Educational Experiences of the International Students in Graduate Programs in Turkey
Bibliographic record
Abstract
Educational quality determined by factors such as academic climate, physical environment and academic quality of universities are considered essential for growing numbers of international students. This study aims to reveal and analyze the experiences of international students studying at graduate education step in Turkey. To this end, it is intended to describe and analyze the language proficiency, course period and thesis period experiences of international students studying in different fields of graduate programs and their perception on how their expectations were met or their apprehension. Phenomenology, one of the qualitative research methods, is used in the study. Semi-structured interviews were conducted in the study to flexibly gather data regarding the views of the participants and the differences between their experiences. Purposive sampling and snowball sampling methods were used together in forming a phase of the participant group. Interviews were conducted with 23 students from 18 different countries who are currently in Istanbul and studying in various departments. Descriptive analysis was used to analyze the data gathered from these interviews to examine the graduate education experience of the international students in Turkey. The educational experience of the students is primarily positive, and the students believe that they have received a high-quality education and they were provided with excellent opportunities. However, not being able to acquire academic writing skills or communicate with the professors sufficiently and the unconformity of the graduate education programs with the international educational context are some of the significant problems that were mentioned.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".