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Record W2804388597 · doi:10.5539/jel.v7n4p92

The Development of a Scale to Measure Teacher’s Self-Efficacy and Confidence in Teaching Compulsory K-12 Theology Courses

2018· article· en· W2804388597 on OpenAlexvenueno aff
Sezai Kocabas, Burhan Özfidan, Lynn M. Burlbaw

Bibliographic record

VenueJournal of Education and Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Islamic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsConstruct (python library)Self-efficacyPsychologyScale (ratio)Self-confidenceMathematics educationQuality (philosophy)PedagogySocial psychologyEpistemologyComputer science

Abstract

fetched live from OpenAlex

One of the most important goals of education is to ensure the quality of teaching and learning. Sense of teacher’s self-efficacy affects the quality throughout the contribution to all stakeholders in educational process. The right of religious education is one of the essential rights in the world. Moreover, it has positive effect on the society by helping to improve social relationship. Therefore, teacher self-efficacy belief based on religious groups is critical for stakeholders in religious education as well as other fields. The purpose of this study is to construct an instrument to measure teachers’ sense of self-efficacy related to teaching compulsory K-12 theology courses. The result of the study indicates that the teacher self-efficacy scale towards religious groups is valid and reliable instrument. The instrument is going to be useful to look to peaceful future with confidence.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.034
GPT teacher head0.365
Teacher spread0.332 · 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 designBench or experimental
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

Citations2
Published2018
Admission routes1
Has abstractyes

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