Towards Automatic Flow Experience Identification in Educational Systems: A Qualitative Study

Abstract

One of the main challenges in the field of learning technologies is the automatic students' flow experience identification in educational systems. This challenge occurs because the flow experience identification is usually conducted by using invasive techniques (e.g., eye trackers or electroencephalograms) or approaches that are not able to handle a large number of students at the same time (e.g., questionnaires/scales or interviews). Despite recent studies proposed to analyze students' flow experience based on user data logs, most of these studies are theoretical without data-based analysis. To move towards the automatic flow experience identification in educational systems, we conducted a qualitative study to analyze possible relations between the students' interaction data logs, behavior, and flow experience in an educational system. The results show that some data logs are related to the students' flow experience. Our results provide insights into the relations amongst the data logs, the flow experience, and students' behavior, which could be beneficial to the development of an approach for automatic identification of the flow experience in educational systems.