Specification of the Autonomic Cycles of Learning Analytic Tasks for a Smart Classroom

Authors: Jose Aguilar, Jorge Cordero and Omar Buendía

Abstract:
In this article, we propose the concept of ‘‘Autonomic Cycle Of Learning Analysis Tasks’’ (ACOLAT), which defines a set of tasks of learning analysis, whose objective is to improve the learning process. The data analysis has become a fundamental area for the knowledge discovery from data extracted from different sources. In the autonomic cycle, each learning analysis task interacts with each other and has different roles: Some of them must observe the learning process, others must analyze and interpret what happens in it, and finally, others make decisions in order to improve the learning process. In this article, we study the application of the autonomic cycle in a smart classroom, which is composed of a set of intelligent components of hardware (e.g., smart board) and software (e.g., virtual learning environments), which must exploit the knowledge generated by the ACOLAT to improve the learning process in the smart classroom. Moreover, we present the set of ACOLATs present in a smart classroom and the implementation of some of them.

Keywords: Learning Analytics, Smart Classroom, Autonomic Computing, Learning Environments, Knowledge Discovery

Link: http://journals.sagepub.com/doi/abs/10.1177/0735633117727698

Competences as Services in the Autonomic Cycles of Learning Analytic Tasks for a Smart Classroom

Authors: Alexandra González-Eras, Omar Buendia, Jose Aguilar, Jorge Cordero and Taniana Rodriguez

Abstract:
Learning Analytic is a useful tool in the context of the learning process, in order to improve the educational environment. In previous works, we have proposed autonomic cycles of learning Analytic tasks, in order to improve the learning process in smart classrooms. One aspect to be considered by the autonomic cycles is their adaptability to the formation of competences, assuming that a student has competences that must be strengthened during the learning process. In this paper, we propose the utilization of competences to guide the adaptation process of a learning environment. Particularly, we propose the extensions of the autonomic cycles for smart classrooms, using the idea of competences. In this case, we define the competences as a service, to help the autonomic cycles in their processes of adaptation.

Keywords: Learning analytics, Smart classroom, Educational competences, Autonomic cycles

Link: https://link.springer.com/chapter/10.1007/978-3-319-67283-0_16

Different Intelligent Approaches for Modeling the Style of Car Driving

Authors: Jose Aguilar, Kristell Aguilar, Danilo Chávez, Jorge Cordero and Eduard Puerto

Abstract:
In this paper, we propose a hierarchical pattern of the style of driving, which is composed of three levels, one to recognize the emotional state, other to recognize the state of the driver, and finally, the last one corresponds to the style of driving. Each level is defined by different types of descriptors, which are perceived in different multi-modal ways (sound, vision, etc.). Additionally, we analyze three techniques to recognize the style of driving, using our hierarchical pattern, one based on fuzzy logic, another based on chronicles (a temporal logic paradigm), and another based on an algorithm that models the functioning of the human neocortex, exploiting the idea of recursivity and learning in the recognition process. We compare the techniques considering the dynamic context where a car driver operates.

Keywords: Hierarchical Patterns, Fuzzy Logic, Chronicles, Dynamic Pattern Recognition, Style of Driving

Link: http://www.scitepress.org/DigitalLibrary/PublicationsDetail.aspx?ID=pKH2LWLdplY%3d&t=1

Towards a Fuzzy Cognitive Map for Opinion Mining

Authors: Jose Aguilar, Oswaldo Téran, Hebert Sánchez, José Gutiérrez de Meza, Jorge Cordero, and Danilo Chávez

Abstract:
In this paper, we propose a Fuzzy Cognitive Map (FCM) to opinion mining, with special attention to media influence on public opinion. Particularly, in this paper, we describe the FCM, the concepts and relationships among them. Our opinion mining model is based on a multilevel FCM, to distribute the concepts according to the aspects that describe the elements conforming public opinion, which are: social, technological and biological. We carry out preliminary tests, and the results are very encouraging.

Keywords: Fuzzy Cognitive Maps, Opinion Mining, Opinion Conformation, Media Manipulation

Link: http://www.sciencedirect.com/science/article/pii/S1877050917309432

Learning analytics tasks as services in smart classrooms

Authors: Jose Aguilar, Manuel Sánchez, Jorge Cordero, Priscila Valdiviezo-Díaz, Luis Barba-Guamán and Luis Chamba-Eras

Abstract:
A smart classroom integrates the different components in a traditional classroom, by using different technologies as artificial intelligence, ubiquitous, and cloud paradigms, among others, in order to improve the learning process. On the other hand, the learning analytics tasks are a set of tools that can be used to collect and analyze the data accumulated in a smart classroom. In this paper, we propose the definition of the learning analytics tasks as services, which can be invoked by the components of a smart classroom. We describe how to combine the cloud and multi-agent paradigms in a smart classroom, in order to provide academic services to the intelligent and non-intelligent agents in the smart classroom, to adapt and respond to the teaching and learning requirements of students. Additionally, we define a set of learning analytics tasks as services, which defines a knowledge feedback loop for the smart classroom, in order to improve the learning process in it, and we explain how they can be invoked and consumed by the agents in a smart classroom.

Keywords: Learning analytics as service, Smart classroom, Cloud computing, Ambient intelligences

Link: http://link.springer.com/article/10.1007%2Fs10209-017-0525-0
Other link: Learning analytics tasks as services in smart classrooms

Cite this article as:

Aguilar, J., Sánchez, M., Cordero, J. et al.

Univ Access Inf Soc (2017).

doi:10.1007/s10209-017-0525-0