A learning analytics methodology to profile students behavior and explore interactions with a digital electronics simulator

Abstract

The automatic collection of data concerning the interaction between students and Technology Enhanced Learning (TEL) systems has become increasingly common. Such data availability has led to applications of Learning Analytics (LA) techniques, characterized by the capability of extracting non-trivial patterns from them. In this framework, we describe the methodology we are adopting to explore the way students learn the concepts of digital electronics by exploiting LA. In particular, a simulator named DEEDS (Digital Electronics Education and Design Suite) is used, and we aim at extracting non-trivial knowledge from data, gathered through a logging application, properly realized for monitoring DEEDS usage. © 2014 Springer International Publishing Switzerland.