Exploring indicators for collaboration quality and its dimensions in classroom settings using multimodal learning analytics

This talk was given at the European conference of technology-enhanced learning organized by the University of Aveiro, Portugal. In this talk, I presented results from a research study exploring relationships between multimodal data (audio, video, and logs) and collaboration quality (and its dimensions as such argumentation). The study identified several key indicators (e.g., verticle head movement) for collaboration quality and its dimensions.

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

Presentation slides: Slides

Abstract

Multimodal Learning Analytics researchers have explored re- lationships between collaboration quality and multimodal data. How- ever, the current state-of-art research works have scarcely investigated authentic settings and seldom used video data that can offer rich be- havioral information. In this paper, we present our findings on potential indicators for collaboration quality and its underlying dimensions such as argumentation, and mutual understanding. We collected multimodal data (namely, video and logs) from 4 Estonian classrooms during au- thentic computer-supported collaborative learning activities. Our results show that vertical head movement (looking up and down) and mouth region features could be used as potential indicators for collaboration quality and its aforementioned dimensions. Also, our results from clus- tering provide indications of the potential of video data for identifying different levels of collaboration quality (e.g., high, low, medium). The findings have implications for building collaboration quality monitoring and guiding systems for authentic classroom settings.