Exploring learning analytics on YouTube: a tool to support students interactions analysis

Abstract

YouTube is a free online video-sharing platform that is often used by students for their learning activities. The interactions of the students when using the platform to shape new concepts, are worth to be investigated to better understand and to optimize the learning opportunities that take place in this platform. In this paper, we investigate which types of data are relevant to analyse the interactions of students with content on YouTube, and we introduce a new tool that emulates students' interactions with the platform in order to provide data to be used in supporting Learning Analytics approaches. Our preliminary study inspects the tool effectiveness in data collection and analyses the effects of the YouTube recommendation system in students' activities. We also identify methodologies based on statistical indexes and social network analysis that can be adopted to analyse students' experiences. Results show how the YouTube recommendation system plays a critical role in affecting the student learning trajectory.