Bibliographic record
Abstract
Abstract This paper describes how Applied Linguistics (AL) seminar students that are proficient in languages other than English intern as classroom assistants (CAs) in foreign language classrooms. The CAs gain useful insights from the seminar on theoretical and pedagogical approaches, methods and techniques in L2 pedagogy and then apply this knowledge through their practical experience as mentors/tutors to language learners. A diverse range of second/foreign language courses thus benefit from these “participant-observers”. Seminar students report on their experiences through written and oral exercises, discussions and presentations, and finally through journal reflections which are first reviewed by their supervising language instructors before submission to the seminar professor. A review of these journal entries shows that placing informed classroom assistants into a second/foreign language classroom can be very helpful to language instructors, their students and the CAs themselves, as long as communication lines are clear and assumptions about theoretical perspectives and practical tasks are understood. Such a course would be a fruitful supportive option in Applied Linguistics programmes with access to second/foreign language programmes that would benefit from informed classroom aides.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.023 | 0.006 |
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".