Learning style detection software based on the Felder and Silverman model
Abstract
Learning styles define characteristic behaviors that identify how a person learns and adapts to their environment. These provide teachers with elements that can guide them in creating appropriate pedagogical and didactic content adapted to the characteristics of students, thereby improving their performance and consolidating their learning processes. This paper presents a learning style detection software based on the Felder and Silverman model to help identify learning styles in an individual or group. The document describes the functionalities, architecture, implementation details, and general characteristics of the software. An example of system operation is provided and discussed, as well as the results of its functional and non-functional tests, which were satisfactory. It was concluded that the system is a useful tool for teachers, facilitating the identification of learning styles and the customization of teaching strategies, which improves the educational process.
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