How to approach problems you have not seen before — understanding what the problem actually is, generating possible solutions, choosing the most promising, and learning from what happens. Problem solving is not about knowing the answer. It is about knowing how to find it.
Problem solving at Early Years level is about building the foundational disposition towards problems — the belief that problems can be solved, the habit of trying more than once, and the willingness to ask for help and try different approaches. Young children encounter genuine problems every day — how to share resources fairly, how to build something that keeps falling down, how to communicate a need that is not being understood, how to manage a conflict with a friend. These are real problems with real solutions and they are the ideal material for problem-solving education. The most important teaching move at this level is to resist solving problems for children. When a child encounters a problem — a block construction that keeps falling, a conflict over materials, a misunderstanding with a friend — the teacher's first response should be: what have you tried? What could you try next? only solving for the child when genuine help is needed removes the learning opportunity. The second most important move is to celebrate persistence: the child who tries five different approaches before finding one that works is learning more about problem solving than the child who finds the answer immediately. In low-resource settings, problems of a practical and material nature are daily realities — finding water, making things work with limited materials, resolving community disputes, managing shared resources. These are excellent material for problem-solving education and should be honoured as such rather than substituted with imported problems from wealthy-world contexts.
Three connected drawings showing the problem, an attempt (or attempts), and the solution. The completion shows that the student tried at least one approach before finding one that worked — not that the first thing worked immediately. Celebrate drawings that show more than one attempt.
Ask: what did you learn from the things that did not work? This question is more important than the solution itself — it builds the habit of treating failures as information.
The problem is that the school gate makes a very loud noise when it opens and it wakes up the babies in the house next door. It affects the family who live there and makes their day harder. One thing I could try is asking if someone could put oil on the hinges to make it open quietly.
Celebrate any genuine problem and any genuine proposed solution, however small or simple. The habit of noticing problems and thinking constructively about them is the goal, not the sophistication of the solution.
If you cannot solve a problem quickly, it means you are not clever enough to solve it.
The speed at which someone solves a problem often reflects familiarity with that type of problem, not raw intelligence. Novel problems — ones you have not seen before — take time for everyone. The people best at problem solving are not those who find answers fastest but those who persist longest and try the most different approaches. Research on expert problem solvers shows they spend more time than novices understanding the problem before attempting a solution — which is slower but more effective.
Asking for help is giving up on solving the problem yourself.
Knowing when to ask for help is itself a problem-solving skill — and an important one. Experienced problem solvers know when a problem is beyond their current tools and when getting input from others will produce a better solution than continuing alone. What matters is how you ask: asking someone to solve the problem for you is different from asking for a hint, a resource, or a perspective that helps you solve it yourself. The ability to use other people and other resources effectively is part of being a good problem solver.
Problems have one correct solution.
Many problems — especially real-world problems — have multiple workable solutions with different trade-offs. The question is not only does this solution work? but which solution works best given the specific constraints, values, and resources available? Often different solutions serve different people's needs differently. The habit of generating multiple possible solutions before choosing one — rather than stopping at the first workable answer — produces better outcomes in almost every domain.
Problem solving at primary level introduces students to a structured process for approaching problems — moving from an intuitive, trial-and-error approach towards a more deliberate and transferable one. The structured problem-solving process has several well-established versions; a practical synthesis for classroom use is: understand the problem (what exactly is the problem? who is affected? what are the constraints?), generate options (produce multiple possible solutions without evaluating them), evaluate options (assess each against the constraints and desired outcomes), implement (act on the chosen solution), and review (did it work? what did you learn?). This process is not a formula to be followed mechanically — it is a set of habits that become more automatic with practice. The most important and most neglected step is the first: understanding the problem properly. Research on problem solving consistently shows that the most common source of poor solutions is not a failure of intelligence but a failure to correctly identify what the problem actually is. People jump to solutions before they understand the problem they are solving — and the solutions they generate are therefore solutions to the wrong problem.
The distinction between tame problems (well-defined, with a clear correct solution) and wicked problems (ill-defined, with multiple stakeholders, no clear correct solution, and where any solution changes the problem) is important for realistic civic education. Most real-world problems — poverty, conflict, environmental degradation, public health — are wicked. Understanding this helps students engage more maturely with why persistent problems persist and why simple solutions usually fail.
The structured process above is the same whether the problem is mathematical, social, practical, or creative. Helping students recognise this — that the same thinking process applies across different types of problem — is one of the most valuable transferable lessons in the curriculum.
Problem: students do not have shade to sit in during the lunch break and spend the hottest part of the day in direct sun. Five Whys root cause: the school was built without shade structures and there is no budget to add them — the root cause is a design and resource decision made when the school was built. Six possible solutions: plant fast-growing trees along the south side; build simple shade structures from locally available poles and thatch; arrange for a large cloth to be stretched between posts; use the corridor of the main building for sitting during the hottest thirty minutes; shift the lunch break to the cooler part of the day; ask families to donate materials for a simple shade structure. Three criteria: must be achievable with no budget; must provide shade within this school year; must not require maintenance that the school cannot provide. Evaluating top three: (1) rearranging lunch break — meets all three criteria immediately; (2) plant trees — meets first and third criteria but not the second, as trees take years to grow; (3) cloth shade — meets all three criteria if cloth can be donated. Recommendation: rearrange the lunch break immediately as it costs nothing and can be done tomorrow, and simultaneously ask the community for cloth donations to build a temporary shade structure this term.
Award marks for: a specific and real problem; genuine root cause identification using the Five Whys rather than just restating the problem; a list that contains creative as well as obvious options; criteria that are specific and genuinely useful for differentiating between options; evaluation that produces a clear recommendation rather than saying all options are equally good; and a recommendation with a clear rationale. Strong answers will recognise when the best solution is a combination of approaches rather than a single one.
In my community, the water point near the market kept running out of water before everyone had collected what they needed. The solution tried was to install a lock on the pump and give only certain families a key, so that use could be controlled. This made things worse because the families without keys had even less access than before, and there were arguments about who deserved a key, which created new conflicts. The root cause — that the water supply was simply not sufficient for the number of people using it — was not addressed at all; the solution only managed the scarcity rather than reducing it. A better approach would have used the Five Whys to find the root cause first (why is there not enough water? because the source is insufficient; why is the source insufficient? because population has grown but the infrastructure has not) and then sought solutions that addressed supply rather than only restricting access.
Award marks for: a specific and genuine example; an honest and specific analysis of why the solution failed — not just it did not work but specifically which step in the problem-solving process was missing or done poorly; and a proposed alternative that genuinely addresses the root cause rather than the symptom. Strong answers will identify that the failed solution addressed the symptom (too many people trying to use too little water) rather than the root cause (too little water), and will propose an approach that includes more stakeholders in defining and solving the problem.
A smart person will be able to see the right solution to a problem immediately.
Expert problem solvers consistently spend more time than novices in the problem understanding phase — before attempting any solution. Research on chess masters, scientists, engineers, and medical diagnosticians all show the same pattern: expertise produces slower, more thorough problem analysis, not faster intuitive leaps. The intuition that experienced problem solvers appear to exercise is actually pattern recognition built from thousands of previous structured attempts — it looks like immediate insight but is the product of accumulated deliberate practice.
Problem solving is a talent — some people are naturally better at it than others.
Problem-solving ability is highly trainable. Research on problem-solving education consistently shows that explicit instruction in problem-solving processes — understanding the problem, generating multiple options, evaluating systematically, reviewing outcomes — produces significant improvements in performance across all ability levels. The structured process in this unit is not a description of how good problem solvers happen to think naturally — it is a learned and practised approach that makes almost anyone a better problem solver.
Once you have found a solution that works, the problem-solving process is complete.
Review — checking whether the solution actually worked and what you learned from it — is the most neglected and one of the most valuable stages of the problem-solving process. Solutions that appear to work often have unintended consequences or only partially address the problem. Regular review produces continuous improvement and prevents solutions from calcifying into problems. The review stage also builds the learning from experience that makes future problem solving faster and more effective.
All problems can eventually be solved if you are persistent and clever enough.
Wicked problems — complex, multi-stakeholder, value-laden social problems — do not have final solutions. They have better and worse management approaches that trade off different values and interests. Recognising that a problem is wicked is not giving up — it is adjusting your approach realistically. For wicked problems, the most important skills are stakeholder inclusion, ongoing monitoring, willingness to adjust, and humility about the limits of any single approach. Treating a wicked problem as if it were tame — by applying a single solution with confidence that it is correct — is one of the most common and most damaging mistakes in governance, development, and community management.
Secondary problem solving engages students with the deeper cognitive, social, and ethical dimensions of problem solving — particularly the ways in which human cognition systematically misleads us, the difference between technical and values-based problems, and the conditions under which collective problem solving is more or less effective than individual.
Research in cognitive psychology and behavioural economics has identified a large number of systematic patterns in human judgment that regularly produce poor problem-solving decisions. The most important for students include: confirmation bias (seeking information that confirms existing beliefs and discounting information that challenges them), anchoring (over-weighting the first piece of information received), availability heuristic (judging the probability of events by how easily examples come to mind rather than by actual frequency), sunk cost fallacy (continuing an unproductive course of action because of investment already made), and functional fixedness (being unable to see uses for objects beyond their usual function). These are not failures of intelligence — they are built-in features of human cognition that affect experts as much as novices. Understanding them is the first step to compensating for them.
Developed at Stanford's d.school and widely applied in business, social sector, and education contexts, design thinking is a human-centred problem-solving approach with five stages: empathise (understand the human experience behind the problem), define (frame the problem from the user's perspective), ideate (generate many possible solutions), prototype (build quick, cheap versions to test), and test (gather feedback and iterate). Its emphasis on genuine empathy with those affected by the problem — rather than assuming you know what they need — distinguishes it from more technical problem-solving approaches and makes it particularly appropriate for social and community problems.
This distinction is one of the most important for civic and political education. Technical problems (how do we build a bridge that will not fall down?) have solutions that can be assessed objectively against physical criteria. Values-based problems (how should we distribute limited healthcare resources between different groups?) require choices between competing values that cannot be resolved by technical analysis alone. Much of the confusion and frustration in public debate arises from treating values-based problems as if they were technical ones — assuming that more evidence will resolve a dispute that is actually about whose values should prevail.
Experts are immune to cognitive biases because of their training and experience.
Research consistently shows that expertise does not eliminate cognitive biases and sometimes amplifies them. Experienced doctors show confirmation bias when diagnosing — their pattern recognition, while usually valuable, can make them close too quickly on a diagnosis that fits their initial impression. Experienced investors are as prone to sunk cost reasoning as novices. The most effective compensation for cognitive bias is structural — building in processes that force consideration of alternative hypotheses, dissenting views, and base rate information — not simply trying to think more carefully.
Groups always make better decisions than individuals because more perspectives are included.
Groups can make better decisions than individuals when they are diverse, when all members contribute freely, and when the group process is designed to prevent premature convergence. But groups can also make dramatically worse decisions than individuals — through groupthink (suppression of dissent), social loafing (reduced individual effort in group settings), cascade effects (later members deferring to earlier ones), and polarisation (groups moving to more extreme positions than any individual held). The conditions for good group decision-making must be actively created rather than assumed to arise naturally.
Better information always leads to better problem solving.
More information does not automatically produce better decisions — it can produce worse ones if it exceeds cognitive processing capacity, if it is selected to confirm existing beliefs, or if the additional information is irrelevant to the actual decision. Research by Barry Schwartz and others shows that expanding the number of options available often produces worse decisions and less satisfaction than limiting choices. The relationship between information and decision quality is non-linear and depends heavily on how information is presented, filtered, and integrated into the decision process.
Problem solving is a purely cognitive skill — emotions are obstacles to clear thinking.
Research by Antonio Damasio and others shows that emotion is not an obstacle to rational decision-making but a necessary component of it. Patients with damage to emotion-processing brain regions cannot make effective decisions even when their logical reasoning is intact — they become paralysed by the inability to assign relative value to options. Emotions provide the motivational and evaluative signal that makes choice possible. Good problem solving requires emotional awareness — particularly the emotions of the people affected by the problem — alongside analytical rigor.
Key texts and resources: Daniel Kahneman's Thinking, Fast and Slow (2011, Farrar Straus and Giroux) is the most comprehensive and accessible account of cognitive biases and their effects on judgment and decision-making — written by one of the founders of behavioural economics and suitable for strong secondary students. Richard Thaler and Cass Sunstein's Nudge (2008, Yale) applies behavioural insights to policy design — useful for understanding structural compensations for bias. For design thinking: IDEO's Design Kit (designkit.org) provides free, practical resources on human-centred design specifically for social impact contexts — directly applicable to low-resource settings. Tim Brown's Change by Design (2009, Harper Business) is the foundational readable account of design thinking. For wicked problems: Horst Rittel and Melvin Webber's original 1973 paper Dilemmas in a General Theory of Planning (freely available online) introduced the concept and remains the most precise treatment. For collective problem solving: Scott Page's The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools and Societies (2007, Princeton) is the most rigorous account of why and when diverse groups make better decisions than homogeneous ones. For decision making under uncertainty: Phil Rosenzweig's The Halo Effect (2007) is the most accessible treatment of how outcome bias distorts learning from business and policy decisions. Annie Duke's Thinking in Bets (2018, Portfolio) applies poker strategy to decision-making under uncertainty in an accessible and engaging way.
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