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Record W2166091694 · doi:10.5539/jedp.v3n1p72

The Capitalization of Personal Self-Efficacy: Yields for Practices and Research Development

2013· article· en· W2166091694 on OpenAlexvenueno aff
Huy P. Phan

Bibliographic record

VenueJournal of Educational and Developmental Psychology · 2013
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologySocial cognitive theorySocial learning theoryIdentity (music)Social psychologyQuality (philosophy)Facet (psychology)Self-efficacyPersonalityBig Five personality traitsEpistemology

Abstract

fetched live from OpenAlex

Quality learning in achievement contexts is an important feat for enhancement and development. In a similar vein, in the contexts of secondary schooling, academic engagement is a major element for scholarly consideration (e.g., “I really enjoy coming to school, and taking part in these social activities”). In the area of educational psychology, there have been various cognitive (e.g., achievement goal orientations) and noncognitive (e.g., self-concept) theories that note and explain individuals’ learning, academic engagement, motives, etc. Bandura’s (1986) social cognitive theory, especially the tenets of personal self-efficacy (Bandura, 1977, 1997) have been researched and used to account and predict individuals’ cognition and behaviors in educational and non-educational settings. This theoretical review then, explores a few identified issues related to quality learning – for example, one’s sense of identity and how this psychosocial facet features in the teaching and learning processes. We also scope, in the latter section of this article, the potency of personal self-efficacy in the contexts of quality learning and school engagement, and how this theoretical orientation, in totality, may result in effective practices and continuing research development.

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)0.001
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 score0.362
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.104
GPT teacher head0.457
Teacher spread0.353 · 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

Citations5
Published2013
Admission routes1
Has abstractyes

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