Authors: Priscila Valdiviezo-Díaz, Jorge Cordero, Ruth Reátegui, Jose Aguilar
Abstract:
This work aims to implement business intelligence strategies in an educational institution based on the distance education, particularly in the online tutoring process. In this paper we propose to use the business intelligence paradigm to analyze the online tutoring process, based on the data collected on the interactions of students and teachers in a virtual learning environment, and the results recorded in the institutional academic system of evaluations. This analysis should answer the following questions: 1) Can we define a model of online tutoring that can adapt to each student profile? 2) Can we predict the success of an online tutoring process for a course and a student given? To this purpose, this paper presents three aspects: characterize and determine the key elements in an online tutoring process, build a descriptive model of the online tutoring process, and build a predictive model of the success of the online tutoring process. The models to be defined will be based on data mining techniques, and will be obtained from the current data stored in transactional databases of the University. This data is preprocessed with ETL techniques to build a multidimensional model, and the key elements are obtained through operations OLAP.
Keywords—Business Intelligence Systems, Data Warehouses, Learning Analytics, Online Tutoring
Published in: Frontiers in Education Conference (FIE), 2015. 32614 2015. IEEE
DOI: 10.1109/FIE.2015.7344385
Link: http://ieeexplore.ieee.org/document/7344385/
miércoles, 21 de octubre de 2015
jueves, 30 de julio de 2015
Conceptual Design of a Smart Classroom Based on Multiagent Systems
Authors: Jose Aguilar, Priscila Valdiviezo, Jorge Cordero and Manuel Sánchez
Abstract - The smart environments have been used in different domains: home, educational and health centers, etc. Particularly, a smart environment in education must integrate different aspects linked to virtual and presencial education, the profile of the students, to the pedagogical paradigm used, etc., in real time. In this paper we characterize a smart classroom considering these aspects, using the multiagent systems paradigm. Particularly, we define the different components of a smart classroom with their properties. Based on that, we describe these components like agents using MASINA, a methodology to specify multiagent systems. We define two frameworks of agents which describe the different types of components in a smart classroom (of software and of hardware), and give examples of applications of these two frameworks in a device and a software of a smart classroom. Finally, we show an example of conversation in a smart classroom based on our multiagents approach, specifically in a work session.
Keywords: Smart Classroom, Multiagent System, AmI, Middleware
Proceedings on the International Conference on Artificial Intelligence (ICAI): 471-477. Athens: The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp). (2015)
Link: http://search.proquest.com/openview/930c8d0a31e0faf9bbd8a2a44137e85a/1?pq-origsite=gscholar
Abstract - The smart environments have been used in different domains: home, educational and health centers, etc. Particularly, a smart environment in education must integrate different aspects linked to virtual and presencial education, the profile of the students, to the pedagogical paradigm used, etc., in real time. In this paper we characterize a smart classroom considering these aspects, using the multiagent systems paradigm. Particularly, we define the different components of a smart classroom with their properties. Based on that, we describe these components like agents using MASINA, a methodology to specify multiagent systems. We define two frameworks of agents which describe the different types of components in a smart classroom (of software and of hardware), and give examples of applications of these two frameworks in a device and a software of a smart classroom. Finally, we show an example of conversation in a smart classroom based on our multiagents approach, specifically in a work session.
Keywords: Smart Classroom, Multiagent System, AmI, Middleware
Proceedings on the International Conference on Artificial Intelligence (ICAI): 471-477. Athens: The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp). (2015)
Link: http://search.proquest.com/openview/930c8d0a31e0faf9bbd8a2a44137e85a/1?pq-origsite=gscholar
martes, 28 de julio de 2015
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
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
jueves, 16 de julio de 2015
Basic Features of a Reflective Middleware for Intelligent Learning Environment in the Cloud (IECL)
Authors: Sánchez Manuel, Aguilar, Jose, Cordero Jorge, & Valdiviezo Priscila
Abstract:
In this paper is proposed an architecture of a Reflective Middleware, which aims to manage an Intelligent Environment of Learning based in cloud learning, which is modeled using a Multiagent system. The Middleware is able to monitor the environment consisting of physical and virtual objects, intelligent or not, based on the context. The middleware manages educational services in the cloud to enhance the learning experience of students, either collaboratively or individually.
Keywords— Intelligent Environment; Cloud Learning; Virtual
Published in: Computer Aided System Engineering (APCASE), 2015 Asia-Pacific Conference on
DOI: 10.1109/APCASE.2015.8
Link: http://ieeexplore.ieee.org/document/7286984/
Abstract:
In this paper is proposed an architecture of a Reflective Middleware, which aims to manage an Intelligent Environment of Learning based in cloud learning, which is modeled using a Multiagent system. The Middleware is able to monitor the environment consisting of physical and virtual objects, intelligent or not, based on the context. The middleware manages educational services in the cloud to enhance the learning experience of students, either collaboratively or individually.
Keywords— Intelligent Environment; Cloud Learning; Virtual
Published in: Computer Aided System Engineering (APCASE), 2015 Asia-Pacific Conference on
DOI: 10.1109/APCASE.2015.8
Link: http://ieeexplore.ieee.org/document/7286984/
viernes, 22 de mayo de 2015
Mecanismos de Coordinación en un Salón Inteligente
Autores—Jose Aguilar, Manuel Sánchez, Prisila Valdiviezo, Jorge Cordero
Resumen—En la literatura se han venido especificando ambientes inteligentes para diferentes ámbitos basados en el paradigma de sistemas multiagentes, como por ejemplo para salones
inteligentes. Por otro lado, los componentes de un salón inteligente necesitan permanentemente comunicarse, interactuar, entre otras cosas, ya que muchas de las tareas deben realizarse colaborativamente. De esta manera, los procesos de coordinación son vitales en estos entornos. En este artículo analizamos el problema de coordinación en un salón inteligente modelado usando agentes, en particular, si es posible formalizarlos matemáticamente; además, presentamos varios casos de estudio. Su formalización matemática es fundamental para poder definir modelos de aprendizaje colectivo en el salón inteligente.
Palabras claves—Inteligencia Artificial Distribuida, Sistemas Multiagentes, Domótica, Mecanismos de Coordinación
Conferencia
6TO CONGRESO IBEROAMERICANO DE ESTUDIANTES DE INGENIERÍA ELÉCTRICA (VI CIBELEC 2015)
Link: https://www.researchgate.net/publication/303959647_Mecanismos_de_Coordinacion_en_un_Salon_Inteligente
Resumen—En la literatura se han venido especificando ambientes inteligentes para diferentes ámbitos basados en el paradigma de sistemas multiagentes, como por ejemplo para salones
inteligentes. Por otro lado, los componentes de un salón inteligente necesitan permanentemente comunicarse, interactuar, entre otras cosas, ya que muchas de las tareas deben realizarse colaborativamente. De esta manera, los procesos de coordinación son vitales en estos entornos. En este artículo analizamos el problema de coordinación en un salón inteligente modelado usando agentes, en particular, si es posible formalizarlos matemáticamente; además, presentamos varios casos de estudio. Su formalización matemática es fundamental para poder definir modelos de aprendizaje colectivo en el salón inteligente.
Palabras claves—Inteligencia Artificial Distribuida, Sistemas Multiagentes, Domótica, Mecanismos de Coordinación
Conferencia
6TO CONGRESO IBEROAMERICANO DE ESTUDIANTES DE INGENIERÍA ELÉCTRICA (VI CIBELEC 2015)
Link: https://www.researchgate.net/publication/303959647_Mecanismos_de_Coordinacion_en_un_Salon_Inteligente
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