Development of Perceptions of Technical and Ethical Expertise In Teams Over Time

Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams

“…To prevent phenomena like the findings of Zhu [8] and Schulz-Hardt, Frey, Luthgens, and Moscovici [7] it is important to identify in-groups in order to merge them promptly. As such, this study utilizes methodologies such as social network analysis and statistical computation of selfreported, rank-order survey data collected by Kenny Feister, Zoltowski, Buzzanell, Torres [10] to classify in-groups. We hypothesized that by constructing a sociogram composed of participants' demographic data and participants' reported perceptions of and willingness to depend on their classmates technical, project-specific, and ethical competencies in-groups will be visually identified through tie reciprocity.…”