The Effects of a Cognitive Apprenticeship Model on the Argumentative Texts of EFL Learners
Bibliographic record
Abstract
In the present study, a quasi-experimental pre-post test design was used to assess the effects of an argumentative writing strategy (POW+TREE) on the performance of grade five and six students of Greek origin who were learning English as a foreign language (EFL) in a Greek setting. The Self-Regulated Strategy Development (SRSD) cognitive apprenticeship model was utilized to improve the text composition skills of the students. In the experimental group (N=77), participants received instruction on general and genre-specific strategy use for planning and writing argumentative essays, on procedures to apply self-regulation (goal setting, self-monitoring, self- reinforcement, and self-instructions), and on establishing additional skills (vocabulary, grammar-drill instruction, good word choice, interesting openings etc.). The control group (N=100) was supported through a traditional curriculum in writing (focusing on spelling and grammar). Findings of the study showed that strategy instructed students wrote argumentative essays that were schematically stronger, qualitatively better, and longer than those produced by their counterparts in the control group.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".