Pull factors influencing enrollment of Mainland Chinese students in Taiwanese universities: An empirical analysis
Bibliographic record
Abstract
A rapidly declining birthrate in Taiwan has placed pressure on universities to bolster waning enrollment. At the same time, Mainland China is becoming an enormous exporter of international students, and the close geographic proximity between Taiwan and China has resulted in many Chinese students enrolling in Taiwanese institutions. Between 2012 and 2013, over 75% of Chinese exchange students studied in the United States, Great Britain, Australia, or Canada. In contrast, Taiwan was unable to attract a meaningful number of these students. Thus, the issue of whether institutions in Taiwan appeal to Mainland Chinese students is worthy of exploration. This study recruited 228 Chinese students that studied at universities in 2012 in order to identify factors that influenced the enrollment of students from Mainland China in Taiwan. Survey results led us to four important findings as follows: 1) sociocultural and school-related factors had the biggest influence on the decision to study in Taiwan; 2) college selection did not influence pull factors, learning satisfaction, or the intention to pursue further education; 3) school-related and personal factors influenced learning satisfaction as well as the intention to pursue further education; and 4) learning satisfaction has a direct and mediating influence on the intention to pursue further education. These findings yield recommendations that can serve as a reference for Taiwanese universities.
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 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".