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Direct linkLuna, J. M.; Fardoun, H. M.; Padillo, F.; Romero, C.; Ventura, S. – Interactive Learning Environments, 2022
The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…
Descriptors: Online Courses, Student Characteristics, Classification, Student Behavior
Mubarak, Ahmed Ali; Ahmed, Salah A. M.; Cao, Han – Interactive Learning Environments, 2023
In this study, we propose a MOOC Analytic Statistical Visual model (MOOC-ASV) to explore students' engagement in MOOC courses and predict their performance on the basis of their behaviors logged as big data in MOOC platforms. The model has multifunctions, which performs on visually analyzing learners' data by state-of-the-art techniques. The model…
Descriptors: MOOCs, Learner Engagement, Performance, Student Behavior
