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Record W2106836754 · doi:10.3102/00028312040003769

Effect of Paced and Unpaced Practice on Skill Application and Retention: How Much Is Enough?

2003· article· en· W2106836754 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

VenueAmerican Educational Research Journal · 2003
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyFluencyGrade retentionMastery learningTerm (time)Mathematics educationAcademic achievementDevelopmental psychology

Abstract

fetched live from OpenAlex

This study examined the relative benefits of mastery learning, overlearning, and fluency-building instructions for academic performance and long-term retention. College students enrolled in introductory quantitative methods classes (n = 168) were asked to practice every week with a computerized flash-card program until they attained various mastery criteria. The results confirmed that practicing until mastery improved individual exam scores, group success rates, and long-term retention. Moreover, overlearning provided additional benefits, especially in long-term retention. However, fluency-building instructions did not further increase academic achievement or long-term retention. Despite the alleged detrimental effects of drill and practice on motivation, a positive relationship was found between amount of practice and attitudes toward the course, the subject matter, and practice activities.

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)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.604
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.065
GPT teacher head0.523
Teacher spread0.458 · 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