The Effect of Cooperative and Individualistic Instruction on Vocabulary and Pronunciation Learning: A Case of Low-Intermediate Iranian EFL Learners
Bibliographic record
Abstract
The present study was carried out in order to find out about the effect of two instructional programs, namelycooperative and individualistic instruction on the vocabulary and pronunciation improvement of low-intermediate EFL learners. The subjects were 50 students at the fifth grade of Mellal school aged 10-12 in Esfahan in Iran, who were randomly assigned to the experimental and control groups. The two selected groups were instructed over a period of ten weeks. For this purpose, a pretest-posttest experimental design was used. Prior to the treatment, a test for both vocabulary and pronunciation was developed, piloted, and administered to check the homogeneity of the participants. Then, the students‟ scores in the homogeneitycheck test were used as the pre-test score, too. For the treatment, the learners in the experimental group were instructed via cooperative technique whereas the learners in the control group received instruction according to a teacher-centered method following an individualistic-instructional approach. At the end of the study, the same test was administered to both groups as the post-test. Results suggested that both individualistic and cooperative instruction can enhance vocabulary achievement of Iranian lowintermediate EFL learners. However, no significant difference was found between the two groups regarding their vocabulary achievement. However, there was a significant difference between the two groups regarding their pronunciation achievement, and, thus, it was concluded that the application of collaborative methods in EFL classes can lead to an improvement in the learners‟ pronunciation.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".