Hindering Factors that Prevent College English Students from Participating in Class Discussions: A Case at Jiangsu University, China
Bibliographic record
Abstract
During several non-participant observations of two advanced College English classes at Jiangsu University, it wasnoticed that most of the students did not engage in class discussions. To ascertain what the problem was, but fromlearners' perspectives, this research was conducted. Seventy-one students enrolled in College English at JiangsuUniversity volunteered to partake in this work. A self-administered questionnaire was used to gather the data. Thefindings indicate that most of the respondents did not take an active stance in class discussions because of their lackof knowledge on strategies to bear their thoughts or opinions. Other expressed that they did not know about thetopics to discuss in class, and that was a significant barrier to their performance. Besides, some participants doubtedto speak in class. That can be linked to their shyness. Knowledge about these findings is helpful for teachers andCollege English authorities to examine what kind of training should be offered to students and teachers to makesteady improvements.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".