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Record W2750758539 · doi:10.12735/ier.v5n1p1

The Correlation between Professional Development and Teacher's Self-Efficacy

2017· article· en· W2750758539 on OpenAlexvenueno aff
Egoza Wasserman, Zipi Maymon

Bibliographic record

VenueInternational Education Research · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCorrelationProfessional developmentPsychologyMedical educationMathematics educationPedagogyMedicineMathematics

Abstract

fetched live from OpenAlex

The purpose of this study is to examine the correlation between professional development of the teaching staff in schools using training courses, and teacher self-efficacy. This study was conducted using the qualitative method, with 144 questionnaires given to teachers in training courses in the Pisgah Centers (Development of Teaching Staff Centers) in Israel, where the questionnaires examined the length of the training, the teacher's self-efficacy, and their standpoint regarding the professional development program. Results of the research show a distinct positive correlation between most of the teacher's standpoints and most of their feelings of self-efficacy. Thus the standpoint of the teachers on the subject of effective teaching methods of the organization predicted the feeling of self-efficacy in the objective, relationships and organizational factors. In addition, the teacher's standpoint on the subject of environment predicted the feeling of self-efficacy in the objective factor and the teacher's standpoint on the subject of ICT predicted the feeling of self-efficacy in both the objective and relationship factors. Furthermore, a definitive correlation was found between the length of the training course and the feeling of self-efficacy amongst the teachers in both the objective and organizational factors.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.345
GPT teacher head0.570
Teacher spread0.226 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

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