Development of a Software that Supports Multimodal Learning Analytics: A Case Study on Oral Presentations

Roberto Munoz (Universidad de Valparaíso, Chile)

Rodolfo Villarroel (Pontificia Universidad Catolica de Valparaíso, Chile)

Thiago S. Barcelos (Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, Brazil)

Alexandra Souza (Instituto Federal de Educação, Ciência e Tecnologia de São Paulo, Brazil)

Erick Merino (Universidad de Valparaíso, Chile)

Rodolfo Guiñez (Universidad de Valparaíso, Chile)

Leandro A. Silva (Universidade Presbiteriana Mackenzie, Brazil)

Abstract: Learning Analytics is the intelligent use of data generated from students with the objective of understanding and improving the teaching and learning process. Currently, there is a lack of tools to measure the development of complex skills in real classroom environments that are flexible enough to add and process data from different sensors and oriented towards a massive public. Based on this finding, we developed a free software system that permits to capture and to visualize a set of 10 body postures using the Microsoft Kinect sensor, along with the ability to track custom body postures and data from other sensors. The developed tool was validated by means of precision and usability tests. Furthermore, with the goal of demonstrating the potential of incorporating this type of software into the classroom, the software was used as a tool to give feedback to the teacher and to the students at the moment of giving and evaluating oral presentations. Also, a clustering analysis of data gathered from 45 student presentations indicate that presentations on similar topics with also similar complexity levels can be successfully discriminated.

Keywords: microsoft kinect, multimodal learning analytics, oral presentations, self-organizing maps

Categories: D.2.2, L.0.0, L.1.1, L.3.0, L.3.6