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Typifying Students’ Help-Seeking Behavior in an Intelligent Tutoring System for Mathematics
Tipificación de comportamientos de estudiantes relacionados con la búsqueda de ayuda en un sistema inteligente de tutorías para matemáticas
DOI:
https://doi.org/10.15446/ing.investig.v42n2.84495Keywords:
Educational technology, Educational innovation, Mining sequence data, Intelligent tutoring system, Behavioral education. (en)Tecnología Educativa, Innovación Tecnológica, Minería de Datos, Sistemas Tutores Inteligentes, Ciencias del Comportamiento (es)
The use of tutoring systems has become normalized in secondary schools (grades 7-9) in many parts of the world. There have been studies analyzing the students' behavior, their affective responses, or the abuse of the system, but little has been done to discover other types of behavior. This paper presents evidence that there are different types of help-seeking behavior which can be typified in Mexican students interacting with the Scooter intelligent tutoring system (ITS), which was designed to teach mathematics at secondary-level. The implemented methodology consisted of applying discovery algorithms and data mining to typify students in terms of their help-seeking behaviors. The results and contributions of this work suggest that gaming the system with the aforementioned ITS may not always be useful. Future work will analyze other student groups who have used this software in other parts of the world to correlate these typologies to students' traits or opinions about mathematics and learning.
En muchas partes del mundo se ha normalizado el uso de sistemas de tutoría en las escuelas de secundaria (grados 7 a 9). Se han realizado estudios que analizan el comportamiento de los estudiantes, sus respuestas afectivas o el abuso del sistema, pero se ha hecho poco para descubrir otros tipos de comportamiento. Este artículo presenta evidencia de que existen diferentes tipos de comportamiento de búsqueda y solicitud de ayuda, los cuales pueden tipificarse en estudiantes que interactúan con el sistema tutor inteligente (STI) Scooter, diseñado para enseñar matemáticas a estudiantes de secundaria. La metodología implementada consistió en aplicar algoritmos de descubrimiento y minería de datos para tipificar a los estudiantes en términos de su comportamientos de búsqueda de ayuda. Los resultados y las contribuciones de este trabajo sugieren que “jugar con el sistema” del STI ya mencionado no siempre es útil. El trabajo futuro analizará otros conjuntos de estudiantes que han utilizado el tutor inteligente en otras partes del mundo para correlacionar estas tipologías con los rasgos u opiniones de los estudiantes sobre las matemáticas y el aprendizaje.
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Copyright (c) 2021 Roberto Angel Melendez-Armenta, Genaro Rebolledo-Mendez, N. Sofia Huerta-Pacheco
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