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Enhancing Peer Influence in STEM Learning and Engagement through Social Media Interactions Using Network Science Principles

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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

8

DOI

10.18260/1-2--34572

Permanent URL

https://peer.asee.org/34572

Download Count

61

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Paper Authors

biography

Arif Mohaimin Sadri Florida International University Orcid 16x16 orcid.org/0000-0001-5571-6741

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Dr. Arif Mohaimin Sadri is an Assistant Professor in the Moss Department of Construction Management of the Moss School of Construction, Infrastructure and Sustainability (MSCIS) at the Florida International University (FIU). Previously he was a Visiting Assistant Professor in the Department of Civil and Environmental Engineering at the Rose-Hulman Institute of Technology and an Adjunct Professor in the Civil Engineering Dept. at the Valparaiso University. Dr. Sadri received his doctoral training from the Lyles School of Civil Engineering at Purdue University with a solid background in Civil Engineering (Transportation), Network Science, and Social Science. Dr. Sadri specializes in resilience engineering, evacuation modeling, shared mobility, social influence modeling, machine learning, agent-based modeling, and network modeling. Dr. Sadri's research focuses on the critical interdependence between social and infrastructure networks and integrates human proactive decision-making components into the civil infrastructure management challenges. Dr. Sadri develops human-centered and network-driven techniques that complement to the science of infrastructure resilience and sustainability.

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Abstract

This Work in Progress (WIP) research presents a framework to explain the usefulness of social media datasets of student interactions that can be retrieved through Twitter, a publicly available social media platform. Traditional datasets have limited capacity to adequately capture student communication strategies and analyze student interactions with such details and coverage. As such, social media datasets, enriched with student activity information over time, will be useful to capture student perception on various STEM topics covered in class and identify ways to facilitate active learning. The major focus of this research is towards understanding how STEM students are socially influenced online, while communicating course topics and interacting in their respective cohorts. The proposed framework of this research will help future studies to craft targeted information dissemination strategies for various student groups based on their online social network characteristics, activities, and interactions on how students’ react to what others post in social media on a related topic. By applying network science principles, this research demonstrates how to (i) define properties and growth of student interaction networks; and (ii) classify student activities, perception and learning behaviors from individual and group dynamics. The proposed framework not only expands our knowledge of student online interaction dynamics, but will also result in better understanding of how students’ express diverse concerns on a given STEM topic and how to harness and embed such information for enhancing engagement and peer influence. The peers not only include instructor and the students taking the course, but also subject matter experts, alumni, faculty, senior students among others.

Sadri, A. M. (2020, June), Enhancing Peer Influence in STEM Learning and Engagement through Social Media Interactions Using Network Science Principles Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--34572

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