Integrated Reading and Writing Tasks and ESL Students' Reading and Writing Performance in an English Language Test
Bibliographic record
Abstract
This exploratory study investigated whether content knowledge from reading would affect the processes and the products of adult ESL (English as a second language) students' writing and reading performance in a simulated English language test that made use of reading and writing modules. Following a counterbalanced within-subjects design, 34 first-year engineering students with intermediate levels of English proficiency did two reading and writing tasks in two conditions, one when the reading passage was related thematically to the writing task, and the other when the reading passage was not. In addition, participants answered interview questions and filled out a retrospective checklist of the writing strategies they used when the writing task was related thematically to the reading task. The students performed significantly better on their writing and on summary recalls of their reading comprehension in the condition where the reading and writing tasks were thematically related. The study revealed that the thematic connection between reading and writing enhanced both the processes and the products of students' writing 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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".