SELF-AWARENESS AND EMPATHY AS TOOLS TO MITIGATE CONFLICT, PROMOTE WELLNESS, AND ENHANCE PERFORMANCE IN A THIRD-YEAR ENGINEERING DESIGN COURSE
Bibliographic record
Abstract
Historically, students in engineering design courses learn how to resolve conflict almost exclusively through experience and with varying degrees of success, which can have ramifications on student wellness and performance [1]. Instructors can intervene by scaffolding conflict resolution, but since they are often made aware only when team conflict becomes unmanageable, proactive strategies are needed. Several strategies were implemented in a new third-year course to enhance students’ self-awareness and empathy for others when working in teams. These included personality and conflict style exercises, the generation of an approachability statement, and the reflective monitoring of team dynamics using ITP metrics’ assessments during the term [2]. Surveys gauged student satisfaction with teamwork, the frequency of team conflict, and preparedness for resolving conflicts. Overall, students felt better prepared to handle future conflict as a result of the course. However, additional accountability measures may enhance the perceived value of the interventions used.
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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 | 0.000 | 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".