Predictive Analysis of Sports Education Students’ Dropout in the Distance Learning Centre
Keywords:Dropout Reasons, Learning Analytics, Dropout, Distance Education, Personal Characteristic Data
The demand for e-Learning in distance education is growing rapidly due to the flexibility it offers in terms of time and location, facilitated by advancements in information and communication technology. This study aims to decrease the dropout rate among students in sports education and gain insight into the factors contributing to their discontinuation of studies. There is a need for research to identify and address the causes of the increasing dropout rate among learners at distance learning centres. The study collected data from 1,125 learners at an e-distance learning centre in Seoul. The findings were analysed using the partial least square – structural equation model (PLS-SEM). This study's implications are significant for preventing learner attrition. The study emphasises the importance of offering a variety of learning resources to enable learners to regularly access an e-learning platform and sustain their engagement in the learning process over a prolonged period of time. When developing education programmes for adult learners with diverse characteristics, it is essential to possess a comprehensive understanding of each learner's attributes beforehand. This will enable the implementation of suitable interventions and facilitate effective learning.