{"title":"电子学习中学生评价的数据挖掘研究","authors":"Wenty Dwi Yuniarti, E. Winarko, Aina Musdholifah","doi":"10.1109/ICIC50835.2020.9288533","DOIUrl":null,"url":null,"abstract":"The diffusion of technology in learning is increasingly massive, marked by the rapid transfer of learning into online environments such as e-Learning. Assessment is an important element of education. Assessment in e-Learning requires methods to be efficient and effective. Data mining is a method of analysis to reveal and recognize hidden patterns in educational databases. Deepening data mining for assessment in e-Learning is both an interesting and a challenge for teachers and institutions to find the right method and make a significant contribution in this area. Therefore, we conducted a literature review and presented state-of-the-art data mining for student assessment in e-Learning from relevant literature publishing from 2016 to 2020. We specifically focus on student assessment research in e-Learning, namely the scope of utilizing data mining, a comparison of several methods, and an analysis of several aspects related to assessment. This study also sheds light on future research directions. We identify the process mining approach as a data mining sub-discipline for the current trend assessment.","PeriodicalId":413610,"journal":{"name":"2020 Fifth International Conference on Informatics and Computing (ICIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Data Mining for Student Assessment in e-Leaming: A Survey\",\"authors\":\"Wenty Dwi Yuniarti, E. Winarko, Aina Musdholifah\",\"doi\":\"10.1109/ICIC50835.2020.9288533\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The diffusion of technology in learning is increasingly massive, marked by the rapid transfer of learning into online environments such as e-Learning. Assessment is an important element of education. Assessment in e-Learning requires methods to be efficient and effective. Data mining is a method of analysis to reveal and recognize hidden patterns in educational databases. Deepening data mining for assessment in e-Learning is both an interesting and a challenge for teachers and institutions to find the right method and make a significant contribution in this area. Therefore, we conducted a literature review and presented state-of-the-art data mining for student assessment in e-Learning from relevant literature publishing from 2016 to 2020. We specifically focus on student assessment research in e-Learning, namely the scope of utilizing data mining, a comparison of several methods, and an analysis of several aspects related to assessment. This study also sheds light on future research directions. We identify the process mining approach as a data mining sub-discipline for the current trend assessment.\",\"PeriodicalId\":413610,\"journal\":{\"name\":\"2020 Fifth International Conference on Informatics and Computing (ICIC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 Fifth International Conference on Informatics and Computing (ICIC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIC50835.2020.9288533\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Fifth International Conference on Informatics and Computing (ICIC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIC50835.2020.9288533","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Data Mining for Student Assessment in e-Leaming: A Survey
The diffusion of technology in learning is increasingly massive, marked by the rapid transfer of learning into online environments such as e-Learning. Assessment is an important element of education. Assessment in e-Learning requires methods to be efficient and effective. Data mining is a method of analysis to reveal and recognize hidden patterns in educational databases. Deepening data mining for assessment in e-Learning is both an interesting and a challenge for teachers and institutions to find the right method and make a significant contribution in this area. Therefore, we conducted a literature review and presented state-of-the-art data mining for student assessment in e-Learning from relevant literature publishing from 2016 to 2020. We specifically focus on student assessment research in e-Learning, namely the scope of utilizing data mining, a comparison of several methods, and an analysis of several aspects related to assessment. This study also sheds light on future research directions. We identify the process mining approach as a data mining sub-discipline for the current trend assessment.