“I Learned How to Think, Not What to Think.” Student Perspectives on an Interdisciplinary Undergraduate Honours Programme
Bibliographic record
Abstract
The Arts and Science Honours Academy (ASHA) is a unique interdisciplinary undergraduate honours programme at a large research-intensive university in Canada. Data were collected in early 2020 from 108 past and present students, representing the first eleven cohorts of the programme. Triangulating results from quantitative and qualitative analyses, we describe the ASHA students’ educational and social experience during their time at university and, for those who have graduated, their post-graduate activities. Situating our investigation within previous literature examining interdisciplinary undergraduate learning communities and high impact practices, we assess whether students from arts and science disciplines experienced the programme differently, and which aspects of the programme were most impactful. We find that academically, students reported benefiting from the exposure to interdisciplinary thought, the opportunity to do research, and the study abroad requirement. Socially, students reported benefiting from the connections they formed with a small cohort of high achieving peers from a variety of disciplinary backgrounds. While science students reported benefitting the most from ASHA socially, arts students were more likely to indicate that the programme influenced their careers following graduation. These findings provide evidence to support the creation and design of future interdisciplinary undergraduate programmes.
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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 | 0.009 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".