Teaching practice: a make or break phase for student teachers
Bibliographic record
Abstract
Teaching practice is an integral component of teacher training. It grants student teachers experience in the actual teaching and learning environment. We explore the experiences of student teachers in the Vaal University of Technology Postgraduate Certificate in Education (PGCE) during their 10 weeks' teaching practice in the Vaal area. In this article we aim to establish the ways in which these experiences influence the student teachers' perception of the teaching profession. Semi-structured interviews with all student teachers were used to collect the data while content analysis was used to identify themes and analyse the data. We established that, despite the positive experiences during teaching practice, student teachers experienced challenges which affected their perception of the teaching profession. Based on the findings of this study, measures are suggested on how to improve teaching practice in order to have a positive influence on the student teachers' perception of, and attitude towards, the teaching profession.
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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 | 0.009 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".