Empowerment and Reconstruction: A New Paradigm for Teaching Transportation Courses Integrated with AI Literacy

As Artificial Intelligence (AI) technology profoundly reshapes the transportation landscape, cultivating versatile talents with AI literacy has become the core task of the curriculum reform in “Transportation Operations and Management”. This paper addresses problems in the traditional teaching model, such as the gap between theory and practice, insufficient student innovation, and the limitation of single evaluation methods. It proposes a new project-based teaching model that deeply integrates AI literacy and constructs a corresponding dual-layer interactive teaching evaluation system for teacher-student and student-student interactions. The article systematically elaborates on the design concepts and implementation path of this model. Through a closed-loop process of “grouping—topic selection—research—evaluation”, it uses intelligent connected vehicles as a specific practical field to guide students in addressing real industry problems. At the same time, the dual-layer evaluation system, through bidirectional evaluation between teachers and students as well as intergroup interactive assessment, breaks the traditional hierarchical barriers in education and establishes a teaching ecosystem characterized by “equal dialogue and collaborative competition”. The comprehensive reform strategy proposed in this paper can effectively stimulate students’ intrinsic motivation for learning, comprehensively enhance their abilities in AI technology application, teamwork, and critical thinking, and provide a replicable and promotable new approach for teaching innovation in transportation-related courses in the new era.