Extraction and presentation of access and usage data from an e-learning platform (moodle): Design and development of a software application

Sykamiotis, G. and Charitopoulos, A. and Rangoussi, M. and Koulouriotis, D. (2017) Extraction and presentation of access and usage data from an e-learning platform (moodle): Design and development of a software application. In: 2017 IEEE Global Engineering Education Conference (EDUCON).

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Abstract

Educational data mining extracts and analyzes data from e-learning platform databases to address a series of questions regarding the quality and aiming at the optimization of the educational process. In this paper, a custom design software tool is presented. It is designed and developed to collect, extract and present data from an electronic course in the undergraduate curriculum of an Electronics Engineering Department, delivered through the moodle e-learning platform. Platform access and usage data by students are collected and presented in a user-friendly form, either in an individual or in a statistical basis, through a flexible modular user interface. The functionalities of this application allow for its smooth incorporation in a wider (educational) data mining framework, currently running in the same Department. The software application has been used in a pilot cycle in the spring semester of 2015-16; its functionalities have been subsequently adjusted and enriched according to the results. Formal evaluation is necessary, however, before putting it to regular use in the Department.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: computer aided instruction, custom design software tool, custom software development, data mining, Data mining, Databases, E-learning platform, educational data mining, Electronic learning, electronics engineering department, flexible modular user interface, Graphical user interfaces, moodle, moodle e-learning platform, optimisation, optimization, platform usage data, Servers, Software
Depositing User: Elizabeth Dalton
Date Deposited: 16 Dec 2019 23:40
Last Modified: 16 Dec 2019 23:40
URI: http://research.moodle.org/id/eprint/377

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