Vertical Integration of Mentorship-Based Experiential Learning Framework in Core 2nd Year Computer Engineering Courses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To address the pedagogical challenges in the fast-evolving fields of computer and software engineering, we have developed a mentorship-based experiential learning framework that incorporates flipped classroom, live-coding sessions, in-class open-floor discussions, and project-driven lab designs to maximize student learning outcomes. This framework incorporates a mid-size software project across two second-year computer engineering courses, embedding it vertically into the Computer Engineering curriculum at McMaster University. The project, typically suited for a two-semester standalone course, aligns theoretical knowledge with hands-on application both in class, during lab sessions, and asynchronously at home. With 35.5% response rate to the anonymous exit survey, the student feedback indicated significant improvements in classroom engagement, the overall learning experience, and the confidence in pursuing self-directed software projects. The framework has yielded promising results in its initial implementation, with ongoing efforts of continuous data collection, further framework optimization, and extension to upper-year courses.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it