{"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}
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.