Predictability in high-stakes examinations: students’ perspectives on a perennial assessment dilemma<sup>*</sup>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Key debates within educational assessment continuously encourage us to reflect on the design, delivery and implementation of examination systems as well as their relevance to students. In more recent times, such reflections have also required a rethinking of who is authoritative about assessment issues and whose views we seek in order to better understand these perennial assessment dilemmas. This paper considers one such dilemma, predictability in high-stakes assessment, and presents students’ perspectives on this issue. The context is the Irish Leaving Certificate (LC) taken by upper secondary students (aged between 16 and 18) in order (mainly) to enter tertiary-level education. The data come from 13 group interviews with 81 students across a range of schools in Ireland. Listening to students about complex, high-stakes examining problems has a limited history within the educational assessment literature. The findings from the study address this shortcoming and depict how students’ insightful reflections can improve our understanding of these dilemmas. Further, students are more than able to reflect on their own situations with regard to high stakes examining contexts and have important contributions to make to our fuller understanding of those elements that will promote high quality and fair assessment.
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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 | 0.007 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it