WHAT IS ENGINEERING SCIENCE? DEFINING A DISCIPLINE THROUGH A CROSS-INSTITUTIONAL COMPARISON AND A MULTI-INSTITUTIONAL WORKSHOP
Bibliographic record
Abstract
The Division of Engineering Science at the University of Toronto offers a complex, multidisciplinary undergraduate program, commonly known as "EngSci”. We are in the first of a multi-year project titled ROLE (Realigning Outcomes with Learning Experiences), designed to proactively realign curriculum, pedagogy, students, and brand with our program goals. The first step in this process is to understand the state of Engineering Science as an academic discipline more broadly, and to better understand its role in the broader engineering and science landscape. To better understand the discipline, we have used the academic plan model to compare eight engineering science programs from around the globe. The academic plan model supports the identification of internal and external factors that shape academic programs and frames the academic plan itself as seven related components that make up curriculum. Utilizing public-facing documentation such as websites and grey literature, we compared the IESC (International Engineering Science Consortium) programs and found differences in fundamental curriculum content, sub-disciplinary foci, organizational structure, and sources of external influence. Concurrently, we conducted a workshop with members from the IESC to facilitate dialogue on the state of the discipline. This workshop resulted in a number of interesting artifacts, documenting the perspective of the participants. Some key themes that emerged included a strong focus on fundamentals and first principles; a focus on non-traditional and rapidly developing sub-disciplines, using the notion that Engineering Science can act as an “incubator” for new disciplines; and a diversity of views on the relationship between science and engineering within Engineering Science programs. Finally, the paper paves a way forward for the next phase of the work, which involves interviewing program faculty and alumni to further understand perceptions of the discipline and the positioning of the discipline in the broader science and engineering landscape.
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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 | 0.069 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.012 | 0.012 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".