Research on the Construction and Empirical Effects of the “AIED+” Multi-intelligent Teaching Model

To align with the digital transformation trend in higher education, a multi-intelligent teaching model was constructed using the BOPPPS teaching model as its underlying framework, integrating AI technology and diverse teaching methods. Taking the “Road Survey and Design” course as an example, this paper systematically elaborates on its construction process and implementation pathway. After one semester of teaching practice, the effectiveness of implementation was comprehensively evaluated through student learning satisfaction surveys, assessing dimensions such as learning engagement, satisfaction, course grades, and goal attainment. Results indicate that this model significantly enhances student learning motivation, optimizes teaching resource allocation and personalized instruction implementation, and effectively promotes overall learning outcomes. Concurrently, it provides instructors with AI teaching assistant support, high-quality student performance data analysis, and teaching process management tools, thereby boosting teaching efficiency and classroom management capabilities. This research validates the feasibility and application value of integrating AI with the BOPPPS model and diverse teaching methods in the digital transformation of engineering education.