M2LADS: A System for Generating MultiModal Learning Analytics Dashboards in Open Education
This system addresses the need for comprehensive learning analytics in open education to potentially improve learning outcomes and content, though it appears incremental as it builds on existing platforms like edBB.
The authors tackled the problem of integrating and visualizing multimodal data in MOOCs by developing M2LADS, a web-based system that combines biometric, behavioral, and performance data into dashboards to capture learners' holistic experiences.
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.