Elliott, J., & Minichiello, A., & Ellsworth, J. (2020, June), Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis  Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34612

\bibitem{asee_peer_34612}
  Elliott, J., \& Minichiello, A., \& Ellsworth, J. (2020, June), \emph{Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis}
  Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line .
  10.18260/1-2--34612

Jack Elliott, Angela Minichiello P.E., and Joel Ellsworth.  "Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis".  2020 ASEE Virtual Annual Conference Content Access, Virtual On line , 2020, June.  ASEE Conferences, 2020.  https://peer.asee.org/34612 Internet.  21 Dec, 2024

\bibitem{asee_peer_34612}
  Jack Elliott, Angela Minichiello P.E., and Joel Ellsworth.
  "Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis".
  \emph{2020 ASEE Virtual Annual Conference Content Access, Virtual On line , 2020, June}.
  ASEE Conferences, 2020.
  https://peer.asee.org/34612 Internet.  21 Dec, 2024

@INPROCEEDINGS{asee_peer_34612
author = "Jack Elliott, Angela Minichiello P.E., and Joel Ellsworth"
title = "Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis"
booktitle = "2020 ASEE Virtual Annual Conference Content Access"
year = "2020"
month = "June"
address = "Virtual On line "
publisher = "ASEE Conferences"
note = {https://peer.asee.org/34612}
number = {10.18260/1-2--34612}
}

TY  - CPAPER
AB  - This paper describes findings from a mixed methods research study that aimed to identify relationships between students’ peer and course resource interactions with student performance in a large (100+) face-to-face (f2f) engineering course. Prior research has shown peer interaction may positively influence student performance in online engineering courses, as well as in f2f courses in other disciplines.  However, more limited research relates the motivations for and effects of student interactions with peers and resources to performance in large, f2f engineering courses. 

This mixed methods study uses Social Network Analysis (SNA) and Qualitative Content Analysis (QCA) to provide new insights about potential relationships that exist between levels of student interaction and performance in a f2f, 2nd year materials science course. The course was offered at a mid-size land grant university in the western United States during the spring 2019. Quantitative and qualitative data were generated over a single semester by administering nine self-report surveys online to student participants in the course. SNA and QCA were used to examine closed (SNA) and open (QCA)-ended survey responses to questions that asked students about their connectedness with peers and resources during the semester.

Mixed data analyses sought to identify correlations existing between individual and network-wide SNA measures and student performance. Findings describe: (1) relationships between student resource interactions and student performance in the course, including the development of effective networks over time, and (2) how and why students’ resource usage and peer interaction patterns changed during the course, including key patterns in students’ motivation for changing resource use. Findings have implications for engineering educators of large undergraduate courses. 

AU  - Jack Elliott
AU  - Angela Minichiello P.E.
AU  - Joel Ellsworth
CY  - Virtual On line 
DA  - 2020/06/22
PB  - ASEE Conferences
TI  - Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis
UR  - https://peer.asee.org/34612
DO  - 10.18260/1-2--34612
ER  -