大数据技术在网络学科教育创新研究中的应用

Chengyi Huang, Wengxi Tan, Xin Yan, Yun Tan, Heyue Wan
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引用次数: 0

摘要

本文运用大数据技术,推动在线学科教育创新发展,提高学生自主学习效率,促进教育行业管理创新互动。在设计过程中,利用大数据技术对海量教育数据进行挖掘和分析,结合在线学科的学习需求,为在线学科教育系统的六个应用层面提供技术支持。通过DCF机制对教育数据进行文档转换,将同步时隙划分为安全时隙和保留时隙。然后,利用自适应推荐函数从行为数据中提取有价值的信息,进行个性化的学习资源推送;为验证大数据技术在在线学科教育创新体系中的实际应用效果,仿真分析结果表明,应用大数据技术后,教育系统的推荐资源偏好在86%以上,学科覆盖率为90.48%,考试成绩较c班提高17.5%。这说明大数据技术优化了在线学科教育的应用模式,可以为学生提供更优质的教育资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The application of big data technology in online subject education innovation research
This paper applies big data technology to promote the innovative development of online subject education and improve students' self-learning efficiency to promote innovative management interaction in the education industry. In the design process, big data technology is used to mine and analyze massive educational data, combine the learning needs of online subjects, and provide technical support for six application levels of the online subject education system. Document transformation of education data is performed through the DCF mechanism, and the synchronization time slot is divided into a safe time slot and a reservation time slot. Then, the adaptive recommendation function is used to extract valuable information from behavioral data for personalized learning resource pushing. To verify the practical application effect of big data technology in the online subject education innovation system, the simulation analysis results show that after applying big data technology, the recommended resources preference of the education system is above 86%, the subject coverage rate is 90.48%, and the performance of test scores is improved by 17.5% relative to Class C. This shows that big data technology optimizes the application mode of online subject education and can provide students with better-quality educational resources.
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