Abstract:
The need for wide use of Mobile learning environments o as an educational technology
component in undergraduate education, has particularly arisen at present due to its vast
potential for expansion. Use of online methods for education started to expand exponentially
with the spread of devastating COVID19 since early 2020. Due to countrywide or regional
wise long-term lockdowns, people are compelled to use online methods, particularly for
learning. „Mobile learning though makes it possible for students to learn and share their
thoughts and views among each other as well as the academics can disseminate their
knowledge with the student‟s community with the support of internet and technology
improvements‟, it is evident that the solution is still suboptimal when compared to traditional
teaching systems. Both the study behaviour of the students and the existing study patterns of
Learning Management Systems (LMSs) in undergraduate studies seem to be responsible for
this status of affairs. The objective of the study was to examine the present m-Learning study
behaviour of undergraduate students and with the help of the outcome, to develop an
improved LMS. Back-end data of the LMS for the period of five years was analysed to
understand the factors that are under performing, and to use such findings to develop a better
performing LMS. The study used Data Mining techniques in respect of the Database of the
undergraduate LMS of the Faculty of Medicine, University of Colombo to test the research
hypothesis. Various data mining algorithms, such as K Mean Clustering algorithm,
Correlation Algorithm, Association algorithm etc have been used. The study found that there
does exist only a mix of positive, negative and absence of relations between students‟ strong
study behaviour and favourable study patterns, in the use of LMS. Distributions are not equal
both among and in-between of attributes with LMS and therefore students are unable to
realize full technical potential of the LMS delivery. LMS is acting as a limitation that keeps
the online option at a suboptimal level. Students do not show a strong study behaviour and
favourable study patterns in the use of LMS.
The conclusion is that there is a wide gap between the actual outcome and the full potential
of the LMS. This pattern and behaviour indicates that the students have neither attempted
questions or examinations nor use the benefits of an integration with social media via LMS
mode. There are unutilized potential areas which can be used or utility can be enhanced
without any technical expansion by only giving more opportunities to students. Findings
provide technical solutions to develop the LMS comprehensively to meet today‟s online
learning needs with further investments.
Citation:
Bandara, H.M.W.G.P.R.A. (2021). Effectiveness of mobile learning platforms for study program delivery: a clustering approach to analyse student learning patterns and behaviour [Master's theses, University of Moratuwa]. Institutional Repository University of Moratuwa. http://dl.lib.uom.lk/handle/123/20420