M2LADS: A System for Generating MultiModal Learning Analytics Dashboards
  in Open Education
Álvaro Becerra Roberto Daza Ruth Cobos Aythami Morales Mutlu Cukurova Julian Fierrez
In this article, we present a Web-based System called M2LADS, which supports
the integration and visualization of multimodal data recorded in learning
sessions in a MOOC in the form of Web-based Dashboards. Based on the edBB
platform, the multimodal data gathered contains biometric and behavioral
signals including electroencephalogram data to measure learners' cognitive
attention, heart rate for affective measures, visual attention from the video
recordings. Additionally, learners' static background data and their learning
performance measures are tracked using LOGCE and MOOC tracking logs
respectively, and both are included in the Web-based System. M2LADS provides
opportunities to capture learners' holistic experience during their
interactions with the MOOC, which can in turn be used to improve their learning
outcomes through feedback visualizations and interventions, as well as to
enhance learning analytics models and improve the open content of the MOOC.