MétaCan
Menu
Back to cohort
Record W4406824681 · doi:10.56397/rae.2025.01.06

The Role of Faculty in Designing Multicultural Curricula to Support International Student Adaptation

2025· article· en· W4406824681 on OpenAlexaffabout

Bibliographic record

VenueResearch and Advances in Education · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Student and Expatriate Challenges
Canadian institutionsLaurentian University
Fundersnot available
KeywordsCurriculumAdaptation (eye)MulticulturalismPedagogyEngineering ethicsPsychologyMathematics educationMedical educationSociologyEngineeringMedicine

Abstract

fetched live from OpenAlex

Canada’s higher education institutions have become a global hub for international students, fostering cultural diversity while presenting unique challenges related to adaptation and inclusion. This paper explores the pivotal role of faculty in designing multicultural curricula to address these challenges, enhance international student adaptation, and promote inclusivity. A multicultural curriculum integrates diverse cultural perspectives into academic content, enabling international students to feel validated and engaged while equipping domestic students with critical intercultural competencies. Faculty efforts to incorporate global viewpoints, adopt inclusive pedagogies, provide academic support, and foster intercultural competence are essential in creating supportive learning environments. The benefits of such curricula extend beyond individual student success, contributing to institutional reputation, fostering social cohesion, and preparing all students for success in an interconnected global society. By prioritizing multicultural curriculum design, Canadian universities can strengthen their leadership in equity, diversity, and global education. This paper underscores the importance of faculty initiatives in shaping inclusive educational practices that benefit both international and domestic students, ensuring a more equitable and globally conscious academic environment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.059
GPT teacher head0.517
Teacher spread0.458 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueResearch and Advances in EducationSame topicInternational Student and Expatriate ChallengesFrench-language works237,207