Pedagogical practice in mainstream university literature courses with generation 1.5 and international ESL participants
Bibliographic record
Abstract
The following mixed-methods study explored the pedagogical practices of mainstream instructors in literature classes with NNS participants at a university in British Columbia. The inclusion of NNS students in these courses presents challenges due to various educational differences as compared with NS peers. This often necessitates changes in the teaching practices of instructors who might have little experience or training in the instruction of NNS students. Participants included three instructors, 33 NS students and 17 NNS students. Results indicated that each instructor employed different types of instruction in their class, including practices implemented specifically for their NNS learners which appeared dependent on experience or the number of NNS participants. Learner perception of these practices varied, with international ESL, Generation 1.5, and NS students all exhibiting preferences unique to their groups. This suggests that university instructors are active in making pedagogical adjustments in classrooms inclusive of students with diverse language abilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 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 teacher head, 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".