Hitting the Conceptual Knowledge Wall: Pre-Service Teacher Responses to High-Stakes Mathematics Testing Failure.
Bibliographic record
Abstract
The research reported here is part of a larger study and examines the cases of two individuals who were initially unable to achieve the required 60% passing grade on a Mathematics for Teaching Exam at the end of their first enrolment in an intermediate-level mathematics methods course. The exam is a graduation requirement of the teacher education program at a specific university in Ontario. The two individuals reacted in markedly different ways to the news that they had not met the mathematics requirement: one took it as an opportunity to grow and learn the mathematics she was aware she had never learned in her past; the other became angry and hostile, blaming his professor for his lack of success. In this article, we present the contrasts in approach between the cases, and how the responses influenced the participants’ further mathematics learning. As well, the somewhat unexpected impact that these responses had on the subjects’ peers is explored. Finally, we document concerns that were raised from the use of a high-stakes exam as a mandatory graduation requirement and consider reasons for the differing reactions.
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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 | 0.007 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".