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Record W4291583626 · doi:10.32674/jcihe.v14i2.3808

The Smell, the Emotion, and the Lebowski Shock: What Virtual Education Abroad Can Not Do?

2022· article· en· W4291583626 on OpenAlexaff
Wei Liu, David Sulz, Gavin Palmer

Bibliographic record

VenueJournal of Comparative & International Higher Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsStudy abroadEmbodied cognitionIntercultural learningInternationalizationPedagogyNarrativeInternational educationPsychologyCultural competenceHigher educationSociologyPolitical scienceComputer scienceBusiness

Abstract

fetched live from OpenAlex

Education abroad has been a key vehicle for students’ intercultural learning. In response to the international mobility challenge due to the COVID-19 pandemic, many institutions have tried to shift to virtual programs in an attempt to provide continued education abroad experiences. This situation has amplified discussions about online education abroad programs as a way to address some equity issues in the internationalization of higher education. However, there seem to be few discussions about differences between physical and virtual programming with regard to students’ intercultural learning experiences. Fundamentally, what dimensions of traditional education abroad programs can and can not be replicated by online programming? Through a narrative inquiry with three international educators on their own intercultural learning experiences, this study argues that the personal cultural immersion and the associated embodied learning of complex nuanced cultural instances cannot be replaced by virtual programming.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.386
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2022
Admission routes1
Has abstractyes

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