Indicator Visualization for Adaptive Exploratory Learning Environments

This paper presents our approach to identifying areas of improvement in the intelligent components of adaptive Exploratory Learning Environments. Students’ interaction data from an online operational database are first transformed into a data warehouse in order to allow visualisation and exploration using online analytical processing (OLAP) tools. Using a microworld for secondary school algebra as a case study, we also present some more targeted visualisations of the students’ interaction data. We demonstrate the possibilities that these visualisations provide for exploratory data analysis, enabling confirmation or contradiction of expectations that pedagogical experts may have about the system and ultimately providing both empirical evidence and insights for its further development.