International student mobility and the politics of distance education
Bibliographic record
Abstract
Abstract Internationalization at a distance (IaD) has been loosely defined as distance education across borders or the international mobility of knowledge without human mobility. It is largely celebrated, for example, for its potential to improve global education access and mitigate environmental harm. However, this depoliticized positioning risks overlooking IaD's relationship to uneven human mobility flows structured by global inequities. In response, this paper calls for a critical IaD research agenda, starting by drawing attention to the mobility politics of IaD at the postsecondary level. First, it proposes a more nuanced conceptualization of IaD rooted in insights from critical border studies, described here as bordered distance education . Second, it suggests the use of two theorizations of capital—citizenship and motility—as avenues to deepen future analysis of not only IaD but also international student mobility more generally. Third, to demonstrate the application of these suggestions, it presents a critical policy discourse analysis of international student mobility policies during the COVID‐19 pandemic era and its aftermath (2000–2024) in Canada. This case study shows how (1) distance education can be used as a bordering tool, and (2) governments can manipulate international student mobility policy to ensure IaD primarily serves immigration, as opposed to educational, needs. Practitioner notes What is already known about this topic The growth of internationalization at a distance (IaD) has the potential to shift how international student mobility is structured, experienced and understood. IaD is loosely described as distance education across borders . There are limited critical studies of IaD. What this paper adds IaD is embedded in mobility politics and bordering practices. In addition to its educational purpose, IaD can allow international students to accumulate citizenship capital and motility in new ways. However, IaD can also be used as a governance tool to (1) recruit/distinguish between potential citizens, (2) manage migration flows and (3) ensure the uninterrupted mobility of capital. IaD raises key questions about the meaning of ‘international’ in the study of internationalization. A more nuanced and critical definition of IaD as bordered distance education stresses what is unique about IaD: Distance education characterized by encounters with bordering practices . Implications for practice and/or policy IaD can benefit from a more critical research agenda, as well as returning to distance education's intellectual roots focused on the politics of access. Immigration policies which attempt to govern international students' geographic mobility differently from domestic students' (eg, disincentivizing international student distance education) should ensure such policies do not negatively impact (1) international students' access to education or (2) education institutions' academic programme design.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.020 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".