A Critical Analysis of Instructors' Perceptions of the Academic Skills of First Year International Graduate Students Enrolled in Education Courses
Bibliographic record
Abstract
Academic literacy is essential for English language learners to be successful in their graduate programs within a Faculty of Education in Ontario. In this paper, I argue that with careful collaboration between faculty members and English for academic purposes instructors, our international graduate students could be provided with an understanding of academic culture, discourse, genre, context and critical thinking needed for academic success. The main question addressed in the study is: what are instructors’ perceptions of the academic literacy skills of first-year international graduate students at an Ontario university? Through the researcher’s use of critical theory and participant interviews regarding the academic literacy of English language learner (ELL) graduate students, the Faculty of Education instructors at an Ontario university will inform the curriculum development of an English for Academic Purposes (EAP) program, as well as other stakeholders in this research. Critical thinking and disciplinary conventions are areas observed by the Faculty of Education instructors as needed additional support for ELL graduate students in the Faculty of Education. In conclusion, further collaboration between Faculty of Education graduate course instructors and EAP instructors are needed to further support ELL graduate students in their coursework. This study also explored implications for curriculum development of an English for Academic Purposes (EAP) program and various stakeholders at the university.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 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".