Integration of Core First Year Engineering Courses into Sequenced Experiential Learning: The Integrated Cornerstone
Bibliographic record
Abstract
Until the beginning of the 2020 academic year, the first-year engineering program at McMaster University was organized as traditional courses to form a common curriculum for all students. The first year core courses were organized as i) Design and Graphics, ii) Computation, iii) Profession & Practice, and iv) Materials. Regardless of which engineering discipline a student enters in second year, the core courses provide a common base for important theory and applications required for the engineering design and development process. The challenge with traditional course organization continues to be concept linkages and attention competition. The purpose of this new approach was to integrate the learning objective of each traditional course into one experiential course through sequential Capstone-style project learning experiences– creating the Integrated Cornerstone. As the name implies, the approach offers the foundational blocks in the engineering student’s education. Focusing pedagogy on a tangible outcomes provides the opportunity to incorporate creativity, self-efficacy, and fosters a sense of community. The Achilles’ heel to a siloed collection of courses offering the Cornerstone approach is that students find themselves immersed in parallel independent projects resulting in unintended distraction. The Integrated Cornerstone merges the core courses learning objectives for better focus of pedagogy. While pandemic restrictions have complicated the quantified comparison of pedagogical approaches between the traditional method of curriculum delivery vs. the Integrated Cornerstone delivery we present aggregate qualitative outcomes of student success. The comparison of approaches and lessons learned for integration will be of interest to other educators seeking better integrated learning for the application of engineering theory in design.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".