The Integrative Curriculum in EAP Programs: Design and Instructional Considerations
Bibliographic record
Abstract
International students, specifically students who study English for Academic Purposes (EAP), are an increasingly important and large part of the makeup of Canadian post-secondary institutions. As these students have diverse learning needs and goals, institutions need to properly support these learners to be successful in academic settings. A review of the literature explores the increasing need to support this particular student population; approaches to the teaching, learning, and programming of EAP courses and programs; and strategies in and beyond the classroom to support these learners. This chapter offers design considerations and suggests that EAP curricula be integrative in nature. This can be achieved through choosing relevant topics, incorporating experiential learning opportunities, designing collaborative learning tasks, discussing issues of culture, and planning purposeful community connections. Approaching the development of EAP curricula through an integrative lens will ensure learners who are ready for post-secondary studies in academic fields. Classroom examples from the author’s professional experience are offered. Discussion of how to achieve integrative EAP curricula in virtual learning environments is also included.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".