Bringing Collaborative Analytics using Multimodal Data to the Masses

This talk was given at the 14th International Conference of Learning Analytics & Knowledge to present results from an evaluation study of CoTrack (a multimodal learning analytics tool), also published in the form of a conference paper. The study analyzed and reported results from teachers’ responses on using CoTrack in their classroom for collaborative learning activities.

You can read more about the presented work here: Paper.

Presentation slides: Slides

Abstract

The Multimodal Learning Analytics (MMLA) research community has significantly grown in the past few years. Researchers in this field have harnessed diverse data collection devices such as eye- trackers, motion sensors, and microphones to capture rich mul- timodal data about learning. This data, when analyzed, has been proven highly valuable for understanding learning processes across a variety of educational settings. Notwithstanding this progress, an ubiquitous use of MMLA in education is still limited by challenges such as technological complexity, high costs, etc. In this paper, we introduce CoTrack, a MMLA system for capturing the multimodal- ity of a group’s interaction in terms of audio, video, and writing logs in online and co-located collaborative learning settings. The system offers a user-friendly interface, designed to cater to the needs of teachers and students without specialized technical expertise. Our usability evaluation with 2 researchers, 2 teachers and 24 students has yielded promising results regarding the system’s ease of use. Furthermore, this paper offers design guidelines for the develop- ment of more user-friendly MMLA systems. These guidelines have significant implications for the broader aim of making MMLA tools accessible to a wider audience, particularly for non-expert MMLA users.