Teaching Reform Exploration of Information Retrieval Course in the Artificial Intelligence Era - Sheng, Yu; Wu, Ying (Journal of Educational Research and Policies, 2025)
The development of artificial intelligence has brought about technological innovation in the field of information retrieval, which has also brought a series of problems such as non-transparency of the process, difficulty in recognizing misinformation and intellectual property rights while achieving convenience. Starting from the characteristics of information retrieval courses, this paper explores the intelligent reform of information retrieval courses from the three aspects of value dilemma, knowledge and technology dilemma and teaching method dilemma, based on the Artificial Intelligence Competency Framework for Teachers issued by UNESCO. The conclusions show that information retrieval teachers should clarify classroom ethical and legal responsibilities, critically evaluate and use search results and advocate green retrieval. In terms of course content, authoritative AI tools should be selected, AI retrieval cases should be increased, AI retrieval technology tracking should be maintained, and the whole process of information retrieval course should be reorganized by AI. Teaching methods should adopt AI to assist teachers in lesson preparation as well as AI participation in personalized teaching and classroom management. Finally, the school level and the legal level should be urged to generate a teaching environment that is conducive for the integration of AI and information retrieval courses.