MétaCan
Menu
Back to cohort
Record W2411210635 · doi:10.5430/ijhe.v5n3p32

Student Self-Efficacy and Gender-Personality Interactions

2016· article· en· W2411210635 on OpenAlexvenueno aff
Lars Fallan, Leiv Opstad

Bibliographic record

VenueInternational Journal of Higher Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicInnovations in Educational Methods
Canadian institutionsnot available
Fundersnot available
KeywordsIntuitionFeelingPersonalityPsychologySocial psychologySelf-efficacyDevelopmental psychology

Abstract

fetched live from OpenAlex

The present study reveals that female students have significantly lower self-efficacy level and self-efficacy strength than their male peers in a course in Principles of Economics. This general conclusion does not hold for all personality types. The general conclusion of lower self-efficacy level in economics for female students compared to those of their male peers does only exist for female intuition and feeling ( NF ) and intuition and thinking students ( NT ) but not for the female sensing and perceiving student ( SP) . Furthermore, the result is revealing that the significant higher self-efficacy level for male students does only exist for male intuition and thinking students ( NT ) and not for male NF and SP students. Female students have significantly lower self-efficacy strength than their male peers. This does only exist for female intuition and thinking ( NT ) and sensing and perceiving ( SP ) students, but not for female NF students. The general result that male students have significantly higher self-efficacy strength than their female peers, does only encompass male intuition and thinking ( NT ) students and not the male SP and NF students. This study tells us that we should be cautions to conclude that self-efficacy is uniformly affected by gender. Gender-personality interactions do matter.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.073
GPT teacher head0.503
Teacher spread0.429 · 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 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

Citations35
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Higher EducationSame topicInnovations in Educational MethodsFrench-language works237,207