Developing a Dashboard to Support the Analysis of Multimodal Educational Data

Abstract

Learning analytics consists of gathering and analyzing data from students in order to understand complex aspects of the learning process and promote its improvement. Currently, there is a lack of tools that allow the visualization of multimodal data. In this paper, we present a visualizer that allows analyzing the data provided by a multimodal learning analytics software. The multimodal data visualizer, in addition to allowing to visualize 10 body postures, permits applying clustering techniques, such as k-means. As validation, we analyze the data provided of 43 engineering student presentations.