MétaCan
Menu
Back to cohort
Record W4410510313 · doi:10.3390/educsci15050615

Intercultural Dialogue on Indigenous Perspectives: A Digital Learning Experience

2025· article· en· W4410510313 on OpenAlexaboutno aff
Kristin Severinsen Spieler, Anne Karin Vikstøl Olsen, Randi Engtrø

Bibliographic record

VenueEducation Sciences · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousPedagogyIntercultural communicationSociologyMathematics educationPsychologyLinguistics

Abstract

fetched live from OpenAlex

This research explores how intercultural dialogue through a Collaborative Online International Learning (COIL) project enhances students’ understanding and integration of Indigenous perspectives. The initiative connected Norwegian Early Childhood Teacher Education (ECTE) students with Canadian Teacher Education students to explore Sámi and Métis cultures. Using a qualitative design, focus group interviews with ECTE students employed a hermeneutic approach to interpret experiences and cultural reflections. These insights, analyzed systematically, demonstrated the COIL project’s effectiveness in facilitating intercultural dialogue, fostering intercultural competence, and encouraging self-reflection among participants. Participants developed invaluable skills for integrating Indigenous perspectives into future educational roles, supported by facilitation that enhanced cross-cultural dialogue and language skills. This study underscores the need for frameworks supporting sustained cultural engagement, acknowledging sample size limitations. Findings advocate for the broader integration of intercultural collaborations in strategies, emphasizing education that enhances cultural competence. Future research should expand with larger samples and varied cultures, using longitudinal studies to assess the impacts on professional development and optimize collaboration educational contexts.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
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 head0.031
GPT teacher head0.408
Teacher spread0.378 · 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 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

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEducation SciencesSame topicGlobal Education and MulticulturalismFrench-language works237,207