Combined developments across several fields, such as educational research and computer sciences, have led to an evolving landscape of personalized learning and the educational context. Yet, traditional educational settings still struggle to ensure that all students receive adequate support to succeed academically, with most research on personalized learning systems focusing on higher education, often neglecting primary education. This study aims to leverage the use of an artificial intelligence-powered Intelligent Tutoring System (ITS) to enhance the personalization of mathematics learning for third and fourth grade students. For this purpose, an ITS prototype is devised, exploring how student knowledge can be modeled and structured, relying on existing theories, and how personalization should occur during student-system interactions. By applying a design thinking approach, we will assess user experiences and system performance throughout the development process via user interviews and usability testing, involving both students and teachers. We will conduct A/B testing using two versions of the prototype: one with AI-driven personalization and one without. User behavior will also be tracked through questionnaires and analytics tools during testing. The insights gained from data analysis will help evaluate the learning experience delivered by an ITS that utilizes AI-driven techniques for personalization. With these findings, we aim to contribute to the design of ITS tools tailored to the needs of primary education.

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Intelligent tutoring system (ITS),Personalized learning,Education,Artificial Intelligence,Young Learners.