Motivation assessment model for intelligent tutoring system based on mamdani inference system

• Main Authors: Thinakaran, Rajermani, Chupra, Suriayati, Batumalay, Malathy
• Format: Article
• Language: English
• Published: Institute of Advanced Engineering and Science 2023
• Subjects: T Technology (General)
• Online Access: http://eprints.utm.my/107581/1/SuriayatiChupra2023_MotivationAssessmentModelForIntelligentTutoring.pdf; http://eprints.utm.my/107581/; http://dx.doi.org/10.11591/ijai.v12.i1.pp189-200
• Institution: Universiti Teknologi Malaysia

Many educators have used the benefit offer by intelligent tutoring system. To become more personalizing and effective tutoring system, student characteristics need to be considered. One of important student characteristic is motivation. Therefore, in this study a motivation assessment model based on self-efficacy theory was proposed. Refer to the theory, effort, choice of activities, performance and persistence were discussed as motivation attributes. Further, time spend, difficulty level, number of correct answers and number of questions skipped are the parameters was defined for each attribute. The model was designed by taking the advantages of Mamdani inference system as fuzzy logic technique to predict students’ motivation level. The model able to inmates like a human tutor does in the traditional classroom to understand students’ motivation level.