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Record W4409458973 · doi:10.3390/educsci15040494

A Collaborative Online International Learning (COIL) Experience in Early Childhood Teacher Education

2025· article· en· W4409458973 on OpenAlexaboutno aff
Kristin Severinsen Spieler, Randi Engtrø, Anne Karin Vikstøl Olsen

Bibliographic record

VenueEducation Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationEducational technologyPedagogyCollaborative learningPsychologyEarly childhood educationComputer scienceMultimedia

Abstract

fetched live from OpenAlex

This study explores the use of Collaborative Online International Learning (COIL) as a pedagogical method to enhance intercultural competence among Early Childhood Teacher Education (ECTE) students, with an emphasis on Indigenous perspectives in Norway and Canada. Using qualitative focus group interviews with Norwegian students engaged in a COIL project with Canadian peers, this research identifies key pedagogical benefits and logistical considerations of this approach. The findings indicate that COIL enhances critical intercultural skills, such as cross-cultural communication and collaboration. This study highlights the necessity of establishing clear guidelines and objectives from the beginning, alongside active teacher participation, to foster a supportive environment that builds student confidence and autonomy. Additionally, COIL has broadened students’ understanding of cultural perspectives, which is valuable for their application in early childhood education settings. Ultimately, this study positions COIL as a valuable method for promoting intercultural collaboration and embedding Indigenous perspectives. This approach serves as a form of internationalization at home, preparing students to integrate diverse cultural insights into their professional roles in Early Childhood Education and Care.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.025
GPT teacher head0.430
Teacher spread0.406 · 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 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

Citations7
Published2025
Admission routes1
Has abstractyes

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