A comparative study of the effects of teacher-initiated planned preemptive and reactive focus on form on L2 learners’ accuracy in narrative writing
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Although researchers in the area of second language acquisition agree on the effectiveness of form-focused instruction, there is little consensus on the appropriate time to direct learners’ attention to linguistic items, that is, whether before or after the error occurrence [Nassaji, H. 2010, “The Occurrence and Effectiveness of Spontaneous Focus on Form in Adult ESL Classrooms.” The Canadian Modern Language Review 66 (6): 907–933; Panahzade, V., and J. Gholami. 2014, “The Relative Impacts of Planned Preemptive vs. Delayed Reactive Focus on Form on Language Learners’ Lexical Resource.” The Journal of Language Teaching and Learning 4 (1): 69–83]. In this regard, adopting a quasi-experimental design, the present study attempted to compare the effects of two techniques of focus on form (FonF), namely teacher-initiated planned preemptive and reactive FonF, on the accurate use of English third person singular -s in L2 learners’ narrative writing. Thirty-two English learners selected out of a total of 70 following a Quick Oxford Placement Test were randomly classified into two groups (one experimental and one comparison) each receiving a different FonF instruction during narrative tasks. Analysis of the groups’ performance on the pretest, immediate posttest, and delayed posttest revealed that both techniques were equally beneficial in bringing the form in focus to the center of the learners’ attention. It can, therefore, be suggested that the teachers need to observe the time when deciding to draw the learners’ attention to the linguistic forms.
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.
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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it