INTEGRATED LEARNING DESIGN OF AN ENGINEERING TECHNOLOGY SUSTAINABILITY AND ETHICS COURSE
Bibliographic record
Abstract
McMaster University’s School of Engineering Technology (SET) offered a unique course structure to students in their final undergraduate term in the 2015-2016 academic year. The intention of the program chair and instructor was to deliver a course that taught sustainability and ethics in a context that would be applicable to 105 Bachelor of Technology (B.Tech.) engineering technology students preparing to commence their careers at the end of the term. The course focused on the delivery of a final project of the students’ choosing that connected to a real-world sustainability issue supported by weekly lectures and testing. The unique delivery style was an experiential learning approach mimicking the dynamics of a real-world project involving client and stakeholder management – concepts that the students were introduced to in prerequisite courses. The project criteria stipulated a “new-worthy” topic which forced the students to be up-to-date and adjust their project work throughout the term based on changes in the media interest, public opinion, or political involvement. Students were challenged to not only look at the problem and address the applicable environmental, social, and economic aspects but to further develop communication strategies within the political context and societal acceptance/understanding of the issue. The evaluation of the course success is reviewed based on student feedback and a formal focus-group session conducted by McMaster Institute for Innovation & Excellence in Teaching & Learning (MIIETL) which highlighted students “felt engaged with the material and described the project as their ‘greatest intellectual challenge’ of the B.Tech. program.” For the purpose of knowledge sharing, this paper will discuss the course design, innovative instructional approach, group project attributes and outcomes from a student the focus-group.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".