Abstract
Abstract The pandemic of COVID-19 forced the transition of education to online platforms. This shift allowed for a more in-depth study of the learning process of students, as it provided access to information about their activities and interactions with the course’s contents [1-3]. In this work, we apply quantitative methods to analyze the student learning progress of students for two first year courses of the B.Sc. degree in Physics (Universidad Católica del Norte). The data are collected from activity logs of digital platforms during Academic year 2021, which were employed to characterize the student learning habits along these processes (experience, selectivity and workflow). Statistical analysis is based on the distribution of the time spent on learning activities, such as the daily time distribution and the cumulative attention per online materials. The results show that the learning process of students in online courses is complex and adaptive. We report statistical patterns similar to those found in financial markets. These empirical results provide evidence about the importance of economic principles and methods in the understanding of the teaching-learning process.
Published Version
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