COVID-19 Pandemic Experiences: Cross-Border Voices of International Graduate Students in Australia and America
Bibliographic record
Abstract
The study analyses cross-border experiences of international graduate students in two universities, one in Australia and the other in the United States of America, during the COVID-19 pandemic to understand how this impacted their learning and wellbeing. COVID-19 crisis led to dramatic changes in higher education institutions worldwide, affecting the academic and social life of international students, and as well opening windows of opportunities for them. International students of African and Asian backgrounds were purposely selected for the study. Data were collected with an open-ended qualitative questionnaire and analysed thematically. Findings indicate international students had mixed experiences, including stress and hardship, isolation, fear and insecurity, frustration and helplessness that affected their academic and social lives and wellbeing. Other students however developed strong connections, resilience, confidence, and optimism for the future. The shared cross-border experiences raise awareness to the global impact of COVID-19 in higher education. Findings have implications for how universities could respond to the needs of international students, which must be inclusive, equitable, and human-centric, during unforeseen crises.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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".