Self Assessments of the Prospective Teachers about the Teaching Materials They Have Designed
Bibliographic record
Abstract
The purpose of the study is to reveal the self-evaluations of the prospective teachers on two-and three-dimensionalvisual teaching materials they have designed in the field of the pedagogical formation education. A qualitativeresearch method was used in the study. The study group was chosen from the prospective teachers who were enrolledin the pedagogical formation education at a state university in Turkey. A questionnaire consisting of three open-endedquestions was used. In this questionnaire, the prospective teachers were asked questions about the strengths andweaknesses of the instructional materials they designed and what kind of arrangements they would make if theydesigned the material again. The data were analyzed descriptively. The views of the prospective teachers on thestrengths of the instructional materials they design are collected under seven themes: the characteristics of us, theeffect on learning the relation with the subject, the preparation and construction process, the gains to the learners, thepresentation of the information and conformity. The opinions of the prospective teachers about the weaknesses of theteaching materials have been collected under five themes. In general, it is seen that the arrangements to be made inthe case of redesign are expressed in terms of the weaknesses.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 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".