The Intervention of Moral Education Personalized Network Teaching Based on Information Technology

Yi Ran
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Abstract

With the deepening of the new curriculum reform, the democratic equality between teachers and students, the need of students' personality development, the individualized classroom teaching of Ideological and moral character has become a very worthy of serious research. In the information explosion, the impact of information technology on educational reform is becoming more and more profound. It has become a national strategy to promote education modernization with information technology. The purpose of this paper is to build a personalized network teaching platform for moral education and promote the moral education information teaching. Based on the demand of moral education individualization in the view of big data, this paper constructs and realizes the moral education network teaching platform with personalized recommendation function. The whole system architecture is designed, the technical feasibility and data feasibility of realizing the system function are analyzed, and the difficulties of developing the system are determined. Learn and master various technical development schemes such as LDA document theme model and recommendation algorithm. According to the requirement analysis, the system function module is realized, the function and performance test of the system are completed, and the test results are analyzed. When the number of users is within 3000, the CPU utilization rate changes slowly, the utilization rate is within 10%, but more than 3000 people, the CPU utilization rate increases rapidly, and the performance of the system is obviously decreased. Because the limit of the number of users is 1000, the system can still meet the needs well.
基于信息技术的个性化网络教学对德育的干预
随着新课程改革的不断深入,师生民主平等、学生个性发展的需要,思想品德个性化课堂教学已成为一个非常值得认真研究的问题。在信息爆炸的今天,信息技术对教育改革的影响越来越深刻。以信息技术推进教育现代化已成为国家战略。本文旨在构建德育个性化网络教学平台,推进德育信息化教学。基于大数据视域下的德育个性化需求,本文构建并实现了具有个性化推荐功能的德育网络教学平台。设计了整个系统架构,分析了实现系统功能的技术可行性和数据可行性,确定了系统开发的难点。学习并掌握 LDA 文档主题模型、推荐算法等多种技术开发方案。根据需求分析,实现系统功能模块,完成系统的功能和性能测试,并对测试结果进行分析。当用户数量在 3000 人以内时,CPU 利用率变化缓慢,利用率在 10%以内,但超过 3000 人后,CPU 利用率迅速上升,系统性能明显下降。由于用户数限制为 1000 人,因此系统仍能很好地满足需要。
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