本科生数据挖掘和机器学习课程内容抽象难懂，传统的高等院校教材以讲授式为主。目前已提出大量的案例

式、项目式教学方法降低学习难度，但仍然存在抽象、不容易实施、缺少对算法原理剖析的缺点。提出在数据挖掘课程中采用

过程生成式启发教学，将学生的生活经验原型逐步形式化为严谨的数据挖掘算法，降低了学习难度，有助于学生对算法的深刻

理解，取得了更好的教学效果，在保证学科知识教学正确性与科学性的基础上，帮助学生学科素养与学科能力的生成。

The content of undergraduate Data Mining and Machine Learning course is abstract and difficult to understand. The traditional teaching materials of colleges and universities are mainly lecture teaching. At present, a large number of case-based and project-based teaching methods have been proposed to reduce the learning difficulty, but they still have the disadvantages of abstraction,

not easy to implement and lack of analysis of algorithm principles. In this paper, the process generation heuristic teaching is proposed for the first time in the Data Mining course, and the prototype of students' life experience is gradually formalized into a rigorous data mining algorithm, which reduces the learning difficulty, contributes to students' deep understanding of the algorithm and achieves better teaching results, on the basis of ensuring the correctness and scientificity of subject knowledge teaching, helps students generate subject literacy and subject ability.