Speaking of Users: Assessing the Frequency, Consistency, and Depth of User-Related Internal Communication of Strong and Weak Novice Engineering Design Teams
Bibliographic record
Abstract
Abstract In order for students on novice engineering design teams (NEDTs) to develop relevant, impactful products, it is important that they continuously engage potential users throughout their design processes. In successful user engagements, teams may identify individuals who can describe their experiences so students can elicit user needs and design requirements. Users may also provide feedback on design concepts and prototypes so students can iterate and improve their work. Finally, these individuals may connect students to other potential users so that the team can gain further perspectives. These interactions can significantly strengthen NEDTs’ design processes and outcomes. Unfortunately, instructors of NEDTs may not be present when students engage with off-campus users. This distance makes it difficult for instructors to assess how well teams are advancing in this critical aspect of design. However, instructors may have access to teams’ internal communication, which could help them track user engagement. To understand how student design teams communicate about users, we analyzed a database of 251,744 Slack messages sent by 16 Strong and 16 Weak NEDTs in a senior-level product design course. Searching for the instances in which team members used the word “user,” we found that Strong teams discussed users more consistently than Weak teams throughout the semester. All teams’ user-related conversations also peaked during periods of design convergence compared to divergence. Finally, to assess the depth of user discussion, a topic modeling analysis of the dataset revealed that Strong teams discussed users alongside more process-focused topics, while Weak teams discussed users alongside more task-focused topics. By elucidating these patterns, we provide valuable insights to instructors who are assessing and coaching NEDTs on user engagements. Student designers themselves can also use these findings to aid in monitoring and structuring their own internal team communication to ensure they are focusing on users consistently and deeply.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.078 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".