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Record W2736706996 · doi:10.5539/jel.v6n4p229

Investigation of the Attitudes of Physical Education Teacher Candidates toward Teaching Profession and Sense of Competence in Terms of Some Variables

2017· article· en· W2736706996 on OpenAlexvenueno aff
Talha Murathan, Kübra ÖZDEMİR

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsnot available
Fundersnot available
KeywordsPhysical educationCompetence (human resources)PerceptionPsychologyMathematics educationPedagogyLikert scaleMedical educationSocial psychologyMedicine

Abstract

fetched live from OpenAlex

The purpose of this study was to examine the attitudes of physical education teacher candidates toward the teaching profession and the perceptions of professional competence according to some variables. A total of 351 teacher candidates, studying in the last class of Physical Education and Sport Teaching Department in the Faculty of Sports Sciences and Physical Education and Sports Schools were enrolled as the research group. “Attitude Scale Related to Teacher Education”, “The Candidate Teacher’s Proficiency Perception Scale” and “Personal Information Form” developed by the researchers were applied on the study subjects to collect the data. It was found that according to the universities, there are differences in the perception of professional competence but there is no difference in attitude. It was also found that there is no meaningful difference between professional perceptions and teaching attitudes in terms of sport branches, the situation in which the education section is selected voluntarily or not.

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 score0.002
Threshold uncertainty score0.007

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 studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.032
GPT teacher head0.362
Teacher spread0.329 · 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

Citations10
Published2017
Admission routes1
Has abstractyes

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