Curriculum and Pedagogy of Transformation: How to Improve EAL Students’ Places and Roles at Simon Fraser University
Bibliographic record
Abstract
Traditionally, university students are deemed to be the people who have to take most of the responsibilities for their academic and lived experiences. Teachers and the university set a stage for the students to perform, yet it is the performers’ motivation and competency that determines the quality of their performance and experiences. Even though universities in Canada have sought to provide a variety of resources and supports, this perception is still deeply rooted in the mind of the people who are involved in the operation of higher educaton, especially the students themselves. This ideology is manifested to the greatest extent in the case of international students who speak English as an additional language (EAL) because not only do they experience difficulty in accessing their host community of practice, but also undergo tremendous stress and disappointment as they interpret their places and roles in EAL context to be subordinate. EAL students’ low self-efficacy and the institution’s denial of funds of knowledge (e.g. writing skills in L1) often cause them to reconstruct subordinate identities which require external supports and internal transformation to alter the status-quo. This paper examines ways to promote both the external supports, from the institution and its members in authority, and internal transformations that can occur within the EAL students themselves based on the supports given.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".