E-book user modelling through learning analytics: the case of learner engagement and reading styles

Boticki I., Akcapinar G., Ogata H.

INTERACTIVE LEARNING ENVIRONMENTS, vol.27, pp.754-765, 2019 (SSCI) identifier identifier


In this paper log data on e-book usage is used as part of a learning analytics approach to generate user models which describe university students' characteristics in multiple dimensions. E-book usage is logged and analysed to extract information on how users use e-books for academic purposes. Two cases contributing to user modelling are presented: generating user engagement and user reading style variables describing students' e-book usage. The paper discusses the approach to the variables extraction from data logs, discusses the relationship between the variables and proposes a user modelling approach specifically targeted at building high-level services related to educational e-books. The study examines how can user model variables from different dimensions be used in getting a higher-level overview of user performance and skills; and proposes services which leverage the variables of learner engagement and reading styles.