A. Seitova, D. Issabayeva, L. Rakhimzhanova, U. Abdigapbarova, S. Issabayeva
{"title":"Evaluation of Independent Work of Students in Distance Learning Based on Eutagogy","authors":"A. Seitova, D. Issabayeva, L. Rakhimzhanova, U. Abdigapbarova, S. Issabayeva","doi":"10.1109/SIST54437.2022.9945719","DOIUrl":null,"url":null,"abstract":"This study aims to identify the impact of distance learning and eutagogy theory on enhancing student independent work based on the digital footprint. In order to assess the time and quality of independent work based on the students' digital footprint, a set of criteria and indicators based on eutagogy is determined, quantitative indicators are selected, and a methodology is proposed that can be used to assess the progress of each student. The article includes algorithms for assessing the success of independent work based on empirical data and learning analytics. The developed algorithms make it possible to interpret digital footprints of the performance of independent work in distance learning, evaluate its success and adjust the student's learning trajectory.","PeriodicalId":207613,"journal":{"name":"2022 International Conference on Smart Information Systems and Technologies (SIST)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Smart Information Systems and Technologies (SIST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SIST54437.2022.9945719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This study aims to identify the impact of distance learning and eutagogy theory on enhancing student independent work based on the digital footprint. In order to assess the time and quality of independent work based on the students' digital footprint, a set of criteria and indicators based on eutagogy is determined, quantitative indicators are selected, and a methodology is proposed that can be used to assess the progress of each student. The article includes algorithms for assessing the success of independent work based on empirical data and learning analytics. The developed algorithms make it possible to interpret digital footprints of the performance of independent work in distance learning, evaluate its success and adjust the student's learning trajectory.