Students as Engaged Partners in Directed Research Courses
Bibliographic record
Abstract
This report from the field reflects on the authors’ experiences in a directed research course on the topic of youth civic engagement in Canada. A literature review was co-written as part of a directed research course where the instructor was a visiting professor from the United States and the student was an undergraduate student in Canada. The content of this report was gathered during various stages of the directed research course and is informed by literature focused on students as engaged partners in teaching and learning in higher education. Specifically, we reflect on the ways viewing students as engaged partners can leverage their knowledge and lived experiences when engaging in directed research courses, especially when the student and faculty member may be coming from different countries in North America. In addition, we reflect on how designing a directed research course that views students as engaged partners can provide a rich ground for the redistribution of power in higher education and strengthen the quality of research through the co-creation of new knowledge and ideas.
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.
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 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.006 |
| Scholarly communication | 0.018 | 0.006 |
| Open science | 0.003 | 0.020 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".