Teaching Reform of “Telecommunication Electronic Circuits” Based on the Integration of Artificial Intelligence and Human Wisdom

As an important compulsory course for the students who major in telecommunications engineering, the Telecommunication Electronic Circuits (High-Frequency Electronic Circuits) course confronts two major challenges: high knowledge complexity and limited resources for practical engineering training. In order to overcome the challenges and promote teaching effects, we utilize the scheme of integrating artificial intelligence (AI) technology with human wisdom in teaching the Telecommunication Electronic Circuits course. The scheme combines the advantages of both AI technology and human wisdom. AI technology can take the responsibilities in records of learning process, analyses of learning data, knowledge delivery of adaptive content based on personalized recommendations, automatic assessment and feedback. Teachers can pay more attention to critical thinking cultivation, engineering experience transmission, values shaping and professional ethics cultivation. In pre-class phase, with AI technology, some preparatory short videos and related questions are pushed to learners for personalized learning. Then, teachers preview the response data of learners and the AI-generated feedback to adjust lesson focus accordingly. In the phase of in-class teaching, teachers explain core principles and those misunderstanding according to the response data generated in the pre-class phase. Circuit simulations are also shown and discussed. During the class, discussions on theoretical analyses, circuit simulation results and actual circuits’ performance are organized. In the process, teachers not only convey engineering thought and experience, but also cultivate innovation thinking and proper ethical values. In post-class phase, AI automatically grades homework of learners, offers real-time feedback, and creates individualized learning profiles. Then, teachers design research projects with different difficulties for learners’ further practical study based on the individualized learning profiles generated by AI. Such a personalized learning process is beneficial to foster the learning interests of each learner and conduct them to achieve more. Besides, AI can help teachers find those who might need assistance in learning, so that teachers can implement early interventions to mitigate academic failure risks. By adopting the scheme, we have improved the test pass rate of lower-performing learners by about 18% in 2024 compared to 2023. The paper then describes the challenges of the scheme and give some comments on the teachers’ role transformation, ethical boundaries, and hybrid assessment systems. The limitation of AI technology nowadays is also discussed.