Problem Solving

Element · All elements
Evidence · 19 claims (9 for, 8 mixed, 2 against) · 28 studies (9 causal, 6 review, 5 theoretical, 3 design, 2 quant-synthesis, 2 qualitative, 1 associational), q1–q4 · 6 of 28 report an effect size · 15 claims rest on one study

Description

Problem solving is the element in which learners identify, analyze, and respond to a challenge by generating and evaluating possible solutions. It is useful when the instructional goal is not only recall, but reasoned action in the face of constraints.

Design Implications

Context

Requirements

• A meaningful problem or challenge
• A process for evaluating possible solutions
• A problem whose solution is not directly retrievable from instruction — learners must reason, not recall
• Prior instruction or resources sufficient to make the problem solvable (Activation of relevant prior knowledge before the task)
• Access to feedback: expert solutions, peer comparison, or instructor coaching after attempted solutions
• A debrief or Self-Explanation prompt that helps learners abstract the underlying principle from their solution path

Constraints

• Ill-structured problems may require stronger scaffolding for novices
• Pure discovery with minimal guidance is less effective than guided problem solving, especially for novices Worked examples reduce unnecessary search for novices. [-M] — unguided search overloads working memory and can reinforce errors
• Ill-structured problems without success criteria leave learners unable to evaluate their own solutions; provide rubrics or exemplars
• High-difficulty problems can demotivate learners who lack self-efficacy; scaffold early success before increasing challenge
• Experts gain little from structured problems and may benefit more from open or novel variants Guidance that helps novices can hinder experts. [~M]

Target Learning Goals

• Develop analytical reasoning, strategy use, and solution generation.
• Analytical reasoning: diagnosing, evaluating, and justifying solution strategies
• Application and transfer: using concepts in novel, realistic contexts Whole-task practice supports transfer better than part-task drill alone. [+M]
• Metacognitive skill: planning, monitoring, and revising an approach over an extended task

Affordances

• Problem-based Learning
• Cognitive Activation
• Active Learning — problem-solving tasks enact this principle by requiring learners to generate and defend solutions rather than receive them, producing the retrieval and elaboration that passive formats omit
• Cognitive Load Management — task sequencing (completion tasks, then near-transfer, then far-transfer) and on-demand hints keep intrinsic load within working-memory limits instead of dumping full complexity on learners at once
• Collaborative Learning — group problem solving exposes learners to alternative solution paths and distributes the reasoning load, provided roles and accountability are structured
• Situated Learning — embedding problems in authentic professional contexts connects the task to the conditions under which the skill will actually be used

Claims

• Functional fixedness — treating an object's or idea's function as fixed — blocks solutions that require reinterpreting it. [+M]
• Productive Failure Improves Conceptual Learning [+W]
• Example–problem sequences reduce cognitive load and improve learning outcomes [+W]
• Usability testing with educators and developers identified chatbot strengths for independent challenge-solving but limited feedback for low-participation learners [+W]
• Problem-based learning connecting coursework and practice is associated with stronger candidate skill development and self-efficacy [+W]
• Evaluating GenAI-generated solutions produced no significant differences on midterm scores, final exam scores, course percentages, or normalized exam change relative to solving problems directly [~W]
• QR faculty on several CSU campuses are incorporating active-learning and problem-solving pedagogies into redesigned entry-level math courses [+W]
• VSDR helped students reflect on and adopt alternative problem-solving approaches to tasks [+W]
• Most students solved BioWorld cases, and successful solvers took less time and fewer actions than unsuccessful solvers [~W]
• Providing contrasting cases reduces the number of solution attempts students generate, both before and after instruction [-W]
• Older adults describe less effective problem-solving solutions, producing fewer relevant steps than younger adults [~W]
• Problem isomorphs with identical structure differ greatly in difficulty; Monster Change took 16 times as long to solve as the standard problem [~W]
• MicroDYN is a stronger predictor of the in-game problem solving estimates than Raven's, with the rule-application facet more relevant than rule acquisition [~W]
• Successful and unsuccessful complex problem solvers differ in transition frequencies between questions and decisions [~W]
• Providing subgoals did not help on the Missionaries and Cannibals problem but facilitated performance on an extended 5-Missionaries and 5-Cannibals variant [~W]

The evidence by question

• How much guidance do novices need inside a problem-centred design? Minimal guidance is less effective for novices than explicit instruction [+S]
• Should learners attempt a problem before the idea is taught, and what must the teaching afterwards do? Productive Failure Improves Conceptual Learning [+M]

Related Elements

• Solution Development
• Decision-Making
• Problem-Based Learning
• Case-Based Learning — a problem-solving task anchored in a rich, realistic case narrative
• Case Studies — published cases that supply the problem context and constraints
• Coaching — the ongoing feedback mechanism that keeps problem solving productive rather than flailing
• Collaboration — the social structure that turns individual problem solving into comparative reasoning

Patterns That Use This Element

• Problem-Based Learning
• Goal-Based Scenarios
• Problem-Based Learning — the problem is the curriculum; tasks drive all content acquisition
• Goal-Based Scenarios — simulated environments where learners pursue a goal and the system responds to their problem-solving moves
• Cognitive Apprenticeship — the exploration phase, where learners tackle problems with decreasing support

Examples

• Learners compare alternative solutions and justify which best fits the constraints of the problem.

Key Sources

• Jonassen, D. H. (2011). Learning to solve problems. Routledge.
• Sweller, J., Kirschner, P. A., & Clark, R. E. (2007). Why minimally guided teaching techniques do not work: A reply to commentaries. Educational Psychologist, 42(2), 115–121. doi:10.1080/00461520701263426
• Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266. doi:10.1023/B:EDPR.0000034022.16470.f3
• Renkl, A. (2014). Toward an instructionally oriented theory of example-based learning. Cognitive Science, 38(1), 1–37. doi:10.1111/cogs.12086
• Jonassen, D. H. (2000). Toward a design theory of problem solving. Educational Technology Research and Development, 48(4), 63–85. doi:10.1007/BF02300500

Page metadata

Field	Value
type	element
id	problem-solving
aliases	problem-solving-tasks
title	Problem Solving
description	Problem solving is the element in which learners identify, analyze, and respond to a challenge by generating and evaluating possible solutions.
status	review
canonical	True
generated	by codex/unspecified on 2026-04-08
trust	unverified — no one has confirmed this page's content

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