Learner Profiling in Intelligent Tutoring Systems: A New Perspective

Abstract

Student profiling lays the foundations of the personalization that happens in adaptive educational applications and Intelligent Tutoring Systems (ITS). A student’s level of knowledge on a topic is estimated from their performance on certain activities related to the topic. For this, researchers have devised many model extensions throughout the years that incorporate specific cognitive features into student profiling. In this paper, a new framework for student profiling has been proposed. The proposed framework takes into account features that include question quality and errors in the formulation of practice items.