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Record W3028139488 · doi:10.1080/14647893.2020.1766008

Tertiary dance education in inclusive settings: teachers’ intercultural sensitivity for teaching international students

2020· article· en· W3028139488 on OpenAlexaff
Li Wang

Bibliographic record

VenueResearch in Dance Education · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicGlobal Education and Multiculturalism
Canadian institutionsAssociation of Canadian Universities for Northern Studies
Fundersnot available
KeywordsDancePedagogyInclusion (mineral)NarrativePsychologyDance educationQualitative researchSociologyMathematics educationSocial scienceSocial psychologyVisual arts

Abstract

fetched live from OpenAlex

In internationalised dance education, many teachers undertake inclusive philosophies and identify themselves as inclusive educators. But there may be possible differences between theories in minds and practices in studios, leading to the research inquiry: How might dance teachers’ teaching practices for international students extend from their intercultural sensitivities in inclusive-oriented tertiary education? In this research, international students are identified as individuals who move across national boundaries from Eastern countries to enrol in Western institutions. Participants are recognised as self-defined inclusive educators who have teaching experiences with international students. The research utilises Milton Bennett’s Developmental Model of Intercultural Sensitivity as a critical framework to understand different intercultural competencies. The framework also guides the demonstration of results in a sequence: Denial, Defense, Minimisation, Acceptance, Adaptation and Integration. The results are tangible narratives that indicate different intercultural sensitivities from participants with inclusive teaching intentions. Data were gathered through semi-structured interviews and analysed in a qualitative content analysis process. The study implies the gap between teachers’ inclusive intentions and teaching experiences, which could facilitate a reflection on educational inclusion for international dance 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 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)0.003
metaresearch head score (Gemma)0.007
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 score0.252
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.059
GPT teacher head0.510
Teacher spread0.451 · 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

Citations9
Published2020
Admission routes1
Has abstractyes

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