Innovative Practice of Smart Education under the Background of Digital-Commerce Empowerment of Agriculture: AI Integration Approach in E-commerce Data Analysis Course

The objective of this research is to innovate the teaching model of the e-commerce data analytics course by utilising artificial intelligence to address the challenges faced by traditional teaching methods. The development of a substantial model-based intelligent library system has been undertaken, integrating an AI teaching assistant, a knowledge graph, and a recommendation engine based on deep learning. The system is capable of accurately matching resources based on learners' cognitive characteristics. The proposed hybrid teaching model integrates online and offline components and is based on an “AI two-teacher collaboration” mechanism. This collaboration facilitates cognitive construction and teacher guidance for value enhancement. The model also introduces a data-driven, industry-embedded context. The data-driven, three-dimensional teaching framework encompasses industry context embedding, cognitive apprenticeship and value immersion education. A multidimensional assessment system combining formative and summative assessment was adopted, and the assessment methods were reorganized. Empirical evidence demonstrates that the model significantly enhances students' data analysis and comprehensive abilities, while concomitantly improving teaching efficacy, students' performance, competition results, and course evaluation. It can be used as a reference paradigm for the reform of business courses in the smart era.