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Record W4402909162 · doi:10.32674/jcihe.v16i4.5459

“What Does Critical Thinking Mean to You?” A Narrative Inquiry of Graduate Students’ Perceptions

2024· article· en· W4402909162 on OpenAlexaboutno aff
Farzaneh Ojaghi Shirmard, Edward R. Howe

Bibliographic record

VenueJournal of Comparative & International Higher Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativeCritical thinkingPerceptionPsychologyMathematics educationGraduate studentsNarrative inquiryPedagogyArtLiterature

Abstract

fetched live from OpenAlex

Critical thinking is an important part of higher education in Canada, and many education systems worldwide, but not all cultural contexts. Critical thinking enables students to expand their perspectives and better navigate important personal and professional decisions. This narrative inquiry compares Canadian and Iranian international graduate students’ perceptions of critical thinking. Through conversations with eight participants, deep and complex transcultural understandings of critical thinking were unearthed. Findings indicate that while Canadian participants can articulate informed viewpoints about critical thinking, some Iranian participants require further knowledge to construct their critical thinking conceptualizations. Results suggest that Canadian higher education needs to consider international students’ limited background knowledge of critical thinking and must provide more opportunities to develop critical thinking skills. This study offers insights for higher education policymakers, curriculum developers, and practitioners to consider international and intercultural perspectives to facilitate critical thinking in both international and domestic students.

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)0.014
metaresearch head score (Gemma)0.026
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 score0.087
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.023
Scholarly communication0.0100.005
Open science0.0010.005
Research integrity0.0020.007
Insufficient payload (model declined to judge)0.0010.000

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 head0.130
GPT teacher head0.510
Teacher spread0.379 · 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
Published2024
Admission routes1
Has abstractyes

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