Deep E-School-Nurse for Personalized Health- Centered E-Learning Administration

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 healthissues 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 eschool- nurse which can take the role of the traditional human school nurse in the e-learning environment is proposed. The proposed e-nurse 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 elearning experience.

Keywords:

e-nurse , e-learning , e-school , deep neural network , diabetic retinopathy