2026 ASEE Annual Conference & Exposition

Engineering educators often look for an association between some kind of treatment (e.g., microaggressions) and some outcome (e.g., belonging, satisfaction). However, some psychological researchers have questioned the validity of this method because negative emotionality can create spurious correlations between self-reported treatment and outcomes. Negative emotionality is the trait-like tendency to consider oneself maltreated and exploited. A person high in negative emotionality should report a high level of victimization (e.g., via microaggressions) and low level of satisfaction regardless of actual circumstances. Negative emotionality thereby acts as a third-variable confound. Our primary goal was to examine whether negative emotionally has this confounding effect. We measured perceived justice (treatment) and inclusion (outcome) in 38 student teams in a project-based engineering course (N = 227). Measures were administered across five time points to minimize measurement error and enable the modeling of lagged effects. A random-intercept cross-lagged panel model (RI-CLPM) was used for modeling. The results indicated that justice and inclusion had reciprocal effects on each other. Negative emotionality pulled down self-reported ratings of justice (p - .006) and inclusion (p = .085). However, the addition of negative emotionality did not change the overall results. Thus, researchers may therefore benefit from measuring this factor but its usage in a statistical model does not seem essential. Results pertaining to other personality traits will also be discussed as part of this presentation. The second goal of this presentation is to introduce engineering education researchers to the RI-CLPM model for handling multiple waves of longitudinal data from students in teams.