Exploration of Data Science Course Teaching Based on the RAP Model
摘要
To meet the urgent demand for data-science talent in the big-data era and to remedy the deficiencies of traditional teaching models, this paper analyzes key instructional pain points and proposes a triadic RAP instructional model integrating Resources (R), an AI assistant (A), and a practical Platform (P), respectively. By systematically unifying these components, the model effectively addresses existing instructional challenges and enhances both the quality and the efficiency of data-science courses.