INCORPORATING TIMBER EDUCATION INTO EXISTING ACCREDITED ENGINEERING PROGRAMS
Bibliographic record
Abstract
The demand for large and tall timber buildings is increasing across Canada. The recently constructed Brock Commons building in Vancouver and the upcoming Arbour building in Toronto are two such examples. These buildings are challenging for practitioners to design, and presently only a limited number of engineering institutions across Canada offer a course in timber design. There is a growing demand for engineering graduates who can contribute to the creation of these structures; however, the number of graduates who meet this criterion is lagging. Separate courses in timber could be introduced to more universities, however the addition of a new course may overload students, whose course schedules are already tightly regulated by the Canadian Engineering Accreditation Board. Moreover, the creation of a new course can take several years and will therefore not meet the current industry demand quick enough. The research herein presents a method of incorporating timber education within the existing civil engineering curriculum in Canada, without the introduction of an additional course. The purpose of the proposed method is to offer an efficient solution that will provide engineering students with knowledge of the timber industry quickly to meet industry demand. Two timber learning modules were integrated within the existing Structural Steel Design course at an accredited university. The timber learning modules paralleled the topics covered within an undergraduate timber design course. Students were surveyed before and after the learning modules were presented to assess level of interest and motivations, knowledge of the industry, and level of understanding. After the learning modules were presented, 76% of students indicated they had some level of confidence in contributing to the design of a timber building. These results show that the timber learning modules were successful at introducing and generating an interest in timber design, and that students gained basic knowledge they could apply in practice.
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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 | 0.001 | 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 | 0.001 |
| 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 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".