Vitaliy Popov

#217 Victor Vaughan

1111 E. Catherine Str.

Ann Arbor, MI 48109, USA

I am an Assistant Professor in the Department of Learning Health Sciences with a courtesy appointment at the U-M School of Information. I am also the Director of Learning Sciences and Technology for the Clinical Simulation Center for University of Michigan Medical School.

My research focuses on understanding how team function can be optimized to lead to better learning gains, performance and healthcare outcomes. My background allows me to utilize evidence in education science, simulation-based training and learning analytics to understand how healthcare professionals can better work in teams and how we can support these processes to foster health care delivery. I completed my Ph.D. on computer-supported collaborative learning at Wageningen University & Research Center, in the Netherlands.

Current research projects are situated at the intersection of Learning Sciences, Health Sciences, Artificial Intelligence, and eXtended Reality. I am currently serving as a PI or Co-PI on several projects funded by the National Science Foundation ranging from applying multimodal learning analytics in teamwork in VR to understanding the mechanisms of joint visual attention in the operating room. I am on the Editorial Boards for the Annals of Medicine Journal - Medical Education section and the International Journal of Computer-Supported Collaborative Learning.

Research areas:

Learning sciences, learning analytics, science of team science, computer supported collaborative learning (CSCL), computer supported cooperative work (CSCW), Human-Computer Interaction, team-based clinical simulation training, eXtended Reality.

news

Jun 12, 2024	Improving shared decision-making among interprofessional teams
May 14, 2024	Collaboration with UM School of Information SI 582 Intro to Interaction Design course. How an experimental intro class shaped UMSI students’ paths
May 13, 2024	Leveraging AI to improve video-based surgical learning
Dec 14, 2023	Serving as the Guest Advisor Editor for Annals of Medicine - Medical Education Section for an Article Collection on The Role of the Metaverse in Medical Education

selected publications

CHI

Looking Together ≠ Seeing the Same Thing: Understanding Surgeons’ Visual Needs During Intra-operative Coordination and Instruction

Popov, Vitaliy, Chen, Xinyue, Wang, Jingying, Kemp, Michael, Sandhu, Gurjit, Kantor, Taylor, Mateju, Natalie, and Wang, Xu

CHI ’24: Proceedings of the CHI Conference on Human Factors in Computing Systems 2024

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BMJ Open

Applying Ordered Network Analysis to video-recorded physician-nurse interactions to examine communication patterns associated with shared understanding in inpatient oncology care settings

Popov, Vitaliy, Tan, Yuanru, and Manojlovich, Milisa

BMJ Open 2024

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JCHE

Using learning analytics to explore the multifaceted engagement in collaborative learning

Xing, Wanli, Zhu, Gaoxia, Arslan, Okan, Shim, Jaesub, and Popov, Vitaliy

Journal of Computing in Higher Education 2022

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Engagement is critical in learning, including computer-supported collaborative learning (CSCL). Previous studies have mainly measured engagement using students’ self-reports which usually do not capture the learning process or the interactions between group members. Therefore, researchers advocated developing new and innovative engagement measurements to address these issues through employing learning analytics and educational data mining. This study responded to this call by developing learning analytics to study the multifaceted aspects of engagement (i.e., group behavioral, social, cognitive, and metacognitive engagement) and its impact on collaborative learning. The results show that group behavioral engagement and group cognitive engagement have a significantly positive effect on group problem-solving performance; group social engagement has a significantly negative effect; the impact of group metacognitive engagement is not significant. Furthermore, group problem-solving performance has a significant positive effect on individual cognitive understanding, which partially mediates the impact of group behavioral engagement and fully mediates the impact of group social engagement on individual cognitive understanding. The findings have important implications for developing domain-specific learning analytics to measure students’ sub-constructs of engagement in CSCL.