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Denis Zhidkikh; Ville Heilala; Charlotte Van Petegem; Peter Dawyndt; Miitta Jarvinen; Sami Viitanen; Bram De Wever; Bart Mesuere; Vesa Lappalainen; Lauri Kettunen; Raija Hämäläinen – Journal of Learning Analytics, 2024
Predictive learning analytics has been widely explored in educational research to improve student retention and academic success in an introductory programming course in computer science (CS1). General-purpose and interpretable dropout predictions still pose a challenge. Our study aims to reproduce and extend the data analysis of a privacy-first…
Descriptors: Learning Analytics, Prediction, School Holding Power, Academic Achievement
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Gupta, Shivangi; Sabitha, A. Sai – Education and Information Technologies, 2019
Aimed at a massive outreach and open access education, Massive Open Online Courses (MOOC) has evolved incredibly engaging millions of learners' over the years. These courses provide an opportunity for learning analytics with respect to the diversity in learning activity. Inspite of its growth, high dropout rate of the learners', it is examined to…
Descriptors: Retention (Psychology), Online Courses, Learner Engagement, Electronic Learning
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Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals