Integrating Reading and Writing in EFL Composition in China.
Bibliographic record
Abstract
Research suggests that the current division between reading and writing instruction for Chinese English as a Second Language (ESL) students, the lack of authentic communication that typically exists in ESL contexts, and difficulties with sequencing teaching-learning activities combine to hinder the development of writing skills. The paper suggests that writing teachers must understand that there is much more involved in writing than the final copy turned in by students. It recommends integrating reading and writing in ESL education, noting that reading and writing are interactive. Writing teachers must move beyond giving students a topic to write on and then grading the final product. They must include plenty of process work, from reading to writing, so students will progress from reading, to discussing and analyzing, to writing. Writing instruction is effective when contextualized through background reading related to real-life interests. This allows students to understand the purpose of the relationship between reading and writing. This integration allows educators to teach more effectively by dealing with reading and writing simultaneously and students to write more effectively in an authentic context. Reading strategies that students learn early in the process will become part of their writing strategies later on. (Contains 15 references.) (SM) Reproductions supplied by EDRS are the best that can be made from the original document. INTEGRATING READING AND WRITING IN EFL COMPOSITION IN CHINA A paper presented at the annual meeting of the Canadian Association of Applied Linguistics, Humanities and Social Sciences, Congress, 2002, Toronto U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) /This document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".