A Case Study of ESL Students’ Remote Speaking Class Learning Experiences in a Canada University During the COVID-19 Pandemic
Bibliographic record
Abstract
The COVID-19 pandemic forced a transfer from face-to-face (F2F) learning to remote online learning in universities worldwide. A university in southern Ontario delivered English courses to language learners living globally. This study, adopting a photo-production visual method, explored four English as a second language (ESL) students’ perceptions of this online learning compared to typical F2F learning and investigated activities enabling speaking opportunities and students’ expectations for online learning. The results showed that students perceived minor differences between online learning and F2F learning, including a non-academic English environment, a sense of community, and instant communications. The learning process involved interactive and collaborative discussions and presentations that allow students’ speaking opportunities. The online discussions contributed to students’ confidence but lacked adequate feedback towards students’ speaking skills. Students expected more types of learning activities that contribute to collaborations among peers, a sense of belonging to the online community, and examination orientated English skills.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".