EnTIRE will fundamentally advance the state of the art in education research and practice as well as engineering for sensors, analytics, and systems. We are working toward an engineered system for automated, secure, and privacy-aware capture, integration, and analysis of multimodal learner data in real-world learning contexts.
For data collection
Video and audio tools are essential; we are developing an expanded set of tools that will provide researchers with data that goes beyond what meets the eye. These include materials, devices, and platforms for long-lived, low-cost, wearable biosensors to measure and track individual physiological and behavioral information, while advances in mm-wave radar allow environment-based tracking of group interactions and physiological measures.
For data analysis
To fuse multimodal information from these sensors with traditional audiovisual and textual data, we will develop new natural language processing and machine learning methods for qualitative analytics. The deeply personal nature of these data necessitates creation of new large-scale computational systems for storage, organization, and processing that are provably secure and privacy-preserving, and development of ethical guidelines for their use.