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Record W4386537660 · doi:10.5206/cie-eci.v52i1.13628

Internationalization at Home: A Reflection on a Semester-Long Online Collaborative Project Between Canadian and Indian Students

2023· article· en· W4386537660 on OpenAlexafffundvenueabout
Tiare Thiessen, Iwona Abraham, Liza Abraham

Bibliographic record

VenueComparative and International Education · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsUniversity of CalgaryAmbrose University
FundersGovernment of Alberta
KeywordsInternationalizationSustainabilityCompetence (human resources)Global citizenshipIntercultural competenceCitizenshipPedagogyStudy abroadInternationalization of Higher EducationCultural competencePolitical sciencePublic relationsPsychologySociologyBusinessSocial psychology

Abstract

fetched live from OpenAlex

In today’s global community, internationalization offers students a crucial advantage by developing their intercultural competence and global citizenship skills. Recent research on Internationalization at Home (IaH) has shown that students can benefit from this approach even without travelling. There has been minimal research conducted on how internationalization affects students’ attitudes towards environmental sustainability, which is another critical theme in our interconnected world. This study evaluates an IaH initiative’s impact on students’ environmental beliefs and values from Alberta, Canada, and Kerala, India. As an IaH initiative, this project engaged students in online collaboration with students from a different world region. Participants worked collaboratively on four tasks and completed an individual reflection assignment. Student and faculty feedback shows that participants improved their knowledge of environmental issues and their commitment to environmental sustainability. Additionally, students also demonstrated stronger intercultural communication and global citizenship skills.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.426
Threshold uncertainty score0.857

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0460.013
Scholarly communication0.0090.003
Open science0.0040.009
Research integrity0.0030.008
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.142
GPT teacher head0.501
Teacher spread0.359 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations1
Published2023
Admission routes4
Has abstractyes

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