The outbreak of COVID-19 has significantly impacted on education, training, and mobility opportunities provided to learners, teachers, and educators. In response to this situation, synchronous online learning has been massively adopted in universities and, therefore, the analysis of student behavior in this context is becoming essential. However, the literature has mainly tackled student behavior modelling in asynchronous online learning (e.g., interactions with pre-recorded videos), making how students learn in synchronous online learning so far under-explored. Grounding on the experience on online learning at the University of Cagliari, this paper proposes a preliminary study on student participation in synchronous lessons, covering more than 80 courses, and identifies patterns and strategies of engagement in classes over the semester. Then, by means of clustering techniques applied to data from more than 25,000 students, we model fine-grained behavioral strategies and discuss how they are related with the student's experience across courses and whether planning elements (e.g., the hour of the day a lesson is delivered) influence their level of participation. We expect that this study will support the educational stakeholders with preliminary data-driven informed decisions and pose the basis for data-driven personalization for students and teachers involved in online synchronous learning. © 2021 CEUR-WS. All rights reserved.
Modelling student behavior in synchronous online learning during the covid-19 pandemic