When intentions meet reality: Consonance and dissonance in teacher approaches to peer assessment
Bibliographic record
Abstract
This article focuses on teachers’ experiences in implementing peer assessment with first semester students. It explores the relationship between teachers’ conceptions of teaching and their approach to peer assessment, where both conceptions and approaches are described as being either learning focused or content focused. Drawing upon analysis of interviews with eight teachers, the study found that one had a consonant view of the interrelationship between conceptions of teaching and approaches to peer assessment, while the remaining seven described their conceptions of teaching and their approaches to peer assessment with a combination of learning-focused and content-focused statements. These statements are labelled as dissonant. Discussion focuses on implications of consonant and dissonant relationships between conceptions of teaching and approaches to peer assessment for implementation of peer assessment; it also addresses academic development issues. The study reveals that when implementing new methods (here, peer assessment), underlying assumptions will impact on the nature of teacher engagement.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".