A general framework for learning analytic in a smart classroom

Authors: Jose Aguilar, Priscila Valdiviezo, Jorge Cordero, Guido Riofrio, and Eduardo Encalada

Abstract. In this paper, we propose the utilization of the “Learning Analytics” paradigm in a Smart Classroom, a classroom that integrates artificial intelligence technology on the educational process. Learning Analytics can extract knowledge from the Smart Classroom platform, to better understand students and his/her learning processes. In this way, a Smart Classroom can understand and optimize
the learning process and the teaching environments proposed. The smart classroom can adapt its components to improve students’ performance, among other aspects. Particularly, this paper proposes a framework about how the Learning Analytics paradigm can be used in a Smart Classroom, in order to provide knowledge about the activities taking place within it. The framework is defined like a closed cycle of Learning Analytics tasks, which generate metrics used like feedback to optimize the pedagogical model proposed by the smart Classroom. The metrics evaluate the learning process and pedagogical practice provided by the smart Classroom. So, our main contribution is about how the Learning Analytics paradigm can be used in a Smart Classroom in order to improve the students’
performance.

Keywords: Learning analytics, Smart classroom,  Ambient intelligence, Data mining

Link: http://link.springer.com/chapter/10.1007/978-3-319-48024-4_17

DOI: 10.1007/978-3-319-48024-4_17