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Resumen. En este articulo se presenta un ambiente inteligente de aprendizaje con manejo afectivo para Java llamado Java Sensei. El sistema esta disenado para ayudar a los estudiantes de programacion a reforzar distintas areas del conocimiento sobre Java. El sistema evalua aspectos como el estado cognitivo y afectivo del estudiante para tomar las estrategias de intervencion que realizara agente pedagogico, asi como realiza procesos de adaptabilidad por medio de un sistema de recomendaciones. El manejo pedagogico se realizo con una perspectiva Example-Tracing con manejo afectivo.

This paper presents the design and implementation of an intelligent tutoring system (ITS) for teaching JAVA, which can recognize the user's emotional state through facial expressions and textual dialogues. For facial emotion recognition we implemented a neural network with WEKA library and a facial feature extractor with OPENCV library. The ITS applies a semantic algorithm (ASEM) to extract textual emotions through dialogues, which has shown a degree of assertiveness of 80% in tests for graduate students. In addition, the tutor uses a set of fuzzy rules to determine the complexity of the next exercise, considering the program implementation time, program executions and compilations, and current difficulty level.

Resumen. Este articulo presenta el diseno e implementacion de un Ambiente Inteligente de Aprendizaje (AIA) capaz de considerar el perfil completo de un estudiante (incluyendo su estado emocional), para la ensenanza de un tema tan complicado como lo es compiladores. El AIA se encuentra enfocado en el metodo de aprendiz (Apprenticeship) el cual permite a los estudiantes aprender mediante la practica, cambiando el arraigado paradigma del aprendizaje meramente teorico. Se incorporan caracteristicas que permiten al AIA elegir el tipo de ejercicio que mejor convenga al estudiante, comenzando por los mas sencillos e incrementando la dificultad, haciendo uso de clasificacion con logica difusa y reconocimiento de emociones. Palabras clave: computacion afectiva, sistemas tutores inteligentes, redes neuronales, sistemas difusos, aprendizaje maquina, ambientes inteligentes.

We have developed an affective and intelligent learning environment that helps students to improve their Java programming skills. This environment evaluates cognitive and affective aspects of students in order to define the level of difficulty of the exercises that are more suitable for the them in its current condition. The cognitive aspects are: the number of mistakes, the difficulty level of the current exercise and the time spent in the solution. The affective aspects are: the acquired emotion from a facial expression and the acquired valence from electroencephalogram signals. This environment also uses a neural network for face recognition of basic emotions, a support vector machine to define the valence of emotion and a fuzzy inference engine to evaluate the cognitive and affective aspects.

The current document presents the design and implementation of an Intelligent Tutoring System (ITS) capable of being configured by different experts, in fields that are important for an ITS. Several features have been implemented so that the specialists are the ones who provide the required tools for the teaching of 3 rd grade natural numbers. The ITS can be modified by adding fuzzy sets and rules, by changing the Affective module, the diagnostic test and student's learning style. This allows the ITS to change according to the environment and to the needs of the students that uses it.

We present the different steps used for developing an Affective and Intelligent Tutoring System for Mathematics Learning. The intelligent tutoring system evaluates cognitive and affective aspects of the users or students in order to present the learning material to them. The whole system applies a fuzzy logic system to decide the next exercise and a neural network to recognize user emotions.

We present Fermat, an Intelligent Social Network for Mathematics Learning, which integrates an Intelligent Tutoring System as an extra feature to help improve the teaching and learning process. The intelligent tutor takes into account both cognitive and affective factors, and by use of artificial intelligence techniques, provides users with a personalized and satisfying experience when taking the courses.