基于教育数据挖掘和人工智能的学生成绩预测研究综述

Poonam S Pawar, Rajashre Jain
{"title":"基于教育数据挖掘和人工智能的学生成绩预测研究综述","authors":"Poonam S Pawar, Rajashre Jain","doi":"10.1109/temsmet53515.2021.9768773","DOIUrl":null,"url":null,"abstract":"Predicting student’s performance helps all stakeholders of education system to plan and take appropriate measures. Increase in the number of higher educational institutes and adoption to online and blended learning has enabled collection of large amounts of data. Data Mining and Artificial Intelligence tools can be successfully used on this data to predict student performance to provide required insights to the stakeholders. This paper focusses a systematic literature review on use of data mining and AI tools for Student’s Performance Prediction. Using Critical review of available literature authors have proposed a combinatorial model for student performance prediction using some techniques like Decision Tree, Random Forest, Genetic Algorithm, Artificial Neural Networks, etc.","PeriodicalId":170546,"journal":{"name":"2021 IEEE 2nd International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A review on Student Performance Prediction using Educational Data mining and Artificial Intelligence\",\"authors\":\"Poonam S Pawar, Rajashre Jain\",\"doi\":\"10.1109/temsmet53515.2021.9768773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Predicting student’s performance helps all stakeholders of education system to plan and take appropriate measures. Increase in the number of higher educational institutes and adoption to online and blended learning has enabled collection of large amounts of data. Data Mining and Artificial Intelligence tools can be successfully used on this data to predict student performance to provide required insights to the stakeholders. This paper focusses a systematic literature review on use of data mining and AI tools for Student’s Performance Prediction. Using Critical review of available literature authors have proposed a combinatorial model for student performance prediction using some techniques like Decision Tree, Random Forest, Genetic Algorithm, Artificial Neural Networks, etc.\",\"PeriodicalId\":170546,\"journal\":{\"name\":\"2021 IEEE 2nd International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 IEEE 2nd International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/temsmet53515.2021.9768773\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 2nd International Conference on Technology, Engineering, Management for Societal impact using Marketing, Entrepreneurship and Talent (TEMSMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/temsmet53515.2021.9768773","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

预测学生的表现有助于教育系统的所有利益相关者计划和采取适当的措施。高等教育机构数量的增加以及在线和混合学习的采用使大量数据的收集成为可能。数据挖掘和人工智能工具可以成功地利用这些数据来预测学生的表现,为利益相关者提供所需的见解。本文着重对数据挖掘和人工智能工具在学生成绩预测中的应用进行了系统的文献综述。通过对现有文献的批判性回顾,作者提出了一种利用决策树、随机森林、遗传算法、人工神经网络等技术进行学生成绩预测的组合模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A review on Student Performance Prediction using Educational Data mining and Artificial Intelligence
Predicting student’s performance helps all stakeholders of education system to plan and take appropriate measures. Increase in the number of higher educational institutes and adoption to online and blended learning has enabled collection of large amounts of data. Data Mining and Artificial Intelligence tools can be successfully used on this data to predict student performance to provide required insights to the stakeholders. This paper focusses a systematic literature review on use of data mining and AI tools for Student’s Performance Prediction. Using Critical review of available literature authors have proposed a combinatorial model for student performance prediction using some techniques like Decision Tree, Random Forest, Genetic Algorithm, Artificial Neural Networks, etc.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信