A Prediction Strategy for Academic Records Based on Classification A within in Online Learning Environment
Wang Li1; Yuan Yaxing2
2019
会议名称19th IEEE International Conference on Advanced Learning Technologies (ICALT)
会议录名称IEEE
页码1-5
会议日期JUL 15-18, 2019
会议地点Maceio, BRAZIL
出版地NEW YORK
摘要With the development of the Internet and the big data technology, online education is growing vigorously. However, a large amount of data is generated in the online learning environment subsequently, in which the learning behavior data of the learner is very large and there is no good method to use these data. How to analyze and use these data and find the relationship between these data and learning effect has been a hot area of research in recent years. Online learning prediction strategy of academic records is proposed in the paper, which by calculating the correlation coefficient between data attributes and academic records firstly, and then using the correlation analysis to determine the impact of the study results, and finally using the classical classification algorithm of machine learning for classification prediction, explores the rules for online learning data based on the machine learning technology. In the end, the strategy has been proved to be effective in strengthening and improving the analysis and utilization of online learning data through experiments.
关键词Data Preprocessing Classification Algorithm Feature Extraction Neural Network
DOI10.1109/ICALT.2019.00007
收录类别CPCI-S
语种英语
WOS研究方向Computer Science ; Education & Educational Research
WOS类目Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Education & Educational Research
WOS记录号WOS:000539155500001
原始文献类型Proceedings Paper
引用统计
被引频次:84[WOS]   [WOS记录]     [WOS相关记录]
文献类型会议论文
条目标识符http://ir.library.ouchn.edu.cn/handle/39V7QQFX/167473
专题国家开放大学
通讯作者Wang Li
作者单位1.Open Univ China, Coll Comp Sci, Beijing, Peoples R China;
2.Open Univ China, Dept Informat, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Wang Li,Yuan Yaxing. A Prediction Strategy for Academic Records Based on Classification A within in Online Learning Environment[C]. NEW YORK,2019:1-5.
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