Towards Automatic Flow Experience Identification in Educational Systems

Abstract

Flow experience is an enjoyable feeling highly linked to the learning experience. Identifying whether a student is in flow while using educational systems is critical to measure the quality of systems and the students' learning. Usually, this process is done through intrusive techniques or with a high cost and can not be applied with a large number of students at the same time. In this study, we propose a computational approach to provide automatic student's flow experience identification in educational systems using only the student's data logs from their interactions in the systems. We conducted a systematic literature review to identify the different possibilities currently used to identify student's flow experience in educational systems, as well as a theoretical study associating student's interaction data logs in educational systems with the flow experience dimensions. Our preliminary results indicate that it is possible to obtain the flow experience in an automatic and implicit way.