Profile of the prospective teachers response to the development of scientific communication skills through physics learning
Bibliographic record
Abstract
This article discusses the profiles of prospective physics teacher responses to the development of scientific communication skills through physics learning. Data were collected using questionnaires and interviews to strengthen the data obtained through questionnaires, data were analyzed descriptively. The results show that prospective physics teachers who have already joined the Teaching practice/Field Experience Program 2 (FEP 2) or who are currently following FEP 1, generally argues that the development of scientific communication skills can be conducted through subject matter learning, especially physics learning. Some prospective teachers give an anomalous response to some statements on the questionnaire, for example they agreed on the statement that the source of physics learning is sufficient from teacher's explanation, students do not need to read textbooks, not yet need to read scientific articles and scientific reports. Based on these findings prospective physics teachers should need to develop their's good understanding of the aspects to be learned in developing scientific communication skills, as well as their ability in transferring or developing scientific communication skill integrated within physics learning need to be assessed.
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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 | 0.002 | 0.014 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".