{"title":"Deep E-School-Nurse for Personalized Health-Centered E-Learning Administration","authors":"Tannaz Karimi, Babak Majidi, M. T. Manzuri","doi":"10.1109/ICELET46946.2019.9091668","DOIUrl":null,"url":null,"abstract":"The increase in obesity in students due to lack of physical activities and having unhealthy diets is reaching dangerous levels. E-learning environments are gradually replacing traditional educational institutions. The health issues resulting from students’ lack of activity will increase with popularity of e-learning courses. Therefore, considering health issues in designing the e-learning environment is critical. Machine learning algorithms are able to diagnose many health issues automatically. In this paper, a machine learning based e-school-nurse which can take the role of the traditional human school nurse in the e-learning environment is proposed. The proposed enurse can automatically diagnose health problems of students and design a personalized health centered e-learning curriculum for them. As a case study, the deep neural networks are used for automatic profiling of students with diabetes. Based on the student diabetes profile a personalized curriculum is designed for the students which includes physical activity and a healthy diet at appropriate intervals during the study. The proposed e-school-nurse can help students to have a healthier e-learning experience.","PeriodicalId":278081,"journal":{"name":"2019 13th Iranian and 7th National Conference on e-Learning and e-Teaching (ICeLeT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 13th Iranian and 7th National Conference on e-Learning and e-Teaching (ICeLeT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICELET46946.2019.9091668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
The increase in obesity in students due to lack of physical activities and having unhealthy diets is reaching dangerous levels. E-learning environments are gradually replacing traditional educational institutions. The health issues resulting from students’ lack of activity will increase with popularity of e-learning courses. Therefore, considering health issues in designing the e-learning environment is critical. Machine learning algorithms are able to diagnose many health issues automatically. In this paper, a machine learning based e-school-nurse which can take the role of the traditional human school nurse in the e-learning environment is proposed. The proposed enurse can automatically diagnose health problems of students and design a personalized health centered e-learning curriculum for them. As a case study, the deep neural networks are used for automatic profiling of students with diabetes. Based on the student diabetes profile a personalized curriculum is designed for the students which includes physical activity and a healthy diet at appropriate intervals during the study. The proposed e-school-nurse can help students to have a healthier e-learning experience.