Successful development of generic capabilities in an undergraduate medical education program
Bibliographic record
Abstract
The development of generic capabilities or graduate attributes in communication, teamwork, critical analysis of information, problem solving and ethical practice is widely recognised as a desired outcome of higher education. This emphasis on generic capabilities has emerged despite ongoing debates about the concept and development of such capabilities. A recent review of comprehensive audits of Australian universities has found little evidence that such outcomes are being achieved. We used data from four different evaluations, both qualitative and quantitative, to explore whether these important generic capabilities are being learned by undergraduate students in the University of New South Wales (UNSW) new Medicine Program. University of New South Wales medical students are significantly more positive than other UNSW students that their university experience is developing several generic capabilities. Measurements concerning generic skills development from the Australian 2009 Learning and Teaching Performance Fund process support these findings. Analyses of qualitative data from two methodologically different student surveys found consistent evidence that medical students value generic capability development in the UNSW program. Furthermore, we report evidence that current UNSW medical students rate their clinical learning in professional placements as a significantly better experience than students in the previous discipline-based program. We believe this is a consequence of generic capability learning in the early years of the new program, such that our students are better prepared to maximise the value of learning from professional experiences. Our results represent consistent evidence of successful generic capability development as a result of a program-wide innovation in undergraduate education. To validate further our conclusions, external assessments of our graduates' generic capabilities in-action in the workplace are currently being obtained.
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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 | 0.008 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 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".