When the Cheese Moves: How Arab and Jewish Education Students Perceive the Transition to Distance Practical Teaching During the Covid-19 Crisis
Bibliographic record
Abstract
The goal of the current study was to examine teaching students’ positions and perceptions regarding the transition to an online format for practical teaching during Covid-19, and whether differences exist between Jewish and Arab students’ positions. The study also examines teaching students’ technological and pedagogical self-efficacies for distance teaching and the extent of differences between the Arab and Jewish students’ self-efficacies. In addition, the study examined which background and personality variables predict positions and perceptions. The findings are based on a questionnaire completed by 279 Arab and Jewish teaching students from two Israeli teacher education colleges that transitioned to online practical teaching as a result of the Covid-19 crisis. Semi-structured interviews were also conducted to gain a deeper understanding of the questionnaire findings and to expand on topics not referred to in the questionnaire. The study reveals that teaching students accept the importance of the distance teaching experience during training in order to prepare them for the changing reality. Nevertheless, this cannot fully replace field experience because of the need for support and the limited ability to learn from the distance experience about face-to-face 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 | 0.002 | 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 | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".