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Record W7019201265

Factors Affecting the General Academic Achievement of University Students: Gender, Study Hours, Academic Motivation, Metacognition and Self-Regulated Learning

2021· article· en· W7019201265 on OpenAlexaboutno aff

Bibliographic record

VenueÇanakkale Onsekiz Mart University AVESIS · 2021
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsMetacognitionAcademic achievementPerceptionScale (ratio)Academic yearLearning developmentPoint (geometry)
DOInot available

Abstract

fetched live from OpenAlex

This study aimed to determine the effects of university students' gender, weekly study hours, academic motivation, metacognition, and self-regulated learning levels on their overall academic achievement and to examine whether academic motivation, metacognition and self-regulated learning total scores predicted their GPAs. This study utilized a survey and prediction research design to analyze the research questions posed. The participants of the study consisted of 86 undergraduate students attending various programs of a university in Western Canada. The research data were collected using the “Metacognitive Awareness Inventory (MAI)” developed by Schraw and Dennison (1994), the “Self-regulated learning perception scale (SASR)” developed by Dugan and Andrade (2011), the "Academic Motivation Scale (AMS-C 28) College Version" developed by Vallerand, Pelletier, Blais, Brière, Senécal and Vallières (1992), and the “demographic form”. We found a significant relationship between the university students' self-regulated learning, metacognition and academic motivation scores, and their grade point averages (GPAs). We also determined that the total scores related to the university students’ self-regulated learning, metacognition and academic motivation significantly predicted their GPAs, and that the gender and weekly study hours of the university students did not have a significant effect on their self-regulated learning, metacognition, academic motivation and academic GPA.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.070
GPT teacher head0.340
Teacher spread0.270 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2021
Admission routes1
Has abstractyes

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