Studies Suspension Prevention System of Distance University using Analysis of Learning Activity and Learner’s Big Data

Abstract

Due to the increase in withdrawals and temporary absences of students from changes in the external environment, distance learning universities are trying to establish various policies and increase the number of enrolled students, and at the same time, are trying to establish various policies and efforts to increase the enrollment. However, it is difficult to systematically diagnose the main cause of the interruption of students, and prior research efforts related to the problem of student suspension in distance learning universities have accumulated, since there are various reasons for the student suspensions. In the proposed distance university Studies Suspension Prevention System (SSPS), distance university students can use two types of learning analytics services. In order to analyze learning activities, we propose the asynchronous learning activity analysis module, and the synchronous learning activity analysis module. In the asynchronous analysis module and symchronous analysis module, quiz, LINE group chatting & discussion forum communication, and online lecture has a learning state score according to the lecturer’s directions. Learning activities in the learning management system have three kinds of learning states, passive activity state, negative activity state, and medium activity state. Learning activity states are used to predict the student learning state. In the proposed Student Support System, there are two types of learning support services connected to the smart learning portal server. One is the intelligent distance university chatbot service for personalized chatting and caring services. The other is push message services for alarm, warning, notices, and alerts, such as dashboard service.