In recent years, e-learning systems have been introduced and used at many educational institutions. However, because of difficulty in maintaining student motivation in classes that use these systems, e-learning systems for self-study may foster user dropout; more precisely, because users are isolated during self-study, they may be highly motivated to engage in e-learning initially, but this motivation may gradually decline over time. In this study, we introduce “Moti-Meter,” a system intended to support the maintenance of user motivation and avoid psychological reactance by enabling users to visualize their own motivation. Estimation of users’ motivation is done using regression analysis of data collected from non-invasive sensor devices, such as smartphones and wearable devices. Visualizing one’s motivation has potential for applications in a range of other fields as well, for instance in healthcare.
Shimazaki, Y., & Kato, T. (2018). Moti-meter: A system for visualizing personal learning motivation. In Advances in Intelligent Systems and Computing (Vol. 608, pp. 117–124). Springer Verlag. https://doi.org/10.1007/978-3-319-60639-2_12