Abstract
In this paper, we present a multiplatform and Intelligent Tutoring System for learning Java (Java Sensei). The learning system combines state-of-the-art action selection, motivation through emotions, a modern recommendation mechanism, and multimodal instructional and selection learning. Java Sensei architecture works with a collection of modules and processes, each with its own effective representations and algorithms. The learning system was implemented under different learning methodologies like problem-solving for the pedagogical module, knowledge space for the expert module, and overlays for the student module. One of the main contributions of this work was the integration of cognitive and affective information in a behavioral graph which is used by a learning companion to show emotions and empathy to the student. Java Sensei was tested with different groups of university students with which we obtained positive results. In addition to providing a detailed description of the implementation and evaluation of Java Sensei, we also provide some proposals of future work in our intelligent tutoring systems.
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The work described in this paper is fully supported by a grant from the DGEST (Dirección General de Educación Superior Tecnológica) in Mexico under the program “Projects of Scientific Research and Technological Innovation”.
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Barrón-Estrada, M.L., Zatarain-Cabada, R., Hernández, F.G., Bustillos, R.O., Reyes-García, C.A. (2015). An Affective and Cognitive Tutoring System for Learning Programming. In: Pichardo Lagunas, O., Herrera Alcántara, O., Arroyo Figueroa, G. (eds) Advances in Artificial Intelligence and Its Applications. MICAI 2015. Lecture Notes in Computer Science(), vol 9414. Springer, Cham. https://doi.org/10.1007/978-3-319-27101-9_12
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