An Investigation of Method Effects on Reading Comprehension Test Performance
Bibliographic record
Abstract
Performance on a test is not dependent on only one factor. Rather, there are so many factors which directly and indirectly influence a test-taker‟s performance on the test. Thispaper reports the results of a study which investigates the effects of the test types on reading comprehension test performance among intermediate and advanced Iranian EFL learners. To this purpose, from a language institute in Khoy, a city in the northwest of Iran, and based on results of a placement test we selected 40 Iranian EFL from intermediate learnersand 40 Iranian EFL advanced participants and divided each proficiency level into two groups. Then, one group in each proficiency level was given a reading comprehension test in the multiplechoice format and the other group the same reading comprehension test in the multiple-choice cloze test. Our analyses showed that the participants in both proficiency levels who took the reading comprehension in the multiple-choice format performed significantly better thanthose participants in both proficiency level who took the reading test in the multiple-choice cloze test. The pedagogical implications of the results are discussed.
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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 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".