Best Practices in Teaching International Students in Higher Education: Issues and Strategies
Bibliographic record
Abstract
Regardless of their level of academic preparedness, international students face distinct challenges that arise from language issues as well as ones of a personal and social nature, all of which can lead to frustration and failure (Bossio & Bylyna, ). This article discusses an online survey carried out in a Canadian college that identified academic and sociocultural issues faced by international students and highlighted current or potential strategies from the input of 229 international students, 343 domestic students, and 125 professors. Findings reveal that counterproductive behavior may obstruct academic achievement and communication, and there is evidence of disagreement about international students’ academic strengths. A disconnect between participants was also found regarding academic expectations. Moreover, findings reveal that English language abilities are not the sole hindrance to academic success. Responses highlight the need for, and list steps toward, a more proactive and continual pedagogical evolution for faculty and postsecondary institutions to enhance the academic experience and success of international students.
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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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.019 | 0.007 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".