A Theoretical Framework for Knowledge Level Assessment in Intelligent Tutoring Systems Using Machine Learning and Adaptive Testing

Rangasubramanian K

Abstract


Machine learning, in general and knowledge level assessment, in particular are gaining momentum these days in the academic and industrial forums due to their immense scope and myriad applications. Ground breaking research has been carried out in the area of student modeling, performance prediction, difficulties faced by a student in a learning environment and so on. This paper attempts to propose only a theoretical framework wherein an intelligent tutoring system would be able to pinpoint a candidate’s knowledge level in a particular topic using various attributes such as question difficulty, time for solving and correctness of answers.


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ISSN : 2251-1563