Supporting African Canadian and First Nations Students: Strategies for Success
Bibliographic record
Abstract
The Transition Year Programme (TYP) at Dalhousie University is designed to increase the successful participation of First Nations and African Canadian students in university studies. This paper provides some general information about the TYP, its genesis, current structure, and some of the challenges faced by students, then focuses on the evolution of one component of the Programme, a course entitled Strategies for University Learning. One particular assignment in this course was inspired by discussions with the students about how they believe their cultural background and experiences influence their learning and motivation. The interaction between cognition and culture is infinitely complex, and any attempt to understand it must take into account not only contemporary theories of learning, but also information from students themselves about their own educational struggles and successes. Since many of our students have encountered racism and prejudice and some seem to have very little moral support as they embark on the often intimidating journey into academia, the instructor decided to include in the course an assignment that would allow some of these issues to be explored in greater depth. Included in this paper are some of the responses to that assignment, especially what it revealed about the students’ prior learning experiences and their educational role models. Also discussed is the question of independent versus collaborative learning and whether students’ comments confirm what researchers have discovered about cognitive and motivational styles. The final section of this paper explains the ongoing support provided to students upon completion of the Transition Year Programme.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.004 |
| Scholarly communication | 0.009 | 0.002 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.003 |
| 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".