What Has Experience Got to Do with It? An Exploration of L1 and L2 Test Takers' Perceptions of Test Performance and Alignment to Classroom Literacy Activities.
Bibliographic record
Abstract
The importance of first language (L1) and second language (L2) test takers’ experience with large-scale literacy testing has been well documented in educational research. Our study focused on the Ontario Secondary School Literacy Test (OSSLT), a crosscurricular literacy test that is one of the graduation requirements for Ontario high school students. We drew on qualitative data obtained from open-ended questions on a largescale survey administered to OSSLT test takers. Whether the test takers were preparing to take the test or had already taken the test seemed to play a critical role in L1 and L2 test takers’ perceptions. The most salient results highlight the role that test experience had on test takers’ perceptions of their test performance and the alignment between the test and their classroom literacy activities.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.003 |
| 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".