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Record W4256161118 · doi:10.31234/osf.io/7ng5y

The Impact of Study and Learning Strategies On Post-Secondary Student Academic Achievement: A Mixed-Methods Systematic Review

2021· preprint· en· W4256161118 on OpenAlexaff
Joy Xu, Jeffrey Ong, Tam Thi Thanh Tran, Yasmine Kollar, Alyssa Wu, Milena Vujicic, Helen Hsiao

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoMcMaster University
Fundersnot available
KeywordsRecallAcademic achievementPsychologyPsychological interventionMathematics educationComputer science

Abstract

fetched live from OpenAlex

BACKGROUNDWithin academic development, it is important for students to use effective study strategies to facilitate learning. Techniques used for long-term information retention include note taking strategies, time management, methods of self-testing and active recall. These strategies are explored to help students learn more effectively to attain their academic goals.METHODA mixed-methods systematic review of peer-review articles and grey literature was conducted with a predetermined criteria for a convergent integrated synthesis approach. PsychInfo (Ovid), Web of Science, and ProQuest databases were searched with guidance of a PICO-P logic grid and search strategy using keywords of student, study strategies, and achievement alongside filters. Initial studies were screened and reconciled by two independent authors with the use of a piloted screening tool. Using the Mixed Methods Assessment Tool (MMAT), included studies were assessed for quality. Two authors independently performed data extraction. Heterogeneity in study designs, outcomes, and measurements precluded meta and statistical analyses; thus, a qualitative analysis of studies was provided.RESULTSFour major themes contributing to academic performance were identified among the appraised articles. These themes were self-testing, scheduling/time management, concept maps, and learning styles. Self-testing, scheduling, and concept maps were positively correlated with increased academic performance, while no correlation was found with learning styles and academic performance.CONCLUSIONIncluded studies provided evidence for significant differences in study strategies implemented by high and low achieving students, such as areas of motivation for learning, efficiency, active recall, retrieval practices, and concept maps. Understanding the effectiveness of certain study strategies is critical for students and educational facilitators to maximize learning.

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)0.036
metaresearch head score (Gemma)0.099
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.036
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0360.099
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0110.012
Bibliometrics0.0150.013
Science and technology studies0.0010.002
Scholarly communication0.0050.004
Open science0.0030.003
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.049
GPT teacher head0.503
Teacher spread0.455 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations8
Published2021
Admission routes1
Has abstractyes

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