The Student Teachers’ Anxiety during Field Experiences in the beginning of New Normal
Bibliographic record
Abstract
The study had the objectives to 1)study student teachers’ anxiety during field experiences in the beginning of the new normal on 7 aspects: 1) own personality, 2)teaching context, 3)supervision context,4) classroom management, 5) subject content, 6) teacher professionalism context, and 7) Covid-19 pandemic context, and 2) compare the levels of the student teachers’ anxiety, classified by sex, duration of bachelor’s degree study, and the academic level. The sample consisted of 457 student teachers. The collection of data employed a questionnaire inquiring about anxiety and a focus group discussion record. The research found that: 1) The student teachers’ anxiety during the field experience in the beginning of the new normal was at a high level; 2)When classified by sex, there were differences in the supervision context, with statistical significance at the .05 level; females had higher anxiety than males; no significant differences were found on the other aspects; 3) When classified by the duration of bachelor’s degree study, there were differences in the teaching context and the supervision context, with statistical significance at the .05 level; the student teachers in the 4-year bachelor’s degree study had higher anxiety than those in the 5-year bachelor’s degree study; no significant differences were found on the other aspects; 4) When classified by the academic level, there were differences in the teaching context, the supervision context and the teacher professionalism context, with statistical significance at the .05 level; the student teachers in the master’s degree study had higher anxiety than those in the bachelor’s degree study; no significant differences were found on the other aspects.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".