The Effects of Planned Focus on Form on Iranian EFL Learners’ Oral Accuracy
Bibliographic record
Abstract
One of the limitations of the meaning focused instruction in an EFL situation such as Iran is that a communicative approach helps Iranian learners to become fluent, but is insufficient to ensure comparable levels of oral accuracy. The purpose of this study was to investigate whether planned focus on form, and also what type of corrective feedback, would be useful for Iranian EFL learners’ oral accuracy. To this end, the study employed a quasi experimental design. Three intact classes were randomly selected as the control group (n=17), recast group (n=19) as experimental group 1, and delayed explicit and metalinguistic group (n=21) as the experimental group 2 respectively. All groups participated in six sessions of the task of story retelling. For all groups, learners were asked to read and summarize their own assigned story in a time limit of four minutes and retell it to the class. For the recast group, students were provided with recasts on their simple past tense errors; for the delayed explicit and metalinguistic group, the researcher corrected the learners' errors after they finished the retelling; and for the control group, there were no feedback on learners' errors. Learners’ improvement was measured by their oral accuracy during the six sessions of story retelling. One-way ANOVAs with post hoc comparisons indicated that all CF groups significantly outperformed the control group in the session six of story retelling and that the two feedback types were equally effective in promoting learners’ oral accuracy. These findings suggest that the planned focus on form can be an effective tool for the development of oral accuracy in the EFL situations. It can also be concluded that intensive recasts which are repeatedly focused on a particular structure are not different from explicit types of feedback in terms of their effectiveness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".