Contrastive Study on Learning Vocabulary through Role-play and Memorization among EFL Female Learners
Bibliographic record
Abstract
The present study was carried out to examine contrastive study on learning vocabulary through role-play and memorization among Iranian upper-intermediate EFL female learners. Seventy five Iranian EFL female students learning English in Hegmataneh English institute in Tehran were selected as the sample from the whole upper-intermediate female learners in every English institute in Iran. A pre-test of vocabulary was administered at the beginning of instruction to get convinced that the new words were unfamiliar to participants. Then, the participants were divided into an experimental and control group. There were thirty seven learners in experimental group and thirty eight learners in control group. The students in the experimental group were given the treatment, that is, they learned vocabulary through roleplay during twenty sessions. Whereas the participants in control group were given no treatment, that is, they learned vocabulary through memorization, as a traditional technique. At the end of the treatment, the same pre-test of vocabulary was given as a post-test to both groups, as experimental and a control group, in order to see which technique was more effective in learning vocabulary. By comparison of the mean scores of both groups, the results showed that there was a significant difference between role-play and memorization. Although both groups had promotions in learning vocabulary, experimental group was observed to make much more promotion in learning vocabulary through role-play than 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".