The use of analytics in analyzing student engagement in e-learning / Mohd Hafriz Nural Azhan, Md Yazid Mohd Saman and Noraida Ali
E-Learning web applications allow users to interact directly with any web platforms together with other users. Some learning applications and their usage in an e-learning platform have not been fully analyzed for student engagement in their learning activities. Big data is data collected in large qu...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
UiTM Press
2017
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| Online Access: | https://ir.uitm.edu.my/id/eprint/59661/1/59661.pdf https://ir.uitm.edu.my/id/eprint/59661/ https://journalined.uitm.edu.my/ |
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| Summary: | E-Learning web applications allow users to interact directly with any web platforms together with other users. Some learning applications and their usage in an e-learning platform have not been fully analyzed for student engagement in their learning activities. Big data is data collected in large quantities, be it in the form of structured or un-structured data. Big data can come from multiple sources. Nowadays, each application and equipment will have log data that is kept that can be translated into meaningful values. In e-Learning, each student activity will be logged and recorded. However, the raw data do not make much sense. Thus, to understand their value, analytic capabilities are highly needed. Analytics is a technology that is used to translate raw data into something more meaningful to users. Data that are being collected can be translated into data that is useful and valuable to users. This greatly depends on the translation process to statistics, computer programming and operations research in order to measure the performance of any web system. This paper reports the development of a system for the application of real-time analytics on the usage of e-learning in a tertiary institution. It includes the descriptions of the tools and statistics of the data collected by the e-learning system manager. All students’ access information such as geographic information, devices used, access times, courses and activities are collected. The development of a dashboard system called Nakhoda is also described in this paper. It is a course learning analytics platform that displays summarized learning data. |
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