Supervisory Styles and Graduate Expectations: Perceptions of Saudi Master’s Students
Bibliographic record
Abstract
The success and timely completion of postgraduate degrees depends heavily on the supervision provided to graduate researchers. The importance of supervision is well recognized yet there is limited research about how Saudi graduate students view their supervisors' styles and if these styles fulfil their needs. The current narrative inquiry study examined how Saudi graduate students view their supervisors' supervisory styles. Seven graduate students pursuing their M.A. TESOL degrees at a Saudi university participated in semi-structured interviews to share their supervisory experiences. The data analysis used Gatfield's (2005) four-styles framework to identify supervisory styles and emerging themes. The research participants described two main supervisory styles: the Contractual style which combines high structure with high support and the Laissez-faire style which features low support with low structure. The participants experienced two additional supervisory styles which included Pastoral (low structure, high support) and Directorial (high structure, low support). Most participants showed satisfaction with their thesis supervision, yet some students encountered obstacles and displayed minimal satisfaction. The study suggests several recommendations for program stakeholders. The supervisor-supervisee relationship requires improvement through better open communication and mutual understanding development. Both students and supervisors need clear explanations about their responsibilities and expectations during the initial stages of thesis work.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".