A Study of Students’ Silence and Teachers’ Questioning Strategies in College English Classroom
Bibliographic record
Abstract
With the development of English language teaching, teachers have paid more and more attention to communicative language teaching and made efforts to encourage classroom interaction. However, many college students are in the habit of keeping silent which discourage teachers and restrict the effective communication between teachers and students. As one of the biggest problems, it has attracted much attention from more and more researchers. This paper here aims to investigate the major causes of students’ silence by means of questionnaire and class observation. Through a detailed description and analysis of the collected data, students’ learning motivation and reasons for silence in classroom are made clear, anxiety being the main cause triggering students’ silence. Meanwhile on the basis of analysis of teachers’ teaching mode, the paper points out that teachers’ questioning strategies have large influence on students’ silence in class, and improper teaching mode are bound to make students feel anxious. Finally, suggestions about improving teaching strategies are put forward for the purpose of lessening students’ feeling of anxiety and decreasing their silence in classrooms.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".