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

摘要： 文章以洛阳职业技术学院新能源汽车技术专业为例，探索高职学业评价改革路径，旨 在提升人才培养质量。通过超星学习通采集学习行为数据并结合过程性与总结性评价，构建 “目标设定－过程跟踪－自我反思－综合评定”闭环，并开展为期两学期的试点工作。实践 结果表明：课堂参与度由改革前的 65.2%±12.1%提升至 81.3%±10.5%，提升幅度为 16.1%， 作业按时提交率由改革前的 78.4%±9.3%提升至 92.6 %±6.7%，提高 14.2 个百分点，实训项目 中学生独立完成率由改前 60.5%±15.4%提升至改后 79.8%±12.2%，学生平均分由（68.7±8.2） 分提高到（81.5±7.4）分，提升了 12.8 分（相对提升约 18.6%），学生对学业评价体系的满意 度平均分由（3.2±0.6）分提升至（4.1±0.5）分。此外，学生满意度、用人单位岗位匹配度 等指标也呈上升趋势。该模式能有效激发学生学习主动性与实践能力，为高职汽车类院校构 建智能化、个性化学业评价体系提供可借鉴经验。

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