MMLA approach to analyze collaborative work in Lego Serious Play activities

Today, the training of professionals has the enormous challenge of covering both the development of professional skills and soft skills. In the educational field of software engineering, teachers should be supported by technology to facilitate the monitoring and development of these skills in students. The use of technology should help teachers to fulfill their role as facilitators of learning and students to become active agents of their learning. In this paper, we present Naira-Hand, as a new approach to multimodal learning analytics that facilitates the analysis of collaborative work conducted with the Lego Serious Play methodology. The multimodal data are obtained through a neural network that processes a video of the activity. These multimodal data are then processed, and different visualizations allow us to observe the collaborative work from different perspectives. Even though health restrictions have prevented us from carrying out the planned experiments, we have obtained very positive results in the detection of people interactions and in visualizations, which allow us to obtain a panoramic view of the collaborative work developed by the students.