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Human bodies vary widely: height, weight, blood volume, handedness, strength, and variations from disabilities, trauma, genetics, etc. Engineers must be trained to include human variance when designing human-interactive systems. Typically, this is not incorporated into mathematical and modeling focused courses. In the spring of 2019, one of three sections of an introduction to biomechanics course was modified to adopt interactive group problem solving and add human body parameter variation to the problems that students solved. Problems were solved for multiple body sizes. Initial evidence suggests this was successful in increasing students’ consideration of human variation and user needs in mathematical modeling and in increasing their mention of specific body parameters and parameter variation. This can be implemented by a wide variety of instructors without special training in pedagogy or in universal design, especially when a course already features interactive small group problem solving, even during a large lecture by having students’ pair to solve equations briefly. Future steps might consider other parameters of diversity, inclusion, or equity topics. We were pleased to see that small changes in pedagogical approach can pay significant dividends encouraging students to situate analytic work in realistic engineering contexts.

 

Abstract. The Circumplex Team Scan (CTS) assesses the degree to which a team’s interaction/communication norms reflect each segment (16th) of the interpersonal circle/circumplex. We developed and evaluated an abbreviated 16-item CTS-16 that uses one CTS item to measure each segment. Undergraduates ( n = 446) completing engineering course projects in 139 teams completed the CTS-16. CTS-16 items showed a good fit to confirmatory structural models (e.g., that expect greater positive covariation between items theoretically closer to the circumplex). Individuals’ ratings sufficiently reflected team-level norms to justify averaging team members’ ratings. However, individual items’ marginal reliabilities suggest using the CTS-16 to assess general circumplex-wide patterns rather than specific segments. CTS-16 ratings correlated with respondents’ and their teammates’ ratings of team climate (inclusion, justice, psychological safety). Teams with more extraverted (introverted) members were perceived as having more confident/engaged (timid/hesitant) cultures. Members predisposed to social alienation perceived their team’s culture as relatively disrespectful/unengaged, but their teammates did not corroborate those perceptions. The results overall support the validity and utility of the CTS-16 and of an interpersonal circumplex model of team culture more generally. 

When professors assign group work, they assume that peer ratings are a valid source of information, but few studies have evaluated rater consensus in such ratings. We analyzed peer ratings from project teams in a second-year university course to examine consensus. Our first goal was to examine whether members of a team generally agreed on the competence of each team member. Our second goal was to test if a target’s personality traits predicted how well they were rated. Our third goal was to evaluate whether the self-rating of each student correlated with their peer rating. Data were analyzed from 130 students distributed across 21 teams (mean team size = 6.2). The sample was diverse in gender and ethnicity. Social relations model analyses showed that on average 32% of variance in peer-ratings was due to “consensus,” meaning some targets consistently received higher skill ratings than other targets did. Another 20% of the variance was due to “assimilation,” meaning some raters consistently gave higher ratings than other raters did. Thus, peer ratings reflected consensus (target effects), but also assimilation (rater effects) and noise. Among the six HEXACO traits that we examined, only conscientiousness predicted higher peer ratings, suggesting it may be beneficial to assign one highly conscientious person to every team. Lastly, there was an average correlation of.35 between target effects and self-ratings, indicating moderate self-other agreement, which suggests that students were only weakly biased in their self-ratings. 

Justice should increase inclusion because just treatment conveys acceptance and enables social exchanges that build cohesion. Inclusion should increase justice because people can use inclusion as a convenient fairness cue. Prior research touches on these causal associations but relies on a thin conception of inclusion and neglects within-person effects. We analyze whether justice causes inclusion at the within-person level. Five waves of data were gathered from 235 college students in 38 entrepreneurial teams. Teams were similar in size, work experience, deadlines, and goals. General cross-lagged panel models indicated that justice and inclusion had a reciprocal influence on each other. A robustness check with random-intercept cross-lagged models supported the results. In the long run, reversion to the mean occurred after an effect decayed, suggesting that virtuous or vicious cycles are unlikely. The results imply that maintaining overall justice at the peer-to-peer level may lead to inclusion.