The use of analytics in analyzing student engagement in e-Learning
Mohd Hafriz Nural Azhan1, Md Yazid Mohd Saman2, Noraida Ali3.
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. One finding is that
devices used to access the e-learning system such as Apple Ipad, Iphone,
Android-based and Symbian-based machines have shown to be the top four mobile devices that are actively used by students. The evidence from
this study suggests that the increasing use of mobile devices as a learning
tool has generated a positive response from e-learning users. As a tool,
analytics data can help lecturers to analyze their students’ behavior, which
can enhance pedagogical practices.
Affiliation:
- Universiti Malaysia Terengganu, Malaysia
- Universiti Malaysia Terengganu, Malaysia
- Universiti Malaysia Terengganu, Malaysia
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