Thriving in Engineering: A Pilot Peer Mentorship Model for First-Year Students
Bibliographic record
Abstract
This paper describes a peer mentorship program piloted in a cornerstone first-year engineering course (ENG 1101: Renaissance Engineer 1) at the Lassonde School of Engineering in York University since fall of 2021. The mentorship program is designed to help first-year students develop the cognitive, emotional, motivational, and relational foundations for success and thriving in an engineering program. Students are brought together in small groups (termed “guilds”) for structured coaching sessions with an assigned upper-year engineering student as a mentor and participate in a total of five sessions, each with their own topic and learning outcomes. The program fosters students’ sense of belonging through participation in meaningful group activities and engaging students in a shared experience. Reflections from students and mentors about the program highlight the importance of building intentional opportunities that promote students’ sense of connection. Program challenges, refinements, and future directions are considered.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".