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. De acuerdo a evaluaciones internacionales en los niveles básicos de educación, México se encuentra entre los países que presentan menor puntuación en lo que respecta al aprendizaje de las Matemáticas. Este artículo presenta el diseño de un Sistema Tutor Afectivo para el Aprendizaje de las Matemáticas (STAAM), el cual relaciona situaciones de aprendizaje con ejercicios matemáticos orientados al plan de estudios oficial vigente. El tutor incluye un reconocimiento bimodal de emociones, una técnica de gamificación para la motivación del estudiante y una retroalimentación en cada ejercicio de acuerdo al estilo de aprendizaje del usuario. La puntuación de cada ejercicio se determina con base a variables como el tiempo de respuesta, el número de intentos y el nivel del ejercicio. Se incorporó el estado emocional del estudiante para determinar el siguiente ejercicio. Los resultados obtenidos con estudiantes, mostraron un grado satisfactorio de aceptabilidad como también un avance significativo en ciertos aprendizajes esperados del plan de estudios. Palabras clave:Computación afectiva, sistemas tutores inteligentes, gamificación, software educativo.Abstract. According to international assessments in basic education levels, Mexico is among the countries with the lowest score in regard to the learning of mathematics. This paper presents the design of an Affective Tutoring System for Learning Mathematics (ATSLM), which relates learning situations with mathematical exercises oriented to the current official curriculum in Mexico. The tutor includes a bimodal emotion recognition, a gamification technique for student motivation and feedback for each exercise according to the user's learning style. The score for each exercise is determined based on variables such as response time, number of attempts and the exercise complexity level. Student's emotional state is incorporated to determine the next exercise. The results obtained with students, showed a satisfactory degree of acceptability as a significant advance in certain learning outcomes of the curriculum.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.