Offering smarter learning support through the use of biometrics

Abstract

The Internet of Things (IoT) has evolved into a mainstream keyword describing the use of interconnected device for data transfer. The authors present their current research study that aims at collecting biometric data from learners and using them for providing innovative feedback for a number of learning tasks. The paper discusses how measuring Galvanic Skin Response heartbeat rate and voice patterns can help to provide an alternative type of learner support. The discussion also covers how biometrics data are filtered by applying a number of profiling techniques to classify learners in different groupings. The paper also briefly touches on hardware aspects of the work carried out, as well as analysis of data sets from a student cohort.