LID Design Education for Undergraduate and Graduate Engineering Students
Bibliographic record
Abstract
At the University of Guelph, in Ontario, LID has been a substantial component of both the senior undergraduate Urban Water Systems Design and graduate Urban Stormwater Management courses since 2002. Key challenges in delivering these courses include the large amount of course content for the undergraduates, the diverse backgrounds of graduate students, and increasing class sizes. To address these challenges and further highlight the important role of LID in achieving better environmental outcomes in urban areas, the course content, its delivery and student assessment methods were updated in 2009. A new design project, involving an LID retrofit for the University of Guelph Campus, is a central component of both courses. Each undergraduate team of 4 students designs an LID retrofit for one block consisting mainly of buildings and parking areas, and each graduate student team designs a green street for the campus. Designs are completed and shared with other groups by week 9 of the 12 week semester, with the final weeks devoted to modeling and evaluating the collective system. Both courses were offered during Fall 2009 and the changes are being evaluated based on observations, student feedback and the results of student assessment relative to learning objectives. Reorganization of the course content in the undergraduate class was effective; although a greater effort is needed to make time for guest lectures by design professionals, municipal staff and faculty from Landscape Architecture, who can offer diverse perspectives on LID. Some students, both undergraduate and graduate, require a more structured introduction to the modeling software. The design project proved to be an exceptional learning experience for most students. Challenges with group dynamics negatively affected the experience for a few groups, particularly in the graduate class. The diverse background of graduate students continues to present challenges. Student assessment methods offer many benefits for the students, but will likely become unmanageable if class sizes continue to increase.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.074 | 0.021 |
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".