Exploring the Factors Affecting Destination and Institutional Choice of Educational Tourists of Emerging Economies: The Case of Nigerian Students in North Cyprus
Bibliographic record
Abstract
Substantial number of Nigerian educational tourists is travelling each year for tertiary\neducation, making Nigeria a leading student exporting country in the world\nparticularly in African continent. Although USA, Canada, UK, and Australia were\nthe most common destinations, in recent years substantial number of educational\ntourists has also traveled to some other European and Asian countries. Recently\nNorth Cyprus has become an important destination for many Nigerian educational\ntourists despite its relatively young and developing tertiary sector. The research, aims\nto explore the factors affecting decisions of Nigerian educational tourists regarding\nstudy abroad from an educational tourism perspective. Knowledge about the reasons\nbehind why Nigerian students have been increasingly enrolling to universities in\nNorth Cyprus is limited. Here it was aimed to make a contribution to the literature by\nthoroughly investigating this issue. Using the pull-push model, the researcher\nconducted a qualitative research to detect and examine factors influencing host\ncountry and host institution choices of Nigerian educational tourists and also to\nidentify influences pushing them to seek for tertiary education opportunities\nelsewhere. The research identified four main categories of push-factors (family and\npeer influence, problems at local higher education system, problems at local higher\neducation institutions, and personal reasons) that encourage and sometimes force the\nNigerian educational tourists to seek for tertiary education alternatives outside their\nhome country. Besides, six main categories of pull-factors (access, cultural factors,\nenvironmental factors, financial factors, plans for future, and influence of others) that\nattract Nigerian educational tourists to North Cyprus were identified. Finally, the\nresearch findings revealed that five main categories of factors (academic factors,\nadmission, financial factors, influence of others, and language) influence the decision\nof Nigerian education tourists in selecting the host institution.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".