关键词: 高职教育；新能源汽车专业；学业评价；个性化学习；大数据分析；过程性评价

Abstract: This paper takes the New Energy Vehicle Technology major at Luoyang Vocational and Technical College as a case study. Student learning behavior data are collected via the SuperStar learning platform. Formative and summative assessments are integrated to evaluate classroom performance, project assignments, internships, and competency development. A closed-loop system of "goal setting-process tracking-self-reflection-comprehensive evaluation" is established. Personalized learning pathways and career guidance are provided to students. Practical results indicate:Classroom participation increased from 65.2%±12.1%before the reform to 81.3% ±10.5%, representing a 16.1% improvement. The homework submission rate rose from 78.4%±9.3% before the reform to 92.6%±6.7%, an increase of 14.2 percentage points. The rate of students independently completing practical training projects increased from 60.5%±15.4% to 79.8%±12.2%. The average student score increased from (68.7±8.2) points to (81.5±7.4) points, representing a 12.8 points (an increase of approximately 18.6%). The average satisfaction score for the academic assessment system rose from (3.2±0.6) points to (4.1±0.5) points. Additionally, indicators such as student satisfaction and employer job-fit alignment have shown an upward trend. This model effectively stimulates students' initiative in learning and practical skills, offering valuable insights for vocational automotive institutions to establish intelligent, personalized academic assessment systems.

Key words: higher vocational education; new energy vehicle major;academic assessment; personalized learning; big data analysis; formative assessment