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2 references
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- Vol 4 RE: Chapter 1
meaningful learningrote learningknowledge transferknowledge constructioncognitive processesassessment alignmentprior knowledgebloom taxonomyJournal article Evidence summaryAt a glance
Mayer distinguishes learning that supports only retention from learning that supports both retention and transfer. Using the revised Bloom taxonomy, he describes meaningful learning as knowledge construction: learners select relevant information, organise it into coherent mental representations, and integrate those representations with prior knowledge.
Key ideas
The article crosses two learning outcomes—remembering and transferring—with three instructional scenarios. No learning yields poor retention and transfer; rote learning yields adequate retention but weak transfer; meaningful learning yields both. Mayer then maps six categories of cognitive processes—remember, understand, apply, analyse, evaluate, and create—onto assessment tasks. The practical implication is that instruction and assessment must be aligned with the intended cognitive outcome.
Why it matters
If teaching emphasises isolated facts and tests only recall, students have little reason to build transferable understanding. Meaningful learning instead requires explanations, organisation, comparison, inference, application, and opportunities to use knowledge in situations that differ from the original lesson.
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- Vol 3 RE: Chapters 5, 9
argumentation-based learningcomputer-supported collaborationargumentative discourseknowledge constructioncollaboration scriptsinstructional scaffoldingtransactive discussiondigital learning environmentsJournal article Evidence summaryAt a glance
Noroozi and colleagues synthesize fifteen years of research on argumentation-based computer-supported collaborative learning.
Key ideas
Their review organizes conceptual and empirical work on how digital environments can support learners in constructing, exchanging, challenging, and integrating arguments while solving problems together. The authors examine learning processes, instructional design features, and outcomes, including knowledge construction, subject learning, problem solving, and quality of argumentative discourse. They distinguish supports such as representational tools, collaboration scripts, prompts, and scaffolds, and consider how these shape participation and transactive discussion. The synthesis finds substantial promise but also variation in theory, measures, tasks, and implementation, making direct comparisons difficult.
Why it matters
It concludes with design and research priorities for connecting technological affordances to specific argumentative processes and for testing whether gains transfer beyond a supported activity.
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Edition abbreviations
- TE
- Teacher Edition
- PE
- Practice Edition
- RE
- Research Edition
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