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Record W2803789634 · doi:10.1177/0829573518773225

Retrieval Practice and Distributed Practice: The Case of French Canadian Students

2018· article· en· W2803789634 on OpenAlexaffabout
Mathieu Gagnon, Stéphanie Cormier

Bibliographic record

VenueCanadian Journal of School Psychology · 2018
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsUniversité du Québec en OutaouaisRoyal Military College of Canada
Fundersnot available
KeywordsPsychologyReading (process)RecallContext (archaeology)Test (biology)Cognitive psychologySocial psychologyDevelopmental psychologyLinguistics

Abstract

fetched live from OpenAlex

Much evidence suggests that long-term retention can be maximized by practicing the recall of information and spreading out one’s learning over time. Nevertheless, previous surveys have shown that undergraduates often ignore the benefits of such strategies and engage in less efficient techniques such as repetitive reading and massed studying. To date, however, this research has focused exclusively on Americans and has paid little attention to potential gender differences. The present study addressed such limits by using a web-based survey of the rereading, self-testing, and distributed learning habits of 1,371 French-speaking Canadian undergraduates. Overall, the results are consistent with American data, suggesting that their original observations extend beyond American campuses. Furthermore, chi-square tests followed by standardized residual analyses suggest that females are more likely to engage in distributed learning than their male counterparts. On the contrary, there was little evidence of such an advantage in the context of self-testing.

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 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)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.052
GPT teacher head0.394
Teacher spread0.343 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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

Citations6
Published2018
Admission routes2
Has abstractyes

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