In this paper, we explore student dropout behavior in Massive Open Online Courses(MOOC). We use as a case study a recent Coursera class from which we develop a survival model that allows us to measure the influence of factors extracted from that data on student dropout rate. Specifically we explore factors related to student behavior and social positioning within discussion forums using standar...

E-learning has been developing rapidly in recent years; however, as the student number and market scale are growing fast, there is also a growing concern over the issue of high dropout rates in e-learning. High dropout rate not only harms both education institutions and students, but also jeopardises the development of e-learning systems. Understanding the behavioural mechanism of students’ con...

The present case study describes the results of the educational data mining aimed at predicting the undergraduate courses of computer science (BCA and B.Tech.) students’ instant dropout or after first semester. For this purpose, the preliminary data of 220 students collected randomly in prescheduled format on personal interview to find out dropout rates and dropout reasons. The simple and intui...

Deep learning is a trending topic widely studied by researchers due to increase in the abundance of data and getting meaningful results with them. Convolutional Neural Networks (CNN) is one of the most popular architectures used in deep learning. Binarized Neural Network (BNN) is also a neural network which consists of binary weights and activations. Neural Networks has large number of paramete...

BACKGROUND Patient dropout from treatment can lead to a deterioration in clinical condition, thereby increasing the need for more intensive therapy that incurs substantial social and economic losses. The aim of this study was to identify factors related to psychiatric patient dropout at a university outpatient clinic in Japan. METHODS We retrospectively examined the medical charts of new psyc...

PURPOSE Despite the importance of selecting students whom are capable for medical education and to become a good doctor, not enough studies have been done in the category. This study focused on analysing the medical students' academic performance (grade point average, GPA) differences, flunk and dropout rates by admission types. METHODS From 2004 to 2010, we gathered 369 Konyang University Co...

This study examines dropout incidence, moment of dropout, and switching behavior in organized exercise programs for seniors in the Netherlands, as determined in a prospective cohort study (with baseline measurements at the start of the exercise program and follow-up after 6 months; N = 1,725, response rate 73%). Participants were community-living individuals 50+ who participated in different fo...

The big breakthrough on the ImageNet challenge in 2012 was partially due to the ‘dropout’ technique used to avoid overfitting. Here, we introduce a new approach called ‘Spectral Dropout’ to improve the generalization ability of deep neural networks. We cast the proposed approach in the form of regular Convolutional Neural Network (CNN) weight layers using a decorrelation transform with fixed ba...

OBJECTIVE To investigate mental health dropout rates in secondary care and to identify possible associations between this variable and social, demographic, psychopathologic, and health care process-related variables. METHOD This prospective, observational study included 994 patients referred to a secondary service by four primary care units and evaluated by a specialist mental health team bet...

Massive open online courses (MOOCs) have received wide publicity and many institutions have invested considerable effort in developing, promoting and delivering such courses. However, there are still many unresolved questions relating to MOOCs and their effectiveness. One of the major recurring issues raised in both academic literature and the popular press is the consistently high dropout rate...