Teacher Candidates’ Attitudes Towards the Teaching Profession in Turkey
Bibliographic record
Abstract
This study examined the attitudes of teacher candidates in Turkey towards the teaching profession. Descriptive surveys were used and the research data was obtained from Pamukkale University Classroom Teaching students. During data analysis, the arithmetic means and standard deviations of the groups were calculated and a t-test and One-Way ANOVA were used. The attitudes of teacher candidates towards the teaching profession don’t vary in terms of “gender”, “type of teaching”, “type of high schools they graduate from” and in order of their preferences to be a teacher. More than half of the candidates choose the Classroom Teaching Program willingly and about all of them want to perform this profession, but their attitudes towards the teaching profession were not well developed. The majority of the participants were not satisfied with the University and faculty administrations and reopted that they don’t show enough effort required to develop themselves for the profession. It is found that the attitudes of students expressing their discontent are at a lower level. It is necessary to provide the teacher candidates not only with knowledge and skills, but also to help them develop the beliefs and positive attitudes related to the profession.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".