Analysing Ongoing Learning Experience with Educational Data Mining for Interactive Learning Environments

Interactive learning environments have widely been accepted in enhancing students' learning performance. Students can have interaction with different learning modules, materials, and activities. However, the ongoing learning data is not well utilized for further analysis. Educational data mining has played an increasing role in considering such essential data in order to improve students' ongoing learning and teachers' ongoing instructions. Therefore, this study proposes several model frameworks in analyzing the students' ongoing learning experience by integrating with data mining techniques for interactive learning systems, which can be applied on different learning platforms. Three models have been proposed for updating learning activities to match with ongoing learning performance, for identifying students' learning problems for teachers to adjust the instructions, and for presenting the students' preferred learning materials format. The results of this study can be further implemented by learning system developers to help improve their interactive learning platforms for more significant benefits for students and teachers.