Applications of Explainable AI (XAI) in Education

As one of the emerging methods for increasing trust in Artificial Intelligence (AI) systems, explainable AI promotes the use of methods that produce transparent explanations and reasons for decisions made by AI. In this chapter, we present an overview of applications of explainable AI in education with examples of empirical studies. More specifically, we discuss the following questions: What are the main categories of explainable AI approaches used to interpret and explain AI models? What are the unique characteristics of the use of explainable AI in education? How can explainable AI models be used by teachers, students, and researchers to inform their decisions? What are the challenges and potentials for explainable AI applications in education?