Do Test Formats in Reading Comprehension Affect Second-Language Students' Test Performance Differently?
Bibliographic record
Abstract
Large-scale testing in English affects second-language students not only greatly but also differently than first-language learners. The research literature reports that confounding factors in such large-scale testing such as varying test formats may differentially affect the performance of students from diverse backgrounds. An investigation of test performance between ESL/ELD students and non- ESL/ELD students on the Ontario Secondary School Literacy Test (OSSLT) was performed to investigate whether test formats in reading comprehension affected the two groups differently. The results indicate that the overall pattern of difficulty levels on the three test formats were the same between ESL/ELD students and non-ESL/ELD students, except that ESL/ELD students performed substantially lower on each format and that more variability was found among ESL/ELD students. Further, discriminant analysis results indicated that only the multiplechoice questions obtained a significant discriminant coefficient in differentiating the two groups. The results suggest a lack of association between test formats and test performance.
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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 | 0.005 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".