Bibliographic record
Abstract
Although pair and group work are commonly applied in English language classrooms, research investigating EFL learners’ perceptions of collaborative writing (CW henceforth) is still limited. The present study explores EFL students’ attitudes and perceptions toward CW. The study involved 30 L2 students enrolled in a writing course at one of the largest universities in Saudi Arabia. The course was divided into two parts: individual writing (IW) for the first month (four weeks) and collaborative writing for the second month (four weeks). The study uses a within-groups mixed methods design whereby the same group of students received both the individual writing and collaborative writing assignments for exploring participants’ attitudes toward collaborative writing as compared to their views toward individual writing. The same self-report survey (6-point Likert-scale) was used two times (after each writing condition) to determine the participants’ views of each writing condition. In addition, semi-structured interviews were conducted to gain qualitative insights while exploring the participants’ views toward the two writing conditions they experienced as well as to find out the benefits and challenges they faced. Results show that participants reported the effectiveness of CW significantly higher than individual writing. The analyses reveal a statistically significant difference where ratings of CW were higher compared to IW, indicating helpfulness of CW in enhancing not only their writing skills but also their learning of all four English language skills. Despite some reservations, the majority of the participants were supportive of the CW experience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".