Kousuke Mouri, Fumiya Okubo, Atsushi Shimada, H. Ogata
{"title":"Bayesian Network for Predicting Students' Final Grade Using e-Book Logs in University Education","authors":"Kousuke Mouri, Fumiya Okubo, Atsushi Shimada, H. Ogata","doi":"10.1109/ICALT.2016.27","DOIUrl":null,"url":null,"abstract":"This paper describes visualization and analysis methods using educational big data collected by research project at Kyushu University in Japan. The project uses an e-book system called BookLooper, Moodle, and Mahara. Logs for this analytics were collected from 99 first-year students in an information science course at Kyushu University. The number of logs are collected approximately 330,000, and this paper visualize and analyze the collected logs. The purpose of this study is to predict students' final grade and to profile visualization and analysis results. The prediction of this study shows that it leads to discoveries of students who fail to make the grade.","PeriodicalId":188900,"journal":{"name":"2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 16th International Conference on Advanced Learning Technologies (ICALT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT.2016.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 30
Abstract
This paper describes visualization and analysis methods using educational big data collected by research project at Kyushu University in Japan. The project uses an e-book system called BookLooper, Moodle, and Mahara. Logs for this analytics were collected from 99 first-year students in an information science course at Kyushu University. The number of logs are collected approximately 330,000, and this paper visualize and analyze the collected logs. The purpose of this study is to predict students' final grade and to profile visualization and analysis results. The prediction of this study shows that it leads to discoveries of students who fail to make the grade.
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