Understanding Learner Behaviour in Online Courses through Learning Analytics

Raju, D. Thammi and Murthy, G. R. K. and Khade, S. B. and Padmaja, B. and Yashavanth, B. S. and Kumar, S. Ajay and Soam, S. K. and Srinivasarao, Ch. (2021) Understanding Learner Behaviour in Online Courses through Learning Analytics. Asian Journal of Agricultural Extension, Economics & Sociology (39): 10. pp. 381-390. ISSN 2320-7027

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Abstract

Building an effective online course requires an understanding of learning analytics. The study assumes significance in the COVID 19 pandemic situation as there is a sudden surge in online courses. Analysis of the online course using the data generated from the Moodle Learning Management System (LMS), Google Forms and Google Analytics was carried out to understand the tenants of an effective online course. About 515 learners participated in the initial pre-training needs & expectations’ survey and 472 learners gave feedback at the end, apart from the real-time data generated from LMS and Google Analytics during the course period. This case study analysed online learning behaviour and the supporting learning environment and suggest critical factors to be at the centre stage in the design and development of online courses; leads to the improved online learning experience and thus the quality of education. User needs, quality of resources and effectiveness of online courses are equally important in taking further online courses.

Item Type: Article
Subjects: Asian STM > Agricultural and Food Science
Depositing User: Managing Editor
Date Deposited: 24 Mar 2023 07:17
Last Modified: 04 Apr 2024 09:13
URI: http://journal.send2sub.com/id/eprint/1062

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