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- Vol 2 RE: Chapters 1, 2, 6, 7, 8
- Vol 3 RE: Chapters 3, 5, 8, 9
- Vol 3 TE: App C
- Vol 4 RE: App C
- Vol 4 RE: Chapter 3
- Vol 4 TE: App C
- Vol 7 PE: App D
- Vol 7 RE: Chapters 1, 2, 3, 4, 5, 8, 10, 11, App B, App D
generative learning strategiessummarisingconcept mappingself-testingself-explanationprior knowledgeinstructional scaffoldingguided discoveryBook Evidence summaryAt a glance
Fiorella and Mayer organise research on generative learning around the idea that understanding requires learners to select relevant information, organise it into coherent representations, and integrate it with prior knowledge. They examine eight strategies: summarising, mapping, drawing, imagining, self-testing, self-explaining, teaching, and enacting.
Key ideas
For each, the book reviews cognitive mechanisms, empirical evidence, boundary conditions, and practical guidance. Activities are not effective merely because learners are visibly busy or produce an artefact. Prompts, prior knowledge, task complexity, feedback, and instructional support determine whether an activity elicits productive processing or imposes unhelpful demands. The authors distinguish generative learning from passive exposure while also rejecting minimally guided discovery as a general prescription.
Why it matters
Teachers should align a strategy with the intended mental process, model and scaffold it for novices, and gradually shift responsibility as competence develops. The framework turns broad calls for active learning into testable decisions about what learners should generate and why.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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