Development of Early Warning Systems to monitor e-learning progress. Issue 3 (March 2021)

• Record Type: Journal Article
• Authors: Arafiyah, R; Hasibuan, Z A; Santoso, H B
• Is Part Of: IOP conference series. Volume 1098:Issue 3(2021)
• Publication Date: 2021-03
• Subjects: Materials science -- Periodicals; 620.1105
• DOI: 10.1088/1757-899X/1098/3/032062
• Languages: English
• ISSNs: 1757-8981

Abstract

Abstract: Almost in every course, there are some successful learners and unsuccessful learners. There are many methods to reduce the number of unsuccessful learners. One of the methods is monitoring learning progress which can be used to recognize whether a learner will pass or not. In order to prevent unsuccessful learner, a modelling is needed on learning progress prediction. The modelling on learning progress prediction can be used as an early warning system (EWS) that can warn the learners throughout the learning process. Thus, it will decrease the number of unsuccessful learners and furthermore improve number of successful learners. This study aims to design the Early Warning System (EWS) in e-Learning. Decision making in EWS is a step-based function which is a prediction function of learning progress where the function consists of risk unsuccessful learner variables such as: the number of course accesses, files, URLs, attempted quizzes, and formative test scores. EWS will detect learner progress according to the progress and map the decision threshold.