An innovative approach of progressive feedback via artificial neural networks

Singh, Shaveen and Jokhan, Anjeela D. and Sharma, Bibhya N. and Lal, Sunil P. (2012) An innovative approach of progressive feedback via artificial neural networks. Journal of Machine Learning Technologies, 3 (1). pp. 64-70. ISSN 2229-3981

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Abstract

This paper highlights the importance of Machine Learning (ML) as an e-planning tool to enhance learning and improve student performances. The ML algorithms can be deployed to intelligently examine the interactions and the activity reports in a Learning Management System (Moodle) to diagnose each student's academic progression. In this study, we group the behavior of students of an online course using the Self Organizing Map. The ML algorithm uses data obtained from the logs of Moodle to obtain a prediction map that permits rating each student’s ability to pass a course throughout the semester. Such swift e-planning mechanisms can be immensely helpful in identifying weak performances so that the coordinators, sponsors, parents and even the flagged students can take corrective measures, early in the semester. Within the scope of this work, the predictive attributes are further investigated and compared to reveal the degree of effectiveness of various activities in the online course.

Item Type:	Journal Article
Subjects:	L Education > LC Special aspects of education
Divisions:	Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences Faculty of Science, Technology and Environment (FSTE)
Depositing User:	Ms Shalni Sanjana
Date Deposited:	23 Jul 2012 10:02
Last Modified:	18 Jan 2017 23:40
URI:	https://repository.usp.ac.fj/id/eprint/4960

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