A Study on the Perceptions of Secondary School Students regarding the Form-focused and Communication-focused English Instruction
Bibliographic record
Abstract
Form-focused instruction (FFI) and communication-focused instruction (CFI) are two different L2 or foreign language teaching approaches. In actual teaching practice, almost every EFL teacher has a preference for them so that these two instructional approaches dominate EFL classrooms to a great extent. This study, by using a self-designed questionnaire, attempts to examine student perceptions toward FFI and CFI. The subjects in this quantitative study were 300 ninth graders and 300 twelfth graders from two public urban schools. Findings from two-way MANOVA analysis revealed that: 1) Both ninth-grade and twelfth-grade students held highly positive perceptions toward CFI, but they were not very positive toward FFI. In contrast, ninth graders showed more positive perceptions toward FFI than twelfth graders. 2) Gender differences existed in student perceptions toward FFI. Male students were more positive toward FFI than female students. 3) Results showed that the two predictors FFI and CFI had certain correlations with the academic achievement of ninth-grade and twelfth-grade students. Based on the findings of this study, a few constructive conclusions are as follows: 1) EFL teachers are encouraged to apply the communicative approach in class to foster and develop secondary school students’ communication skills. 2) Teaching grammar to junior high and male students is likely to achieve effective results. 3) EFL teachers need to take gender differences into account when they design English curriculum. 4) Both FFI and CFI can help students achieve academic success at school.
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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 | 0.003 |
| 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 | 0.001 |
| 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 | 0.001 |
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".