大学生在线学习评测的研究

Research on Online Learning Evaluation for College Students

高等院校在人才培养过程越来越多的使用网络辅助或独立进行课程教学,学生大量参与了在线学习,但是由于在线学习中师生时空分离的特性,教师很难实时掌握学生学习的参与程度、实时学习情况和知识掌握程度。以《信息与网络安全技术课程》为例,爬取学生在线学习数据和华为应用商城教育类软件评价数据,按照学生投入分数计算方法进行数据分析,综合使用Python语言、Flask框架和SQLite数据库等技术,把分析结果进行可视化展示。教师根据分析结果,了解学生的学习情况并对存在问题的学生及时干预。学生通过系统反馈的学习数据和班级整体学习情况,及时调整自己的学习状态。

Higher education institutions are increasingly using online assistance or independent course teaching in the process of talent cultivation. Students are heavily involved in online learning, but due to the spatiotemporal separation between teachers and students in online learning, it is difficult for teachers to real-time grasp the degree of participation, learning situation, and knowledge mastery of students in the learning process. Taking “Information and Network Security Technology Course” as an example, we crawled student online learning data and Huawei Application Mall education software evaluation data, analyzed the data using the student input score calculation method, and used technologies such as Python language, Flask framework, and SQLite database to visualize the analysis results. Based on the analysis results, teachers should understand students' learning situation and intervene in a timely manner for students with problems. Students adjust their learning status in a timely manner based on the learning data provided by the system and the overall learning situation of the class.