On the Design of AI Teaching Assistants for Algorithm Courses with Integrated Teaching, Learning, Assessment and Practice

Algorithm courses are fundamental in undergraduate majors related to information technology. However, with the rapid advancement of artificial intelligence, traditional instructional approaches are encountering both new opportunities and challenges. This study investigates the integration of large language model-based teaching assistants into undergraduate algorithm courses, aiming to establish a new instructional framework that combines teaching, learning, assessment, and practice. By designing intelligent teaching processes and developing an AI assistant system capable of providing personalized guidance, real-time feedback, and adaptive learning support, we seek to promote synergy between algorithm education and AI technology. The proposed model is expected to improve students’ learning efficiency and foster stronger algorithmic thinking and practical problem-solving skills in the context of AI applications. This work offers theoretical perspectives and practical experience on the transformation of algorithm teaching in higher education.