The Impact of Studying English in China on Thai University Students’ Intercultural Competence
Bibliographic record
Abstract
The major purposes of this study aimed (1) to investigate the communication differences and cross-cultural adaptation of Thai university students studying English in China PR., (2) to investigate the problems of the Thai university students’ cross-cultural adaptation, as well as (3) to investigate factors influencing their intercultural competence. A structured questionnaire was conducted across 30 Thai students as the target group studying English at Yu’Xi Normal University China PR, selected by the purposive sampling technique. The results of the study revealed that 1) demographically, there was not much difference in adaptation between male and female target groups in terms of gender, age, and residency length; 2) negative attitudes in Thai university students to Asians caused a separation between Thai and Chinese groups due to the behavioural characteristics of Thai people who were concerned about speaking straightforwardly. In terms of communication ability, language affects communication directly between individuals and groups in everyday life and the classroom. Also, they all are looking to be positive, open-minded, and accepting; moreover, a new culture can be accepted by not setting yourself up, and language contributes to adapting across cultures to create mutual understanding, as well as to build relations with local people. Also, choosing a friend from various groups in different activities is necessary to exchange opinions with each other in the target society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".