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Record W4410951464 · doi:10.3390/bs15060765

Working Memory and Instructional Fit: Reintroducing Aptitude–Treatment Interaction in Education Research

2025· review· en· W4410951464 on OpenAlex
Faria Sana, Barbara Fenesi

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBehavioral Sciences · 2025
Typereview
Languageen
FieldPsychology
TopicEducational and Psychological Assessments
Canadian institutionsWestern UniversityAthabasca University
FundersSocial Sciences and Humanities Research CouncilSocial Sciences and Humanities Research Council of Canada
KeywordsAptitudePsychologyCognitive psychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Working memory (WM) is a cognitive system with limited capacity that enables individuals to focus on goal-relevant information while filtering distractions and integrating new knowledge. Differences in WM capacity influence how students engage with instructional materials, shaping the effectiveness of educational interventions. This raises the following question: which instructional methods work best, for whom, and under what conditions? The aptitude-treatment interaction (ATI) framework addresses this by examining how learning outcomes are influenced by the alignment between cognitive abilities, such as WM, and instructional strategies. This paper reviews WM's role in learning and academic achievement, explores ATI's relevance in contemporary education research, and highlights how this framework can guide the development of adaptive instructional strategies that support diverse learners.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.558
GPT teacher head0.642
Teacher spread0.084 · 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