Design of a Completely New First Year Engineering Program at the University of Saskatchewan
Why this work is in the frame
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Bibliographic record
Abstract
The rapidly evolving role of the engineering profession in society requires an engineering graduate with a more diverse and robust skill set than ever before. To answer this challenge, the University of Saskatchewan’s College of Engineering has embarked upon a complete redesign of its first year program. This project essentially started from a “blank slate” and posed the question, “If we could design any first year program that we wanted, what would we create?” The outcome of this endeavor is intended to be an extremely effective first year program that excites, engages and inspires students, and that holistically prepares them for the challenges to come in later years. In this paper, we review the broad learning objectives of our new first year, and the values that we applied to our decision making during its design.The overall project consists of three distinct phases: determination of required first year graduate attributes, development of program structure and delivery methods, and detailed course design. Phase I has been completed. It has left us with a detailed inventory of knowledge, skills, experiences, and attitudes, distributed across 23 content categories, that the College wants students to internalize by the end of their first year of study.We will outline the methods that we used to compile and refine this attribute inventory, including multiple approaches aimed at meaningful stakeholder engagement, surveys of existing first year programs across Canada, and an analysis of gaps and redundancies between the Saskatchewan high school curriculum and our existing first year program. We will also describe the 23 content categories used to organize the graduate attributes of the proposed first year program and how these categories are weighted in relative terms. 
 We share some of our key learnings from Phase I of the project, including which consultation strategies worked most effectively, why we focused on first year graduate attributes and not content, and key elements that will be emphasized in our new program. We will also briefly describe the process by which we are starting to develop the program structure and delivery methods i.e. Phase II.
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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 | 0.000 | 0.000 |
| 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