Exploration of Civics Teaching Mode in Colleges and Universities Relying on Digital Classroom Platforms

IF 3.1 Q1 Mathematics
Xueying Dong, Guizhen Liu
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Abstract

The digital teaching model of Civics at the current stage still has deficiencies and does not achieve the expected effect. This paper utilizes data analysis and mining methods starting from the digital classroom platform to assess students’ knowledge and skill mastery through the CDA static cognitive analysis model. Then, students’ learning behaviors were analyzed using K-Means, and an evaluation model of interactive behavioral characteristics was constructed to analyze students’ Civics learning characteristics in combination with the above three aspects. Relying on the digital classroom platform, a corresponding teaching model for Civics in colleges and universities was developed. Our analysis of the impact of teachers’ and students’ interaction behaviors in Civics teaching and the realistic results of the Civics teaching model designed in this study is aided by the selection of empirical samples. The results show that the optimized students’ interactive behavior rate of Civics learning is more than 50%, and the interaction time increases to 19 minutes, which has a significant improvement effect. Analyzing the digital classroom teaching model of Civics, 28 students in Case 2 in the course comparison had greater interest in Civics learning, meanwhile, only 6 students had low interest in Civics learning, and the digital teaching model of Civics effectively enhanced students’ knowledge and literacy.
依托数字化课堂平台的高校思政课教学模式探索
现阶段思政课数字化教学模式仍存在不足,没有达到预期效果。本文利用数据分析与挖掘方法,从数字化课堂平台入手,通过CDA静态认知分析模型,对学生的知识与技能掌握情况进行评价。然后,利用K-Means对学生的学习行为进行分析,结合以上三个方面构建了互动行为特征评价模型,分析学生的思政学习特征。依托数字课堂平台,开发了相应的高校思政课教学模式。通过实证样本的选取,我们分析了思政课教学中师生互动行为的影响以及本研究设计的思政课教学模式的现实效果。结果显示,优化后的学生思政学习互动行为率超过50%,互动时间增加到19分钟,提升效果显著。分析思政课数字化课堂教学模式,课程对比中案例2有28名学生对思政课学习兴趣较大,同时只有6名学生对思政课学习兴趣较低,思政课数字化教学模式有效提升了学生的知识素养。
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来源期刊
Applied Mathematics and Nonlinear Sciences
Applied Mathematics and Nonlinear Sciences Engineering-Engineering (miscellaneous)
CiteScore
2.90
自引率
25.80%
发文量
203
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