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Record W4321385986 · doi:10.23887/ijerr.v5i1.44442

International Opportunities in Higher Education Promoted by the COVID-19 Pandemic: Results of A Three-Country Teaching-Learning Experience

2022· article· en· W4321385986 on OpenAlexaffabout
Jens Holst, Julie Hard, Mathieu J. P. Poirier

Bibliographic record

VenueIndonesian Journal Of Educational Research and Review · 2022
Typearticle
Languageen
FieldComputer Science
TopicE-Learning and Knowledge Management
Canadian institutionsYork University
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Higher educationCollaborative learningPolitical scienceMedical educationPsychologyPedagogyPublic relationsMedicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has brought challenges and opportunities to teaching in higher education. The sudden pivot from in-person to online education posed unprecedented challenges to both teachers and students. At the same time, the sudden worldwide suspension of traditional ways of lecturing opened a space for experiments with innovative pedagogic approaches and techniques, including various forms of real-time inter-university exchange and student cooperation. COVID-19 pandemic caused a sudden and disruptive shift to emergency remote learning and teaching, as well as a simultaneous halt to international mobility of students, faculty and staff. These changes to established modes of teaching and learning in higher education along with the de facto end of all international mobility efforts led global health course directors from York University in Canada and Fulda University of Applied Sciences in Germany to establish a globally networked learning environment involving shared virtual lectures and international collaborative group projects. Students reported benefits of an enriched learning experience through the sharing of different perspectives, approaches and debates with international professors and peers. Coordination relating to time differences and expectations played a key role in success and overcoming challenges for collaboration among students. The COVID-19 pandemic has shown that cross-border inter-university teaching and learning is a feasible and beneficial pedagogic option.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.884
Threshold uncertainty score0.388

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.232
GPT teacher head0.425
Teacher spread0.193 · 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.

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

Citations0
Published2022
Admission routes2
Has abstractyes

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