Student Communication Opportunities During a Teacher Planned ESL Class
Bibliographic record
Abstract
A classroom that implements Communicative Language Teaching (CLT) or Task-Based Language Teaching (TBLT) emphasizes the importance of student-centred learning that provides opportunities for students to learn from each other (Rahmatillah, 2019; Thorne, 2000; Chinyamurindi, 2018; Bruner, 1986). To explore student interaction in TBLT, this study investigates the opportunities students receive in an English as a second language (ESL) classroom to communicate about their personal experiences that are not directly related to the classroom topic. Transcripts from the House of Friendship, a Montreal community-based organization staffed by volunteer teachers and preservice teachers from Concordia’s BEd program in TESL, were analyzed for both teacher-to-student communication and student-to-student communication. The coding identified how many opportunities students had to discuss their own ideas, feelings and experiences as compared to information about the teachers’ planned topic. The findings indicated that students spend more time discussing the lesson topic than talking about unrelated personal experiences. The implications are discussed in terms of the distribution of student communication across different activity types and strategies for increasing opportunities to talk about personal experiences in ESL 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".