Student Modeling: Supporting Personalized Instruction, from Problem Solving to Exploratory Open-Ended Activities

The core of this personalized instruction is a student model: the ITS component in charge of assessing student traits and states relevant to tailor the tutorial interaction to specific student needs during problem solving. There are however, other educational activities that can help learners acquire the target skills and abilities at different stages of learning including, among others, exploring interactive simulations and playing educational games. This article de - scribes research on creating student models that support personalization for these novel types of interactions, their unique challenges, and how AI and machine learning can help. Intelligent tutoring systems (ITSs) are the ultimate example of this challenge: their goal is to provide instruction personalized to the specific needs of each learner, as good human tutors do. But understanding these needs can be extremely hard, because it entails modeling and capturing that complex ensemble of processes and states that constitutes human learning.