Exploring graduate student learning in applied science and student-supervisor relationships: views of supervisors and their students
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study presents the results of a questionnaire about the learning that occurs at graduate level and how the supervision of research contributes to this learning. Graduate students (PhD and Masters) and academic staff who supervise graduate students in applied science were surveyed. Graduate student responses exemplified how critical the relationship with their supervisor is in the success of their research term. The descriptive answers given by supervisors demonstrated their genuine interest in graduate school learning and showed they are cognizant of many issues pertaining to culture and learning environments in graduate study. The questionnaire sought to expand the trends and concepts identified by phenomenographic interviews with graduate students and supervisors. Other important insights such as opinions about coursework, learning environments and barriers are highlighted. Addressing such issues can only encourage an outcome that is beneficial to both students and supervisors through good research and a life-long skill of deep learning for the student.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it