Knowledge tracing technology analyzes data, such as students’ response sequences to questions, to accurately predict their mastery of knowledge points. This allows for more precise educational interventions and improves students’ learning outcomes. Over time, knowledge tracing technology has become a vital tool in achieving intelligent education goals and is widely applied in this field. This review examines the current development of knowledge tracing technology in intelligent education. First, the concept of knowledge tracing technology is defined. Next, two types of knowledge tracing models and their associated issues are analyzed, and the strategies proposed by researchers to address these challenges are summarized. The review then explores the practical application scenarios of knowledge tracing models in intelligent education. Finally, various challenges faced by knowledge tracing models in this field are outlined, and future development prospects are discussed.