Abstract:In the context of digital transformation in education and intelligent empowerment of higher education, our course team has conducted in-depth exploration on three core issues: the content system of Modern Engineering Microbiology with electronic information characteristics, the optimization of teacher-student-machine deep interaction, and the full-cycle accurate real-time evaluation. We have built a smart course ecosystem that integrates graph empowerment, intelligent companion learning, and digital intelligence evaluation. The system is based on the fundamental theory of microbiology and utilizes a multidimensional graph encompassing knowledge, problem, and education to visualize and logicalize complex concepts, mechanisms, engineering problems, and value goals, achieving structured navigation of course contents. Through the deep incorporation of interdisciplinary core knowledge connections in the talent training program for biomedical engineering, the achievement of learning objectives has been strengthened. In addition, we have developed an intelligent teaching assistant system based on massive digital resource training iterations to provide personalized learning paths and instant feedback, effectively enhancing students’ mastery of course contents. The independently developed multimodal digital intelligence evaluation system for comprehensive education can track and visualize students’ learning outcomes throughout the process, achieving precise guidance. After multiple iterations of teaching practice, the results show that students’ mastery of knowledge points, engagement in self-directed learning, and academic performance have all significantly improved. The construction of this intelligent course ecosystem not only improves teaching efficiency and fosters students’ active learning and critical thinking, but also fairly and justly quantifies the learning outcomes of students throughout the entire process, laying a solid foundation for cultivating outstanding innovative talents in biomedical engineering in the context of emerging engineering education.
