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智能教育领域的知识追踪模型综述
(东北石油大学 计算机与信息技术学院, 大庆 163318)
Review of Knowledge Tracing Models in Intelligent Education Field
(School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China)
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Received:November 26, 2024    Revised:January 24, 2025
中文摘要: 知识追踪技术可以对学生题目作答序列等数据进行分析, 从而准确预测学生的知识点掌握状况, 以帮助教育管理者更精确地对学生进行教学干预, 提升学生的学习效果. 随着时间的推移, 知识追踪技术已经成为实现智能教育目标的重要辅助手段, 并在智能教育领域得到了广泛应用. 本综述主要研究智能教育领域的知识追踪技术发展现状. 首先, 本综述对知识追踪技术进行了概念界定; 随后, 分析了两类智能教育领域的知识追踪模型及其存在的问题, 同步总结了国内外研究者对这些问题的应对策略; 接下来, 探讨了智能教育领域知识追踪模型的实际应用场景; 最后, 明确指出了智能教育领域的知识追踪模型面临的各种挑战, 并对其未来发展进行了展望.
Abstract: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.
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基金项目:国家人文社会科学基金 (22BTJ046); 黑龙江省哲学社会科学规划项目 (22EDE389)
引用文本:
赵娅,托晋宽,单可欣,贾迪.智能教育领域的知识追踪模型综述.计算机系统应用,2025,34(6):1-11
ZHAO Ya,TUO Jin-Kuan,SHAN Ke-Xin,JIA Di.Review of Knowledge Tracing Models in Intelligent Education Field.COMPUTER SYSTEMS APPLICATIONS,2025,34(6):1-11