DEPLOYING ENGINEERING CASES TO FACILITATE PROBLEM-BASED THINKING IN ENGINEERING COMMUNICATIONS
Bibliographic record
Abstract

 First-year engineering students often struggle to communicate the value of their work because they do not understand how problem-based reasoning drives engineering research and industry. Recognizing the effectiveness of discipline-specific teaching of the conventions of engineering communications, researchers have recently suggested the value of teaching the Swales "CARS" model to help students contextualize and justify their work. In two sections of Communications for the Engineering Profession at the University of Waterloo, we incorporated teaching of the Swales model of problem-based reasoning to help students understand the conventions of engineering communications, but found that authentic engineering documents are often too complex for this purpose. To address this limitation, we deployed engineering cases in two electrical/computer engineering courses to exemplify this model, and used pre-teaching and post-teaching surveys to measure students' perceptions of improvement in their ability to understand problem-based reasoning and apply it to project conceptualization. The results show that using simplified engineering cases of this kind both improves students' ability to use this model and improves their confidence in doing so. This outcome has implications for increasingly popular engineering-communications courses because it demonstrates the value of using realistic but simplified engineering scenarios to teach the Swales model in authentic and effective engineering communication.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".