Improving the use of virtual worlds in education through learning analytics: a state of art

Abstract

The use of Virtual Worlds in Education is becoming an innovative alternative to traditional education. However, these solutions are confronted to several issues such as: lack of indicators to follow up the students’ progress, lack of well-defined evaluation parameters, difficulties for evaluating collective and individual contributions, difficulties for keeping students engaged and motivated, a very time-consuming teachers’ supervision, and the absence of tutors for guiding the learning process, among others. In this review, we explore and describe academic contributions focused on the application of Learning Analytics to improve Virtual Worlds in Education from three perspectives: Personalized Learning, Adaptive Learning and Educational Intervention. Our results highlight that most of the research focus on support decisions whose nature concerns operational non-real-time issues. Additionally, almost all the contributions focus in solving only a few issues, but none of them offer a holistic framework that could be used by teachers or pedagogical personnel for decision making. Keywords: Virtual environments · Virtual worlds · Learning analytics Data mining · Educational platform