Analysis of Designer Emotions in Collaborative and Traditional Computer-Aided Design
Bibliographic record
Abstract
Abstract Technology is transforming the way engineering designers work and interact with others; Synchronous collaborative computer-aided design (CAD) tools allow designers to manipulate the same model at the same time. We present a new method using automated facial emotion detection software and cursor tracking to map designer emotions and corresponding designer activities in synchronous collaborative CAD. We present findings from a dataset of 9 participants that were assigned to two distinct working styles in the same synchronous CAD environment: single participants working by themselves and paired participants working together. In general, our results show that designers working in the paired workflow exhibited more emotion compared to designers who worked alone. A frequency analysis was performed by linking occurrences of each emotional response to their antecedent activities, revealing that user emotions were predictable to some degree by specific antecedent activities of CAD work. We concluded that activities happening in the graphics area were the most frequent antecedent events of emotions for single-users, while for paired participants, activities in the chat section and feature menu were the most frequent antecedent events for joy and fear, respectively. Finally, logistic regression was applied for each combination of event and emotion for each participant in order to further investigate the relationships between the user activities and emotions, and meta-regression was used to aggregate the regression results for the two different working styles. In particular, for single-users, activities in the model tree were found to be positively correlated to joy and negatively correlated to disgust, and navigating the feature menu increased the likelihood of contempt. For participants in pairs, communicating with CAD partner and receiving communications from partner was associated with joy, navigating the feature menu was associated with sadness, anger and disgust were associated with partner’s action in the model tree, and contempt corresponded to the designer’s own activities in the model tree area. The approach and conclusions presented in this paper allow us to better understand designer emotions in fully synchronous CAD, which leads to insight related to designer satisfaction, creativity, performance and other outcomes valued by engineering designers in a virtual collaborative environment.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".