Transitions: Orienting to Reading and Writing Assignments in EAP and MBA Contexts
Bibliographic record
Abstract
With the increased enrolment of non-native speakers from diverse cultural backgrounds in university programs, researchers have begun to explore how such students cope with the academic challenges awaiting them (Leki, 2001; Spack, 1997). The present paper draws on data from a 2-year qualitative study of Chinese students enrolled in an English-medium Masters in Business Administration in a Canadian university. Specifically, we focus on how students' orientations to reading and writing assignments changed as they moved from an English for Academic Purposes (EAP) program to their MBA courses. Drawing on genre theory and activity theory, we suggest how these changes were related to differences in what was valued as learning in these two contexts (i.e., the construal or epistemic motive). Although as in Spack (1997), students adapted their reading and writing strategies to cope with assignments in the MBA program, the study also suggests how historically inscribed academic practices may mitigate against students' ability to appropriate relevant literacy resources.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".