Perceived Teacher Self-Efficacy of Teacher Candidates Enrolled in the Pedagogical Formation Certificate Program
Bibliographic record
Abstract
This study aims to determine the variables affecting teacher candidates’ perceived self-efficacy levels. The study was conducted with 560 students who attended the pedagogical formation programs, a type of teacher training program, run by two different universities in Turkey during the academic year of 2016-2017. The data was obtained by Teachers’ Sense of Efficacy Scale, developed by Tschannen-Moran and Hoy (2001) and adopted to Turkish by Çapa, Çakıroğlu and Sarıkaya (2005). SPSS package program was used for data analysis, and percentage, arithmetic mean, standard deviation, independent groups t-test, one-way analysis of variance (ANOVA) and LSD test were used for the analysis of data. According to the study findings, candidates’ views on self-efficacy differ according to their ages, sexes, universities, settlements they have lived the longest, faculties and mother’s education level while their self-efficacy views did not differ according to their own and father’s education level. As the teacher candidates’ ages increased, their self-efficacy also increased. Males compared to females, Kafkas University’s students compared to Niğde Ömer Halisdemir University’s students, the students who have lived in metropolises the longest compared to others, students from faculties who accept students with ability exams compared to other faculties considered themselves more efficacious about teaching.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".