{"title":"Prospects and Challenges of Equipping Mathematics Tutoring Systems with Personalized Learning Strategies","authors":"Xinguo Yu, Jing Xia, Weina Cheng","doi":"10.1109/IEIR56323.2022.10050082","DOIUrl":null,"url":null,"abstract":"Equipping mathematics tutoring systems with per-sonalized learning strategies is a crucial task in providing personalized learning service. The advance of intelligent educational technology sheds a touchable prospect for practicing personalized learning model. The cloud-based education systems have already provided the platform that can support the scale personalized service. The solving algorithms in mathematics is going to support the personalized learning for mathematics. The educational robots have potential to provide the personalized interactions with learners. However, we still face the challenges in building personalized learning strategies for mathematics. The challenges lie in that we still have difficulty in acquiring the trust learner profile, building strategies of learning mathematics, and finding the relations between profiles and strategies.","PeriodicalId":183709,"journal":{"name":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Intelligent Education and Intelligent Research (IEIR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEIR56323.2022.10050082","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
Equipping mathematics tutoring systems with per-sonalized learning strategies is a crucial task in providing personalized learning service. The advance of intelligent educational technology sheds a touchable prospect for practicing personalized learning model. The cloud-based education systems have already provided the platform that can support the scale personalized service. The solving algorithms in mathematics is going to support the personalized learning for mathematics. The educational robots have potential to provide the personalized interactions with learners. However, we still face the challenges in building personalized learning strategies for mathematics. The challenges lie in that we still have difficulty in acquiring the trust learner profile, building strategies of learning mathematics, and finding the relations between profiles and strategies.