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4 references
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- Vol 1 RE: Chapter 3
- Vol 4 RE: Chapter 3
learning stylesaptitude-treatment interactionsinstructional matchinglearning preferencesevidence-based instructionprior knowledgeaccessibilityJournal article Evidence summaryAt a glance
Pashler and colleagues evaluate the educational claim that students learn better when instruction is matched to a diagnosed learning style. They distinguish preferences and differences in aptitude from the stronger “meshing” hypothesis used to justify tailored teaching.
Key ideas
A valid test requires classifying learners by style, randomly assigning learners within each style to contrasting instructional methods, using a common outcome measure, and finding a crossover interaction in which each group learns best from its matched method. Their review found that very few studies used this design and that the qualifying evidence did not support broad classroom use of learning-style assessments; some appropriate studies directly contradicted the hypothesis. The authors do not claim that learners are identical, that preferences are unreal, or that every possible interaction has been disproved. Rather, evidence was inadequate to justify the cost and instructional consequences of general matching programmes.
Why it matters
For educators, content, prior knowledge, accessibility, and well-supported teaching methods provide firmer grounds for choosing representations than labels such as visual or auditory learner.
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- Vol 3 RE: Chapter 4
prior knowledgeexplanatory questioningprediction questionselaborative interrogationinferential learningmisconception correctionknowledge integrationJournal article Evidence summaryAt a glance
Pressley and colleagues review four increasingly rigorous lines of evidence for the claim that attempting to construct explanatory answers improves learning. Correlational studies first show that students who provide explanations during group work tend to learn more.
Key ideas
Experimental manipulations that increase explanation during interaction then produce better outcomes. Research on prediction questions suggests that trying to anticipate upcoming text can activate and reorganise relevant prior knowledge. Finally, elaborative-interrogation experiments show benefits when learners answer “why” questions about facts, especially when their knowledge permits plausible connections. The proposed mechanism is mindful inferential transformation: learners do more than repeat information by linking it to what they know, identifying relations, and constructing a coherent account. Success depends on relevant prior knowledge and the quality of the generated explanation; attempts can fail or introduce error when learners lack a sound basis.
Why it matters
For educators, explanation prompts are most useful when questions target important relations, students have enough background knowledge, answers are checked, and discussion or feedback corrects misconceptions. The review presents promising but then-preliminary evidence rather than a universal guarantee.
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- Vol 4 RE: Chapters 7, 14
- Vol 7 PE: App D
worked examplescognitive loadfading guidanceproblem solvingschema constructionbackward fadingself-explanationprior knowledgeJournal article Evidence summaryAt a glance
Renkl and Atkinson address how instruction should move from studying worked examples to independent problem solving. Early in skill acquisition, conventional problem solving can overload working memory because novices must search for solution steps while also trying to learn underlying principles.
Key ideas
Complete worked examples reduce unproductive search and support schema construction. As knowledge develops, however, repeatedly studying complete solutions becomes redundant and may impede active learning; learners need increasing responsibility for producing steps. The authors propose fading: begin with fully worked solutions, then successively omit steps that students must complete until they solve entire problems. Backward fading can align with the natural subgoal structure of some domains, while prompts for self-explanation help learners process principles rather than imitate procedures.
Why it matters
The transition should be adapted to prior knowledge because support that helps novices can become extraneous for more advanced learners. For educators, the implication is a planned continuum, not an abrupt switch between explanation and practice: model the process, remove support gradually, require explanation, monitor success and mental effort, and adjust the pace of fading.
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- Vol 5 RE: Chapter 8
retrieval practicegenerative learningfollow-up learning tasksknowledge constructionlearning task sequencingfeedback designprior knowledgemetacognitive mechanismsJournal article Evidence summaryAt a glance
Roelle and colleagues examine the underdeveloped relationship between retrieval-practice research and generative-learning research.
Key ideas
Retrieval is typically used to consolidate accessible memory representations, whereas activities such as explaining, mapping, drawing, or generating examples aim to construct or reorganize understanding. Because these functions may complement one another, the authors use follow-up learning tasks to analyze when retrieval can prepare learners for later generative activity and when generative activity can enrich subsequent retrieval. They distinguish direct effects on practiced material from indirect effects on new learning, discuss cognitive and metacognitive mechanisms, and identify design variables such as sequencing, feedback, task demands, and prior knowledge.
Why it matters
The paper calls for experiments that explicitly integrate the two research traditions instead of comparing isolated techniques, with the goal of designing combinations whose processes and boundary conditions are theoretically understood.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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