Undergraduate Research Learning in the Liberal Arts: A Case Study of Transformative Student-Faculty Collaborations
Bibliographic record
Abstract
To cultivate a learning environment promoting meaningful engagement with research, Huron University College—a small, primarily undergraduate liberal arts institution—launched the Centre for Undergraduate Research Learning (CURL). One major initiative of CURL's pilot phase was to fund extracurricular research opportunities (Student Fellowships) for undergraduate students. These projects enable students to conduct independent research projects with the guidance of a faculty mentor. The current paper presents the findings from a case study of the first four CURL Student Research Fellowship award recipients and their faculty mentors, using the concept of transformative experience (Heddy and Pugh, 2015) as the lens to conduct a content analysis of participant interviews. Our findings show evidence of substantive dialogue and active collaboration between students and their faculty mentors, providing a safe space for students to experiment, explore and develop their research skills. The students articulated development of specific skills related to research process, connection between theory and practice, as well as personal intellectual and interpersonal gains, which are suggestive of a transformative experience in progress. Although this paper reports on a limited sample, the findings may provide insight into the potential transformative impact of mentored undergraduate research experiences in the liberal arts.
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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 | 0.023 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.027 | 0.014 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 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".