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Examining Relationships Between Student Interactions with Peers and Resources and Performance in a Large Engineering Course Using Social Network Analysis

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Conference

2020 ASEE Virtual Annual Conference Content Access

Location

Virtual On line

Publication Date

June 22, 2020

Start Date

June 22, 2020

End Date

June 26, 2021

Conference Session

Understanding Student Behavior and Experiences

Tagged Division

Educational Research and Methods

Page Count

16

DOI

10.18260/1-2--34612

Permanent URL

https://peer.asee.org/34612

Download Count

130

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Paper Authors

biography

Jack Elliott Utah State University

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Jack Elliott is a concurrent M.S. in Engineering (mechanical) and Ph.D. in Engineering Education student at Utah State University. His work focuses on group work in face to face courses, including the application of Social Network Analysis.

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biography

Angela Minichiello P.E. Utah State University Orcid 16x16 orcid.org/0000-0002-4545-9355

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Angela Minichiello is an assistant professor in the Department of Engineering Education at Utah State University (USU) and a registered professional mechanical engineer. Her research examines issues of access, diversity, and inclusivity in engineering education. In particular, she is interested in engineering identity, problem-solving, and the intersections of online learning and alternative pathways for adult, nontraditional, and veteran undergraduates in engineering.

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Joel Ellsworth Utah State University

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Abstract

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.

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

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