Postgraduate Students' Perceptions of Supervisor and Qualifications that is Sought in the Supervisor Selection
Bibliographic record
Abstract
In postgraduate education, the supervisor is a very important actor in terms of the quality of the education process. Therefore, how graduate students perceive supervisor is important in terms of the quality of the educational process. In this study, it was aimed to determine the postgraduate students’ perceptions of supervisor and qualifications sought in the selection of supervisor. It is thought that determining how the supervising faculty members are perceived by postgraduate students and what the criteria are for the selection of supervisors may contribute to the field in terms of understanding the student and supervisor relationship on an academic basis in postgraduate education. This research is a qualitative study. The phenomenological design was used in the study. 51 postgraduate students studying in various departments at Dicle University, Institute of Educational Sciences participated in the study in the 2017-2018 academic year. As the data collection tool, a semi-structured interview form was developed by the researchers and used in the study. According to research findings, the criteria that graduate students want to consider in the selection of supervisors are seen as “Having a good command of subject”, “Good communication skills”, “Guidance”, “Close to my field of interest”, “Openness to innovation”, “Having the knowledge of method”, “Entrepreneur”, and “Experienced”. The findings of this research can be used in supervisor training programs to be organized in the field of graduate education. Research can be conducted to examine the expectations of the supervisor from the graduate students.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".