Bibliographic record
Abstract
Internationalization and digitalization – how do these two higher education trends go together? Projects dealing with virtual mobility, collaborative online international learning (COIL), or virtual transnational education (TNE) have shown that the link between the international and the digital is not only a theoretical possibility, but already a reality in many higher education institutions. There is a considerable amount of literature about Open and Distance Education and Massive Open Online Courses (MOOCs) crossing national borders, and about supporting students in gaining intercultural competence and global awareness with the help of virtual media. Still, there remains a gap in the literature when it comes to conceptualizing a framework encompassing the manifold ways in which information and communications technology (ICT) can be used to internationalize higher education. In order to address this gap, this paper proposes an approach of drafting a framework for virtual internationalization in higher education, by focusing on its global, intercultural, and international dimensions. Résumé Internationalisation et numérisation – comment ces deux tendances de l’enseignement supérieur s’associent-elles ? Les projets traitant de la mobilité virtuelle, de l’apprentissage international collaboratif en ligne, ou de l’éducation virtuelle transnationale ont montré que le lien entre l’international et le numérique n’est pas seulement une possibilité théorique, mais déjà une réalité dans bon nombre d’institutions d’enseignement supérieur. Il existe une vaste littérature, qui dépasse les barrières nationales, concernant la Formation Ouverte et A Distance (FOAD) et les Cours en Ligne Ouverts et Massifs (CLOM) aussi bien que le soutien apporté aux étudiants pour développer une compétence interculturelle et une conscience planétaire à l’aide des médias virtuels. Pour autant, une lacune demeure dans la littérature quant à la conceptualisation d’un cadre englobant les multiples manières de prendre en compte les Technologies de l’Information et de la Communication (TIC) pour internationaliser l’enseignement supérieur. Afin de combler cette lacune, cet article propose une approche permettant d’esquisser un cadre pour l’internationalisation virtuelle dans l’enseignement supérieur en se centrant sur ses dimensions mondiales, interculturelles et internationales.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.006 | 0.039 |
| Scholarly communication | 0.017 | 0.022 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".