Intelligent tutoring system: New criteria and evaluation to measure students’ degree of mastery

Abstract

Intelligent Tutoring Systems (ITSs) are computer software designed to simulate or imitate a human tutor’s behavior and guidance. ITSs can be seen as personalized tutoring systems that arouse students’ learning enthusiasm. One of the important features of ITS is the capability to interpret complex student’s responses and to estimate the student’s degree of mastery, and as a result, it manages to adjust the behaviour of the tutoring accordingly. Mastery learning requires that the tutoring system have a mechanism to evaluate the student’s degree of mastery in a particular knowledge. Motivated by this, and realizing that ITS still needs to improve its capability in helping students attain knowledge according to their degree of mastery of the underlying knowledge of a particular topic, this study has proposed new criteria and approaches to measure the student’s degree of mastery through data pre-processing. The pre-processing was done on some data files to obtain more meaningful data to achieve the aim. From the results obtained, it was shown that student’s degree of mastery was able to be measured through the proposed approach. This can benefit the ITS to be a personalized tutor according to the student’s capability.

Keywords

• intelligent tutoring system
• mastery level
• pre-processing
• evaluation criteria
• evaluation function