{"title":"A Review of Personalized Education Based on Machine Learning","authors":"Zhijia Li","doi":"10.61173/mggvmx39","DOIUrl":null,"url":null,"abstract":"Personalized education aims to meet the individual needs of each learner through tailored learning paths. Recent research has shown that the personalization of education and the online learning experience can be effectively enhanced through the use of supervised machine learning techniques and other machine learning approaches, which will not only provide personalized learning advice and resources but also highlight the importance of ensuring data security, algorithmic fairness, and transparency when implementing these techniques. In this paper, existing systematic reviews are integrated and updated through analyzing latest papers and classify their solution to the challenges in the educational field.","PeriodicalId":438278,"journal":{"name":"Science and Technology of Engineering, Chemistry and Environmental Protection","volume":"17 12","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science and Technology of Engineering, Chemistry and Environmental Protection","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.61173/mggvmx39","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Personalized education aims to meet the individual needs of each learner through tailored learning paths. Recent research has shown that the personalization of education and the online learning experience can be effectively enhanced through the use of supervised machine learning techniques and other machine learning approaches, which will not only provide personalized learning advice and resources but also highlight the importance of ensuring data security, algorithmic fairness, and transparency when implementing these techniques. In this paper, existing systematic reviews are integrated and updated through analyzing latest papers and classify their solution to the challenges in the educational field.