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Record W4389555412 · doi:10.1080/21683603.2023.2292033

Relationship between students’ academic self-concept, intrinsic motivation, and academic performance

2023· article· en· W4389555412 on OpenAlexaff
Seth Sunu, David Baidoo-Anu

Bibliographic record

VenueInternational Journal of School & Educational Psychology · 2023
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsQueen's University
Fundersnot available
KeywordsIntrinsic motivationPsychologySelf-determination theoryMathematics educationLearning developmentPerceptionGoal theoryAcademic achievementAffect (linguistics)Social psychologyHigher educationAutonomy

Abstract

fetched live from OpenAlex

This study examined the relationship between academic self-concept, intrinsic motivation, and academic performance of Senior High School students. A quantitative approach using a descriptive cross-sectional survey design was used in the study. A multi-stage sampling technique was used to select 346 participants. The results showed that students who had a positive perception of their academic self-concept were more likely to be intrinsically motivated. Intrinsic motivation and academic self-concept also predicted students’ academic performance. While the results from the study revealed that academic self-concept and intrinsic motivation are great recipes for predicting students’ academic success, it must be emphasized that academic self-concept and intrinsic motivation generally do not operate in isolation. Therefore, educators who wish to improve the academic performance of the students especially among Senior High School students must consider paying attention to other factors that affect students’ learning. Implications for policy and practice have been discussed.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.040
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.117
GPT teacher head0.474
Teacher spread0.357 · 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 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

Citations9
Published2023
Admission routes1
Has abstractyes

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