How People Learn¶
Bransford, J. D., Brown, & Cocking, R. R. (2000). How People Learn: Brain, Mind, Experience, and School. National Academy Press.
Cited by¶
2 citations across 2 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Chunking
- A claim like "experts process more efficiently" resolves into "experts hold domain-specific chunks that experts but not novices recognize; when presented with domain-meaningful material, experts encode it as ~5 chunks while novices encode the same material as 20+ items; this chunking accounts for expert performance on memory and prediction tasks involving domain-meaningful arrangements but not on random arrangements; the chunks are learned through ~N hours of experience and generalize to domain-meaningful novel material but not to scrambled material.
This sourceThe key attribute of expertise is a detailed, organized understanding of domain facts; effective teaching scaffolds learners through progressive chunk levels.
- A claim like "experts process more efficiently" resolves into "experts hold domain-specific chunks that experts but not novices recognize; when presented with domain-meaningful material, experts encode it as ~5 chunks while novices encode the same material as 20+ items; this chunking accounts for expert performance on memory and prediction tasks involving domain-meaningful arrangements but not on random arrangements; the chunks are learned through ~N hours of experience and generalize to domain-meaningful novel material but not to scrambled material.
- Constructivist Learning
- Knowledge transfer—the ability to apply learning from one context to novel contexts—is not automatic but depends on the depth of understanding and the learner's ability to recognize structural similarities across surface-different problems, a synthesis Bransford, Brown, and Cocking (2000) anchor in the National Research Council's How People Learn report.
This sourceNRC synthesis showing transfer depends on depth of understanding and recognizing structural similarities across surface-different problems (supports D48-053; prior annotation about 'chunking' corrected).
- Knowledge transfer—the ability to apply learning from one context to novel contexts—is not automatic but depends on the depth of understanding and the learner's ability to recognize structural similarities across surface-different problems, a synthesis Bransford, Brown, and Cocking (2000) anchor in the National Research Council's How People Learn report.
Verification¶
Does it exist? Not checked yet. This entry carries no identifier to resolve. It was extracted from the citation as written in the article, normalized, and deduplicated against the rest of the registry.
Does it back the claim? Not recorded. Neither this nor any other of the 2 citations of this work carries a recorded support check.
Was it audited? Yes. A second, independent pass read the citation against the article text and recorded a verdict.
Support is checked per citation rather than per work — the same source can be cited soundly in one article and wrongly in another. Per-citation recording began recently, so a citation with no recorded check is a gap in the record rather than evidence it went unchecked.
See how references were verified.
Registry ID ref:59dcaaead8bd · see in the full table