Determining Attitudes towards Pedagogical Teacher Training: A Scale Development Study
Bibliographic record
Abstract
Education is the key to raising generations that are modern, democratic, productive, diligent, understanding, perceptive, critical and inquisitive. Teacher education is more important today than it has been in half a century. Thus, teachers are so significant to education and scholars argue that teacher quality is the most important within-school factor affecting student performance because great teachers help create great students. In fact, research shows that an inspiring and informed teacher is the most important school-related factor influencing student achievement, so it is critical to pay close attention to how we train and support both new and experienced educators (Edutopia, 2008). The Republic of Turkey has made great efforts to train teachers and meet the demand for teachers. Pedagogical teacher training is a part of this effort. This study will help determine the attitudes of teacher candidates towards the Pedagogical teacher training they receive, and in this regard the purpose of this study is to develop a measurement tool that can be utilized in future studies. The study showed that “The Attitude Scale towards Pedagogical Teacher Training (PFETO)” is a valid and reliable tool. PFETO is a valid and reliable data collection tool for future studies on attitudes towards Pedagogical Teacher Training.
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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 | 0.015 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".