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Analysis of Students’ Personalized Learning and Engagement within a Cyberlearning System

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

October 19, 2019

Conference Session

Experimentation and Laboratory-Oriented Studies Division Technical Session 2

Tagged Division

Experimentation and Laboratory-Oriented Studies

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Paper Authors


Debarati Basu Virginia Tech

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Dr. Debarati Basu is an Assistant Teaching Professor in the College of Computing and Informatics at the University of North Carolina at Charlotte. She earned her Ph.D. in Engineering Education from Virginia Tech (VT) in 2018. She received her bachelors and masters in Computer Science and Engineering. Her research areas are in the Cyberlearning or online learning, computer science education, and experiential learning including undergraduate research. She is also interested in curriculum development, assessment, and program evaluation. She teaches in active teaching environments, such as project-based learning and flipped classrooms. She aims to bring in engineering education research into practice.

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Vinod K. Lohani Virginia Tech

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Dr. Vinod K. Lohani is a Professor of Engineering Education and also serves as the Director of education and global initiatives at an interdisciplinary research institute called the Institute for Critical Technology and Applied Science (ICTAS) at Virginia Tech. He is the founding director of an interdisciplinary lab called Learning Enhanced Watershed Assessment System (LEWAS) at VT. He received a Ph.D. in civil engineering from VT. His research interests are in the areas of computer-supported research and learning systems, hydrology, engineering education, and international collaboration. He has served as a PI or co-PI on 16 projects, funded by the National Science Foundation, with a $6.4 million research funding participation from external sources. He has been directing/co-directing an NSF/Research Experiences for Undergraduates (REU) Site on interdisciplinary water sciences and engineering at VT since 2007. This site has 95 alumni to date. He also leads an NSF/Research Experiences for Teachers (RET) site on interdisciplinary water research and have 10 alumni. He also leads an NSF-funded cybersecurity education project and serves as a co-PI on two International Research Experiences for Students (IRES) projects funded by the NSF. He has published over 90 papers in peer-reviewed journals and conferences.

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Kang Xia Virginia Tech

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Kang Xia received her Ph.D. from the University of Wisconsin-Madison (1997), M.S. from Louisiana State University (1993), and B.S. from Beijing Agricultural University (1989). She was a Postdoctoral Researcher at the University of Wisconsin-Madison (1997-1998), an Assistant Professor at Kansas State University (1998-2001), University of Georgia (2002-2005), and Assistant Professor, Dept. of Chemistry, Mississippi State University (2006-2010), an Associate Professor at Mississippi State University (2010-2011) and at Virginia Tech (2011-2016). She also served as Director for Re-search Division and Industrial and Agricultural Services Division, Mississippi State Chemical Laboratory (2006-2011). She is currently a Professor at Virginia Tech (2016-present). She has served as adhoc reviewer for a number of scientific journals and funding agencies. She served as associate editor for the Journal of Environmental Quality (2007-2017). She is an expert on method development for analysis of organic chemicals in environmental matrixes and environmental occurrence, fate, and impact of organic chemicals. She has successfully managed and accomplished close to $9 mil-lion federal and state funded interdisciplinary environmental projects. She has published 51 peer-reviewed papers, 5 book chapters, and given 113 professional presentations. She holds membership of the American Chemical Society, the Soil Science Society of America, and SigmaXi.

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“Advance Personalized Learning” is one of the 14 grand challenges of engineering as identified by the National Academy of Engineering. One possible approach for this advancement is to deploy systems that allow an investigator to understand the differences in the learning process of individuals. In this context, cyberlearning systems, like remote and virtual labs, that use networked computing and communication technology to reach a large number of learners offer the affordance to uniquely identify learners and track their learning process in real-time. Motivated by this idea, this study aims to investigate personalized learning and engagement within a cyberlearning system, called the Online Watershed Learning System (OWLS) that combines features of both remote and virtual labs. This cyberlearning system utilizes learning resources generated by a real-time high-frequency environmental monitoring system, called the Learning Enhanced Watershed Assessment System (LEWAS).

To understand individualized learning and engagement, the OWLS is advanced with a user-tracking system. Previously, the OWLS used a Google-Analytics based user-tracking system. This new user-tracking system can identify individual users and their actions across devices. A pilot study was carried out by designing an OWLS-based learning task and implementing it within a senior level Environmental Science classroom for exploring personalized learning and engagement within the OWLS. Informed by the engagement theory and the literatures on learning analytics, the study follows a pre-experimental research design where students completed the OWLS-based learning task followed by a post-survey within the in-class time. Results indicate that students’ learning scores are significantly related to the time students were spending outside the OWLS for completing the OWLS-based task. Various engagement patterns/ strategies taken by individual students to complete the task were also revealed. The study shows that a custom user-tracking system, like the one developed in this study has the potential to overcome several limitations of the google-analytics based user-tracking system by providing fine-grained individualized student data that can help in understanding students’ engagement behaviors within a cyberlearning system. Finally, the study has implications of how a cyberlearning tool, like the OWLS, can be utilized in a hybrid classroom setting for helping students gain environmental monitoring knowledge, and skills in real-time data analysis, leveraging the idea of technology-enhanced laboratory instructions within a classroom environment.

Basu, D., & Lohani, V. K., & Xia, K. (2019, June), Analysis of Students’ Personalized Learning and Engagement within a Cyberlearning System Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32088

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