Teaching Reform of the Database Systems Course Based on Artificial Intelligence

Abstract

Background/Objectives: In the era of rapid digital transformation, database systems serve as a cornerstone course for computer science and data science programs. However, traditional pedagogical approaches often suffer from fragmented knowledge delivery, a pronounced disconnect between theoretical instruction and practical application, and insufficient cultivation of data-driven thinking among students. This study aims to address these challenges by redesigning the database systems curriculum through the integration of artificial intelligence technologies, with the overarching goal of cultivating students into competent future data analysis engineers. The reform also seeks to develop essential competencies including teamwork, analytical rigor, innovative problem-solving, and data-driven decision-making. Methods: The proposed approach moves beyond the conventional teaching model that relies predominantly on theoretical lectures followed by syntax-oriented exercises. Instead, it incorporates a systematic analysis of student learning profiles to inform targeted revisions to instructional content. Innovative teaching methods are introduced, including AI-assisted query optimization exercises, project-based collaborative learning, and real-world case studies that bridge the gap between academic concepts and industry practices. Results: Implementation of the redesigned curriculum in actual classroom settings has demonstrated significant improvements in student engagement, practical skill acquisition, and overall learning outcomes. The approach has been validated through both formative and summative assessments, providing a replicable and valuable model for curriculum innovation across related disciplines. Conclusions: This study has established a practical, effective, and sustainable pathway for modernizing database systems education, offering actionable insights for educators seeking to integrate artificial intelligence into their teaching practices.