M2LADS Demo: A System for Generating Multimodal Learning Analytics Dashboards

TL;DR

M2LADS is a web-based system that integrates, visualizes, and analyzes multimodal biosensor data from learning sessions to provide comprehensive insights and facilitate data relabeling.

Contribution

The paper introduces M2LADS, a novel system for synchronized visualization and analysis of multimodal learning analytics data in a web-based dashboard.

Findings

Supports diverse biosignals including EEG, heart rate, and eye-tracking.

Enables synchronized visualization of multimodal data and videos.

Aids data scientists in comprehensive analysis and data relabeling.

Abstract

We present a demonstration of a web-based system called M2LADS ("System for Generating Multimodal Learning Analytics Dashboards"), designed to integrate, synchronize, visualize, and analyze multimodal data recorded during computer-based learning sessions with biosensors. This system presents a range of biometric and behavioral data on web-based dashboards, providing detailed insights into various physiological and activity-based metrics. The multimodal data visualized include electroencephalogram (EEG) data for assessing attention and brain activity, heart rate metrics, eye-tracking data to measure visual attention, webcam video recordings, and activity logs of the monitored tasks. M2LADS aims to assist data scientists in two key ways: (1) by providing a comprehensive view of participants' experiences, displaying all data categorized by the activities in which participants are engaged, and (2) by synchronizing all biosignals and videos, facilitating easier data relabeling if any activity information contains errors.