Alternative Forms of Mobility in an Emergency Remote Teaching Context: A Study of Greek Undergraduate Students’ Attitudes
Bibliographic record
Abstract
Since the outset of the COVID-19 pandemic, there has been a lot of talk about alternative ways of student mobility. Higher Education Institutions are adopting new forms of mobility to provide flexibility. Among them, hybrid mobility and internationalisation activities at home are offered to university students. Within this framework, a preliminary study has been conducted to investigate Greek undergraduate students’ attitudes towards alternative solutions devised by Higher Education Institutions in an emergency remote teaching context in a time of global crisis due to the coronavirus. In essence, the present study addresses the following research question: How do undergraduate university students in Greece view hybrid mobility or internationalisation activities at home compared to physical mobility? More specifically, 57 students from two public universities in Greece completed an online questionnaire and five students were interviewed. Both the questionnaire and the semi-structured interviews were designed to measure students’ attitudes towards physical mobility, hybrid mobility and home-based internationalisation. The findings demonstrate that although the pandemic has not notably affected students’ attitudes towards Erasmus+ mobility, most of them prefer physical mobility to alternative forms of mobility as it provides a more complete and unique experience. The findings obtained herein are used to make suggestions on alternative ways of making home-based, online and blended internationalisation activities more effective, inclusive and engaging in the years to come.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".