Towards Textual Reporting in Learning Analytics Dashboards

Abstract

In this paper we present the Soft Learn Activity Reporter (SLAR) service which automatically generates textual short-term reports about learners' behavior in virtual learning environments. Through this approach, we show how textual reporting is a coherent way of providing information that can complement (and even enhance) visual statistics and help teachers to understand in a comprehensible manner the behavior of their students during the course. This solution extracts relevant information from the students' activity and encodes it into intermediate descriptions using linguistic variables and temporal references, which are subsequently translated into texts in natural language. The examples of application on real data from an undergraduate course supported by the Soft Learn platform show that automatic textual reporting is a valuable complementary tool for explaining teachers and learners the information comprised in a Learning Analytics Dashboard.