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The Psychology of Academic Achievement

2009· review· en· W2147881997 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnnual Review of Psychology · 2009
Typereview
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsHeuristicsPsychologyEducational psychologyPsychology of learningMetacognitionSnapshot (computer storage)Experimental psychologyCognitive scienceCognitive psychologyComparative psychologyLearning theoryMathematics educationSocial psychologyCognitionComputer science

Abstract

fetched live from OpenAlex

Educational psychology has generated a prolific array of findings about factors that influence and correlate with academic achievement. We review select findings from this voluminous literature and identify two domains of psychology: heuristics that describe generic relations between instructional designs and learning, which we call the psychology of "the way things are," and findings about metacognition and self-regulated learning that demonstrate learners selectively apply and change their use of those heuristics, which we call the psychology of "the way learners make things." Distinguishing these domains highlights a need to marry two approaches to research methodology: the classical approach, which we describe as snapshot, bookend, between-group experimentation; and a microgenetic approach that traces proximal cause-effect bonds over time to validate theoretical accounts of how learning generates achievements. We argue for fusing these methods to advance a validated psychology of academic achievement.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.013
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.125
GPT teacher head0.564
Teacher spread0.439 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it