Facilitating Dialogue Across Disciplines: A Thematic Learning Community at Sir Wilfred Grenfell College
Bibliographic record
Abstract
The reputation of Sir Wilfred Grenfell College, a campus of Memorial University of Newfoundland, is a narrative in which undergraduate student teaching is at the heart of the institution’s mandate. Central to this narrative is the premise that a lower student/faculty ratio enhances the learning environment as it increases the potential for interaction between the two. However, a growing awareness in post-secondary education is the necessity of students interacting with each other as an important element in facilitating intellectual growth and constructing a sense of belonging within the academy. At Sir Wilfred Grenfell College, a psychology and a French professor piloted a thematic learning community project in the fall of 2006 bringing together 16 students registered in introductory French and psychology courses. These students attended both classes together and met once a week for an additional 50-minute session. The premise of the additional session, as well as the project itself, was to enable students to appreciate the overarching themes connecting two seemingly unrelated disciplines and to understand better the interconnectedness of their first-year undergraduate experience both intellectually and personally. This paper will outline how the learning community project at SWGC fits the institutional mandate, how it has been influenced by recent trends in pedagogy of higher learning, and how the project was designed and executed.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".