Exploring science teachers’ conceptions and efficacy of assessment in Manitoba schools: A case study.
Bibliographic record
Abstract
Contemporary classroom assessment practices have been identified as a promising pedagogical approach to improve students’ learning and the development of their metacognitive skills; however, the complexities inherent in assessment point towards the need for careful consideration of the educational context of such practices, as well as the numerous factors influencing teachers’ assessment practices. Research has established that such factors include teachers’ conceptions of assessment, particularly in terms of the purpose assessment plays in the classroom and teachers’ perceived self-efficacy. In science education and particularly in Manitoba, there is an opportunity to further investigate the relation between these concepts, especially since the publication of some provincial guidelines on assessment a little more than a decade ago. The purpose of this multiple case study research is to provide insights into three Manitoban high school science teachers’ conceptions of assessment, classroom assessment practices, and their perceived self-efficacy in developing and using contemporary assessments in their science classrooms. The data from one-on-one interviews with the three teachers and the assessment artifacts they shared were analyzed using qualitative content analysis. Results corroborate literature that indicates a strong connection between assessment conceptions, perceived self-efficacy and classroom practices, and suggest an interesting relationship to provincial assessment recommendations, despite teachers’ stated unfamiliarity with one of these documents. Implications of the study for science teacher’s practices, science education, policymakers, and future research are presented.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.007 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".