Fostering science students as partnerships. Examining undergraduate students’ perspectives of pedagogical partnerships
Bibliographic record
Abstract
There has been a growing discourse within higher education to engage with Students as Partners (SaP) and to transform institutional culture by harnessing the strength of students and faculty working together. Engaging with SaP offers benefits to both students and faculty, yet there continues to be less research on SaP practices at the macro-degree level. The purpose of this study was to conduct a faculty-wide investigation of student-faculty partnerships within the Faculty of Science at a mid-sized university in Ontario, Canada. Through a mixed methods approach of surveys (n = 178) and semi-structured interviews (n = 10) with undergraduate students, we examined the types of student partnerships occurring within the Faculty of Science as well as gathered insights into students’ perspectives of the benefits and challenges they experience engaging in these partnerships. Collaborating with faculty on research projects, teaching assistantships, and being a student leader in an organization with faculty guidance were considered the most impactful partnerships among participants. Students also reported several social, personal, academic, and career-related benefits as a result of working in partnership with faculty members, while common challenges included barriers to engaging in activities, social barriers, power imbalances, difficult working environments, and personal challenges. By studying the benefits and challenges experienced by students, we provide advances towards creating an engaged learning environment that supports undergraduate student engagement, collaboration, and enhanced student-faculty relationships that in turn support recruitment and retention efforts.
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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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.011 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".