Abstract
Online learning is gaining increasing attention by researchers and educators since it makes students learn without being limited in time or space like traditional classrooms. Particularly, several researchers have also focused on gamifying the provided online courses to motivate and engage students. However, this type of learning still faces several challenges, including the difficulties for teachers to control the learning process and keep track of their students’ learning progress. Therefore, this study presents an ongoing project which is a gamified intelligent Moodle (iMoodle) that uses learning analytics to provide dashboard for teachers to control the learning process. It also aims to increase the students’ success rate with an early warning system for predicting at-risk students, as well as providing real-time interventions of supportive learning content as notifications. The beta version of iMoodle was tested for technical reliability in a public Tunisian university for three months and few bugs were reported by the teacher and had been fixed. The post-fact technique was also used to evaluate the accuracy of predicting at-risk students. The obtained result highlighted that iMoodle has a high accuracy rate which is almost 90%.
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Denden, M. et al. (2019). iMoodle: An Intelligent Gamified Moodle to Predict “at-risk” Students Using Learning Analytics Approaches. In: Tlili, A., Chang, M. (eds) Data Analytics Approaches in Educational Games and Gamification Systems. Smart Computing and Intelligence. Springer, Singapore. https://doi.org/10.1007/978-981-32-9335-9_6
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DOI: https://doi.org/10.1007/978-981-32-9335-9_6
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