Design of a Completely New First Year Engineering Program at the University of Saskatchewan – Part II
Bibliographic record
Abstract
Over the last three years, the University of Saskatchewan’s College of Engineering has embarked upon a complete redesign of its first year common program. This project 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 goal is to offer a first year program that excites, engages, inspires, and holistically prepares students for learning in subsequent years. At CEEA 2018, Phase I of this project was reviewed with a focus on the content of the new first year. This year, the focus is on the structure of the proposed program and how it aims to satisfy programmatic design objectives. The proposed first year program is highly modular, allowing for more intentional uses of time during the academic year. Course duration and intensity vary and are selected to best serve student learning, rather than conform to the traditional academic schedule. To provide more timely and targeted feedback, summative assessments occur throughout each term allowing course scheduling to extend into the traditional end-of-term final exam period. This paper presents the current structural design of the new first year and the rationale for its significant features. Some of the program design objectives that have been facilitated by this structure include: • strategic sequencing of learning with opportunities to integrate and reinforce essential skills, • multiple, individualized opportunities for students to stumble and recover, • holistic balancing of content and pacing for better student wellbeing, and • comprehensive, well-timed exposure to wide-ranging programmatic choices for students. Throughout this project, the program structure has evolved continuously. This paper will describe the development process, the challenges faced in that process, and the lessons learned. The paper will conclude by describing the current status of the project, and the focus of work currently being undertaken to prepare for implementation.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".