课程团队依托大数据技术对先修课程学习数据进行分析，构建出消极型、勤奋型、中规中矩型、三好学生型4类学生画像，挖掘不同画像类型学生在中医临床护理学课程中的教学问题，以此开展精准教学改革。课前精准划分学习小组、诊断学情、定制目标，课中精准互动、设计三类进阶式案例，课后设计分类学习任务，满足不同画像类型学生的学习需求。实践发现，学生画像作为精准教学的数据中枢，将学生学习数据转化为教师教学策略调整的有效依据，有助于破解教学中规模化与个性化的矛盾，促使教学范式从主观经验主义向客观数据主义转变。

Relied on big data technology to analyze the learning data of prerequisite courses，the curriculum team developed four types of student portraits，namely the passive type，the diligent type，the moderately performing type，and the all-round excellent student type. Through identifying genuine teaching issues faced by students of different portraits in the Clinical Nursing of TCM，the team initiated precision teaching reforms tailored to these students’ profiles. Before the class，the learning groups were precisely divided，students’ academic conditions were accurately diagnosed，and customized learning objectives were set. During class，precise interactions were conducted，and three types of progressive cases were designed. After class，classified learning tasks was designed to meet the learning needs of students with different portrait types. The practice has found that，as the data hub of precision teaching，student portraits can transform students’ learning data into an effective basis for teachers to adjust their teaching strategies. This is helpful for solving the contradiction between large-scale teaching and personalized teaching，and promoting the transformation of the teaching paradigm from subjective empiricism to objective dataism.