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Educational Psychology

2015· other· en· W4229798718 on OpenAlexaff
Tony Perez, Bradley W. Bergey, Ting Dai, Jennifer G. Cromley

Bibliographic record

VenueThe Encyclopedia of Clinical Psychology · 2015
Typeother
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsDalhousie University
Fundersnot available
KeywordsEducational psychologyPsychologyField (mathematics)Psychological researchApplied psychologySchool psychologyEducational researchMathematics educationSocial psychology

Abstract

fetched live from OpenAlex

Abstract Educational psychology is an interdisciplinary field that uses psychological principles to understand and improve learning in and out of schools and across the lifespan, with a focus on typically developing learners. The field bridges basic and applied research, and most research considers a combination of cognitive (how people learn) and/or motivational (what energizes people to learn) variables. The field uses a range of research designs, from large‐scale international longitudinal questionnaire studies, to classroom experiments, laboratory studies, interviews, and mixed‐methods research. Clinical psychologists working with clients who present with learning or motivational difficulties at school might benefit from educational psychology findings in these areas. The entry concludes with some common theoretical constructs employed within both educational and clinical psychology, such as self‐efficacy and self‐determination theory.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.197
Threshold uncertainty score0.660

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.1970.070

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 head0.235
GPT teacher head0.583
Teacher spread0.348 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations368
Published2015
Admission routes1
Has abstractyes

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