A mixed-method investigation into international university students’ experience with academic language demands
Bibliographic record
Abstract
Post-secondary education institutions with English as a medium of instruction have prioritized internationalization, and as a result, many universities have been experiencing rapid growth in numbers of international students who speak English as an additional language (EAL). While many EAL students are required to submit language test scores to satisfy university admission criteria, relatively little is known about how EAL students interpret admission criteria in relation to language demands post admission and what their language challenges are. This study, situated at a large Canadian university, integrated student and faculty member focus group data with data obtained from a domain analysis across three programs of study and a reading skills questionnaire. Findings suggest that many students and faculty members tend to misinterpret language test scores required for admission, resulting in surprise and frustration with unexpected level of language demands in their programs. Also, students experience complex and challenging language demands in their program of study, which change over time. Recommendations for increased student awareness of language demands at the pre-admission stage and a more system-wide and discipline-based approach to language support post-admission are discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".