The Use of Peers in Assessment for Learning: A Case Study of Trainee Teachers at Bindura University of Science Education (BUSE), Zimbabwe
Bibliographic record
Abstract
The study was an exploration of trainee teachers’ understanding, perceptions of, and confidence in the use of peers in assessment for learning (AfL) at Bindura University of Science Education, Zimbabwe. Trainee teachers were enrolled in a programme that used a blended model of teaching and learning between February and June 2021. Trainees participated in online seminars and peer assessment in a course on curriculum development and completed questionnaire eliciting their attitudes toward peer assessment. A mixed-methods approach using both quantitative and qualitative methodologies was adopted. Quantitative data were analysed using descriptive statistics, mean item scores and the summated scores for the three constructs of confidence, benefits of and threats to peer assessment. Open-ended items were analysed qualitatively and emerging themes were reported. Summated scores of 4, meant trainees had positive attitudes toward peer assessment and believed in numerous benefits of using peer assessment. A summated mean score of 3 for threats to peer assessment meant trainee teachers had neutral views to the construct. Conflicting messages were evident. The same trainees who believed that peer assessment was useful still doubted sincerity of peers and preferred teacher assessment. Further research, using a larger population and sample and interviews to probe doubts in peer assessment, is recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".