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Record W4415545857 · doi:10.5430/jct.v14n4p179

Formation of Transcultural Competence in the System of Art Education in the Context of European Integration

2025· article· W4415545857 on OpenAlexvenueno aff
Tetiana Humeniuk, Susanna Chakhoian, Dmytro Poliachok, Volodymyr Openko, Svitlana Borovyk

Bibliographic record

VenueJournal of Curriculum and Teaching · 2025
Typearticle
Language
FieldSocial Sciences
TopicEducation and Social Development in Ukraine
Canadian institutionsnot available
Fundersnot available
KeywordsIntercultural competenceCultural competenceCompetence (human resources)Visual arts educationUkrainianCultural group selectionCultural diversityCultural knowledge

Abstract

fetched live from OpenAlex

In the contemporary artistic space, the development of transcultural competence plays a vital role in the professional growth of an artist. This article aims to determine the level of transcultural competence among students of art institutions in Ukraine. The quantitative analysis was used for this purpose. The study involved 50 students of artistic specialities of Ukrainian educational institutions, who were included based on a purposive sample. The main instruments used in the study were a survey among students and the Cultural Intelligence Scale (CQS). The survey was conducted from 1 to 20 November 2024. The CQS allowed measuring different levels of transcultural competence: metacognitive, cognitive, motivational, and behavioural dimensions. The results indicate that students have average levels of cultural knowledge and are good at adapting their behaviour in intercultural environments. Students also expressed an average understanding of integrating different cultures in art (3.18 mean). At the same time, it was noted that students who participated in international conferences and exchange programs had high scores. The conclusions emphasise the further development of transcultural competence and offer the following recommendations: in-depth knowledge of other cultures through open lectures and seminars by artists from different countries, emphasis on project-based methods, and group discussions on the importance of different cultures for contemporary art.

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)0.006
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.205

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
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 head0.013
GPT teacher head0.308
Teacher spread0.294 · 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 routes1
Has abstractyes

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