This study explores teaching reform strategies for the Big Data and Data Mining course in response to the requirements of New Engineering Education Initiatives. The course currently faces challenges such as rigid teaching models, limited practical environments, and an underdeveloped assessment system. To address these issues, several reform strategies are proposed. First, a blended teaching approach that integrates online and offline instruction through Massive Open Online Courses (MOOC) and classroom teaching is implemented. Secondly, diverse teaching methods, including case-based instruction and innovative project-based learning, are adopted to enhance student engagement, foster active learning, and improve hands-on and problem-solving skills. Finally, the assessment system is restructured to incorporate both formative and summative evaluations, ensuring a more comprehensive assessment of students’ theoretical knowledge and practical abilities. The results of the reform demonstrate significant improvements, effectively cultivating high-quality professionals with innovative thinking, practical competencies, and engineering literacy in the field of big data.
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