Work Integrated Learning Online Enrichment Intervention Programme for Student Teachers
Bibliographic record
Abstract
The study is based on research conducted on work-integrated learning (WIL), also known as teaching practice during the online enrichment and intervention programme for final-year student teachers at a tertiary institution in Johannesburg. This programme was conducted from 2016 and modified in 2020 to enhance and improve the History methodology student teachers’ Pedagogic Knowledge and Pedagogic Content Knowledge (PCK), during the Corona virus pandemic using different online tools. Former students of the institution who are now teachers, school learners and a psychologist participated in the process of enhancing the student-teachers’ WIL. The purpose of the study was to explore the effectiveness of the online enrichment intervention programme in providing History student teachers with necessary teaching skills and to ensure readiness for WIL during the Covid -19 period. The main research question was: “To what extent can the online enrichment intervention programmes for student-teachers improve and enhance teaching practice before and during WIL in the context of covid-19?” Qualitative research methods of observation, interviews and document analysis were used with a sample of 90 Post-Graduate Certificate in Education (PGCE) and 4th year Bachelor of Education (BEd) students. The findings indicated that the online enrichment intervention programme improved student-teachers’ confidence, emotional readiness before and during WIL and the unfavourable circumstances in their classrooms. Student-teachers reported better understanding of the need for proactive planning for any circumstance or situation. Despite the constraints imposed by the pandemic, they observed changes in their conceptualisation of teaching, improvement in their interaction with learners, in classroom management, in their ability to implement different teaching strategies, resources and assessment tasks.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".