目前中国的高校中开设了许多专业类别,每种专业类别下开设了许多的课程,在大学生群体中对于每门课程的认识程度、课程后对知识的理解程度没有一个明确、直观的呈现方式。构建大学生数据素养评价指标体系可以通过对大学生调查问卷、对授课老师或相关专家和学生的座谈内容来描绘出当前大学生对于当前学科认知程度的画像,同时通过对老师的授课经验与教材为对照归纳出每门课程的关键知识点构建专家语料库,并且基于计算机学科以代码为主,以专家语料库为参照,分别读取教材内代码或者实战中代码文件实现各个代码相关度的可视化呈现,以及所有代码中每个知识点的权重可以有个直观、可视化的呈现。构建大学生数据素养评价指标体系,对于老师可以帮助他们更加直观地看到教材当中每块知识点的权重从而更好地规划自己的授课重点;对于学生也可以在日常学习中不管是课堂还是自学都有一个更清晰、明了的学习规划路线提高学生对于知识点的吸收程度;对于学校也更清晰直观地看到每本教材的各知识点前后关联程度,从而更好地看到不同版本的教材对教学带来的差异。At present, many major categories have been offered in Chinese universities, and numerous courses are set up under each major category. However, among the college student group, there is no clear and intuitive way to present their understanding level of each course and the comprehension level of knowledge after taking the courses. Constructing an evaluation index system of college students’ data literacy can depict the current cognitive level of college students regarding the current disciplines through conducting questionnaires among college students and holding discussions with teaching instructors, relevant experts, and students. Meanwhile, by taking the teaching experience of instructors and textbooks as references, the key knowled