Cultivation of Cross-cultural Adaptability of Application-oriented University Students under the Background of Internationalization
Bibliographic record
Abstract
Under the background of internationalization, the communication between countries is more and more close, which requires the cross-cultural adaptability(CCA) of talents. The cultivation of CCA of application-oriented university students has a great impact on their future development. The cultural foundation of application-oriented university students is relatively weak, but their practical ability is very strong, which requires changing the traditional talent training objectives, combining the characteristics of application-oriented university students and the training objectives of CCA, promoting the effective combination of theory and practice, and improving the effectiveness of CCA training. This paper mainly studies the cultivation of CCA of application-oriented university students under the background of internationalization. This paper analyzes the causes of cross-cultural maladjustment, and then puts forward some measures to cultivate students' CCA in application-oriented universities. In order to understand the problems of application-oriented university students' specific cross-cultural adaptation, this paper adopts the form of questionnaire survey. The results show that the most common problem of application-oriented university students in cross-cultural adaptation is the language problem which accounts for 27%, followed by the interpersonal problem which accounts for 23%, which is also caused by the differences of language and culture in the final analysis. In addition, there are still work situation problems accounting for 13%, psychological problems accounting for 12%, problems caused by natural environment accounting for 11%, problems caused by daily life accounting for 9%, and values problems accounting for 5%.
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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 | 0.001 | 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) | 0.001 | 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".