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

Specification of a Smart Classroom Based on Agent Communities

Authors: Jose Aguilar, Luis Chamba-Eras,  Jorge Cordero

Abstract
For the development of distributed applications, it is required to define a formalization of the process of implementation. Particularly, we are interested in one type of Ambient Intelligence (AmI), the Smart Classroom. In this paper we propose the implementation of a Smart Classroom, called SaCI, using the concept of communities of agents. With this concept, we carry out the definition and implementation of sets of agents according to their roles, functionalities, characteristics, among others, in SaCI. Each community can be designed and implemented independently and later be integrated in SaCI. In this paper we present this approach and its implementation in SaCI.

Keywords
Smart educational environment, Multi-agent system, Ambient intelligence

Link: http://link.springer.com/chapter/10.1007%2F978-3-319-31232-3_95

DOI: 10.1007/978-3-319-31232-3_95

A Smart Learning Environment based on Cloud Learning

Authors: Sánchez, M., J. Aguilar, J. Cordero, and P. Valdiviezo.

Abstract—In this paper is presentedan architecture of a Reflective Middlewarebased in Cloud Learning, for Intelligent Learning Environments.The middleware is defined using theMultiagent Systemsparadigm, and propose academic services on the cloud based on the current context.That is, the middlewaremanages educational services in the cloud to enhance the learning experience of students, either collaboratively or individually.In that sense, in this paper is detailed the middleware components, which enable the process of management of the cloud computing. The paper also presents examples of the utilization of the middleware to provide services on the cloud about tasks of learning analytics, which allow processing of data of students and learning environment in order to understand and optimize their learning processes.

Index terms -Intelligent Learning Environment; Cloud Learning; Reflective middleware; Ambient Intelligence

Link: http://www.academia.edu/download/41072580/A_Smart_Learning_Environment_based_on_Cloud_Learning.pdf