Research and practice on the blended teaching of Modern Engineering Microbiology empowered by large language model and intelligent evaluation

Abstract:

Under the background of digital transformation in education, higher education presents a trend of diversification, personalization, and intelligence. Conventional teaching models cannot fully meet the diverse learning needs of students. Modern Engineering Microbiology, as a course leveraging the strengths of the discipline of electronics and information at Xidian University, aims to cultivate outstanding interdisciplinary and innovative talents in biomedical engineering with a distinctive electronic information character, as well as future leaders in the field. The course is application-oriented, interdisciplinary, and challenging in depth. In the current context of artificial intelligence (AI)+education, it is of great significance to integrate AI into the teaching reform. We investigate the blended teaching practice of this course for the students majoring in biomedical engineering at Xidian University, with focus on the application of human-machine collaborative learning based on the large language model and the team’s self-developed deep network intelligent evaluation model throughout the entire process in course design and teaching process. We encourage students to utilize AI to assist learning and fully leverage the role of AI in assisted teaching. The human-machine collaborative learning model enables the interactive learning of students, who can obtain the necessary knowledge and feedback and thus improve the learning efficiency. At the same time, the intelligent evaluation platform throughout the entire process plays a guiding and supervisory role to ensure the quality of learning. The research and practice results indicate that this teaching model improves the quality and effectiveness of teaching and learning, providing a paradigm and experience for the reform of higher education curriculum in the context of digital transformation.

Key words:large language model;intelligent evaluation throughout the entire process;Modern Engineering Microbiology;blended teaching;human-machine collaborative learning