THAI STUDENTS’ DESTINATION CHOICE FOR HIGHER EDUCATION: A COMPARATIVE STUDY ON U.S, U.K AND AUSTRALIA
Bibliographic record
Abstract
The purpose of this study is to investigate the underlying factors for Thai students’ destination choice as well to explain the relationship between the influencing factors and decision making process of Thai students. Push and pull factors were used to explain the motivation underpinning students’ choice of study destination. A total of 660 self-administered questionnaires were distributed using convenience sampling at OCSC International Education Expo 2013, organized by the Office of Civil Service Com- mission (OCSC), on 2 November 2013, of which 640 were used for analysis. The results showed that both push and pull factors proposed in this study significantly influenced Thai students’ destination choice. It was found that the suitability of the environment factor and recommendations of friends and family were components of country characteristics (pull factor), which have the greatest influence on Thai student’s destination choice. Thai students’ destination choice was also influenced by the cost of education and degree (content and structure), physical facilities and resources and the value of educa- tion. On the other hand, personal factors is the push factors that can influence Thai students’ destination choice.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".