Navick, N., & Kenny Feister, M. (2019, June), Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams  Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32286

\bibitem{asee_peer_32286}
  Navick, N., \& Kenny Feister, M. (2019, June), \emph{Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams}
  Paper presented at 2019 ASEE Annual Conference \& Exposition , Tampa, Florida.
  10.18260/1-2--32286

Nitzan Navick and Megan Kenny Feister.  "Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams".  2019 ASEE Annual Conference & Exposition , Tampa, Florida, 2019, June.  ASEE Conferences, 2019.  https://strategy.asee.org/32286 Internet.  08 Jun, 2024

\bibitem{asee_peer_32286}
  Nitzan Navick and Megan Kenny Feister.
  "Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams".
  \emph{2019 ASEE Annual Conference \& Exposition , Tampa, Florida, 2019, June}.
  ASEE Conferences, 2019.
  https://strategy.asee.org/32286 Internet.  08 Jun, 2024

@INPROCEEDINGS{asee_peer_32286
author = "Nitzan Navick and Megan Kenny Feister"
title = "Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams"
booktitle = "2019 ASEE Annual Conference \& Exposition "
year = "2019"
month = "June"
address = "Tampa, Florida"
publisher = "ASEE Conferences"
note = {https://strategy.asee.org/32286}
number = {10.18260/1-2--32286}
}

TY  - CPAPER
AB  - This study explores the relationship between friendships of engineering students on project teams within a classroom setting and how their perceptions of each other create in-group biases throughout the class. Using Social Network Analysis (SNA), an analysis that enables researchers to examine relationships among members of a given group, we were able to identify distinct in-groups, otherwise described as groups of students with similar social identities. Survey data about participants were collected twice over the course of a semester that identified their designated project team and demographics. We paid particular attention to participants’ perceptions of, and reliance on, a teammate’s competencies as our visual representation of the data indicated that in-groups were rather distinct in these conditions. Attributes including age, sex, ethnicity, racial identification, year, and designated project team were drawn from the demographic portion of the SNA surveys and assigned to each participant to determine if relationships and communication may be impacted by these characteristics. The ability to pinpoint where in-groups begin and end, and the factors that may aid in their formation, is crucial when aspiring to better understand team dynamics. By identifying reciprocal ties and the way they affect perceptions and willingness to rely on others, a more cohesive network can be established throughout the whole class by therefore minimizing any potential knowledge sharing disparities and improving work efficiency. Thus, the findings from this study can be utilized to encourage increased knowledge sharing.
AU  - Nitzan Navick
AU  - Megan Kenny Feister
CY  - Tampa, Florida
DA  - 2019/06/15
PB  - ASEE Conferences
TI  - Board 18: Social Network Analysis of In-Group Biases with Engineering Project Teams
UR  - https://strategy.asee.org/32286
DO  - 10.18260/1-2--32286
ER  -