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Record W2569499570 · doi:10.5539/jel.v6n2p111

Structural Model Development: Branches, Attitudes and Self-Effıcacy of Pedagogical Formation Program Pre-Service Teachers

2017· article· en· W2569499570 on OpenAlexvenueno aff
Sadık Yüksel SIVACI

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsnot available
Fundersnot available
KeywordsConformityPsychologyGraduation (instrument)Structural equation modelingMathematics educationScale (ratio)Test (biology)Self-efficacyCertificatePedagogySocial psychologyMathematicsStatistics

Abstract

fetched live from OpenAlex

In this study, the relationship between attitudes of pedagogical formation program pre-service teachers towards teaching profession and their self-efficacies has been examined. In this case, the effect of graduation branches of the pre-service teachers on teacher self-efficacies and the effect of teacher self-efficacies on attitudes towards teaching profession have been investigated. From this aspect, this research has the characteristics of causal-comparative research. Being suitable for the purpose of this research, it has been carried out with 300 pre-service teachers registered to pedagogical formation training certificate program at a state university in Turkey. Being conducted on pre-service teachers and established scaling models incidental to “Attitude Scale towards Teaching Profession” and “Teacher Self-Efficacy Scale” has been confirmed and the conformity index values obtained from the scaling model have shown good conformity. It is also seen that the structural equation model which is established in order to test the effect of branches on teacher self-efficacies and the effect of teacher self-efficacies on attitudes towards teaching profession has been confirmed and conformity index values have shown good conformity.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.656

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.098
GPT teacher head0.430
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 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

Citations1
Published2017
Admission routes1
Has abstractyes

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