Alin ZAMFIROIU1,2*, Ramesh C. SHARMA3, Diana CONSTANTINESCU2, Mădălina PANĂ2, Cristian TOMA2
1 National Institute for Research and Development in Informatics, 8-10 Mareșal Alexandru Averescu Avenue,
District 1, 011455, Bucharest, Romania Romania
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2 The Bucharest University of Economic Studies, 2-10 Căderea Bastiliei Street,
District 1, 010615, Bucharest, Romania
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3 Dr. B. R. Ambedkar University Delhi, Campus, AUD, Lothian Rd, Kashmere Gate, New Delhi, 110006, India
Abstract: Online education is one of the fastest emerging markets globally. There is a variety of tools, technologies and platforms, which augment learning in the online environments. Moodle and Sakai are probably the most popular open-source learning management systems (LMS) around the world, although there are alternative professional solutions such as TalentLMS or other platforms. Student interaction is one of the success factors of effective online teaching and learning. It is important to understand how students behave in an online environment. This provides good feedback to the syllabus developers and instructors, in order to examine what should be improved. The learning management systems provide a good way for analyzing learners’ behavior through log reports. The LMS records all kinds of interactions by all users. These data are processed using learning analytics, in order to obtain a good picture of the progress achieved by the students during the lectures and the laboratories and of the manner in which the professors manage the students’ learning curves. This paper explains the use of learning analytics in examining learners’ engagement, interaction and behavior in an online environment. The results revealed interesting findings on how the assessment should be organized, in order to find maximum learning attainment.
Keywords: Assessment, Evaluation, e-Learning, Learning analytics, MOODLE, Learning management system, Feedback.
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Alin ZAMFIROIU, Ramesh C. SHARMA, Diana CONSTANTINESCU, Mădălina PANĂ, Cristian TOMA, Using Learning Analytics for Analyzing Students’ Behavior in Online Learning, Studies in Informatics and Control, ISSN 1220-1766, vol. 31(3), pp. 63-74, 2022. https://doi.org/10.24846/v31i3y202206