material development of the solution itself, and (2) the reflective processes used by groups during problem solving. The conceptual framework characterises ‘tacit-procedural knowledge’ as the implicit procedural knowledge embodied in technical skill, accuracy and judgement, and this was further refined in the solutions of more successful groups. Linked to this was the fact that several of the material developments for triangulation and strength were improperly realised by less successful groups which negatively impacted on the functional performance of their solutions. Often, this was despite evidence of a good conceptual understanding of triangulation, tension, and compression in the learning phase. An ontologically endurant solution requires stability over time and lesser developed aspects of tacit-procedural knowledge and knowledge application meant that this was not realised as fully as possible for some groups.

This can be partly explained by the challenge of learning transfer, or more accurately, learning application. Several notable studies have explored these difficulties in technology education (Brown, 2001 ; Dixon & Brown, 2012 ; Kelly & Kellam, 2009 ; Wicklein & Schell, 1995 ), but typically at a subject or interdisciplinary level. The findings of this study suggest that, even when the concepts in a learning unit are tightly aligned with a well-defined problem brief, some pupils find difficulty in applying them within a tangible, material context. It could be argued that more successful groups were better at connecting learning between different contexts associated with the problem-solving task and could apply this with more developed skill and judgement.

The second important knowledge difference arose in the various forms of reflection that groups engaged with. Reflection in this study supports pupils in cycling through the re-application/transformation loop in a similar way to the perception/translation/evaluation blocks of the iterative models of problem solving (Argyle, 1972 ; Miodusre & Kipperman, 2002 ; Scrivener et al., 2002 ). Surprisingly few studies explore ‘reflection’ as a process in technological thinking (Kavousi et al., 2020 ; Luppicini, 2003 ; Lousberg et al., 2020 ), and fewer still in the context of school-level technological problem solving. This study found that more successful groups reflected more frequently, and that more of this reflection was analytical insofar as it explicitly revealed knowledge of technical relationships between different variables or parts of their solution. Such instances are likely to have been powerful in shaping the shared understanding of the group. This type of reflection is significant because it takes place at a deeper level than declarative reflection and is amalgamated with pupils’ subject knowledge and qualitative understanding of their technical solution. This allowed pupils to look back and to predict by explicitly making connections between technical aspects of their solution.

The final area in which important differences were found was management of the problem-solving process which is accounted for by Halfin ( 1973 ) in his mental process set. When analysed, the more successful cohort exploited more positive managerial strategies, and fewer negative traits. They made more extensive and effective use of role and task allocation, spent more time planning ahead and longer in the earlier conceptual phase prior to construction. Other studies have also captured aspects of these for technology education. Hennessy and Murphy ( 1999 ) discuss peer interaction, planning, co-operation and conflict, and changing roles and responsibilities as features of collaboration with significant potential for problem solving in technology. Rowell ( 2002 ), in a study of a single pair of technology pupils, demonstrated the significance of roles and participative decisions as enablers and inhibiters of what pupils take away from learning situations. What was interesting about the groups involved in this study, was that the managerial approaches were collectively more proactive in nature for more successful groups. Less successful groups were generally more reactive to emergent successes or problems during solution development.

The problem-solving activity of pupils in this study was exceptionally complex and a fuller understanding of how these complexities interacted would have to be further explored. Yet, key differences in knowledge and process collectively suggest that effectively solving well-defined technological problems involves a combination of proactive rather than reactive process management, and an ability to make two different types of technology-specific connections: contextual connections and technical connections. Proactively managing is generic and involves planning, sequencing, and resourcing developments beyond those that are immediately in play to minimise avoidable errors with reference to problem parameters. It involves group members through agreed roles and task allocation that, where possible, capitalise on their strengths. Contextual connections involve effectively linking and applying technological knowledge, concepts, and principles to the material context that have been learnt form other contexts out with solution development. This is supported by skill and judgement in the material developments that embody this knowledge. Finally, technical connections appear to be important for better functioning solutions. These are links in understanding that pupils make between different parts of the developing solution that reveal and build knowledge of interrelationships, dependencies and how their solution works. In addition to helping pupils developing effective managerial approaches in group work, this suggests that pedagogical approaches should not assume pupils are simply able to make contextual and technical connections during technological problem solving.  Rather, pedagogy should actively seek to help pupils make both forms of connection explicit in their thinking.

This study has determined that proactive management, contextual and technical connections are important characteristics of the modus operandi of pupils who successfully solve well-defined technological problems. This study does not make any claim about the learning that pupils might have taken from the problem-solving experience. It does, however, provide key findings that teachers can use to support questioning, formative assessment and pedagogies that help pupils in solving well-structured technological problems more effectively.

Ethical approval

Ethical approval for this study was granted by the School of Education Ethics Committee at the University of Glasgow and guided by the British Educational Research Association Ethical Code of Conduct. All necessary permissions and informed consents were gained, and participants knew they could withdraw at any time without giving a reason. The author declares no conflicts of interest in carrying out this study.

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Acknowledgements

I would like to thank Dr Jane V. Magill, Dr. Alastair D. McPhee and Professor Frank Banks for their support in this work as well as the participating teachers and pupils who made this possible.

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Morrison-Love, D. Technological problem solving: an investigation of differences associated with levels of task success. Int J Technol Des Educ 32 , 1725–1753 (2022). https://doi.org/10.1007/s10798-021-09675-5

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Accepted : 25 April 2021

Published : 02 June 2021

Issue Date : July 2022

DOI : https://doi.org/10.1007/s10798-021-09675-5

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