Mathematical modeling and mining real-world Big education datasets with application to curriculum mapping

Kah Phooi Seng; Fenglu Ge; Li-minn Ang

doi:10.3934/mbe.2021225

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Mathematical modeling and mining real-world Big education datasets with application to curriculum mapping

Journal article

Open access

Peer reviewed

Mathematical modeling and mining real-world Big education datasets with application to curriculum mapping

Kah Phooi Seng, Fenglu Ge and Li-minn Ang

Mathematical Biosciences and Engineering, Vol.18(4), pp.4450-4460

2021

DOI: https://doi.org/10.3934/mbe.2021225

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Abstract

graph learning

learning analytics

curriculum mapping

learning technologies

Big data

This paper proposes an approach for modeling and mining curriculum Big data from real-world education datasets crawled online from university websites in Australia. It addresses the scenario to give a student a study plan to complete a course by accumulating credits on top of subjects he or she has completed. One challenge to be addressed is that subjects with similar titles from different universities may put barriers for setting up a reasonable, time-saving learning path because the student may be unable to distinguish them before an intensive research on all subjects related to the degree from the universities. We used concept graph-based learning techniques and discuss data representations and techniques which are more suited for large datasets. We created ground truth of subjects relations and subject's description with Bag of Words representations based on natural language processing. The generated ground truth was used to train a model, which summarizes a subject network and a concepts graph, where the concepts are automatically extracted from the subject descriptions across all the universities. The practical challenges to collect and extract the data from the university websites are also discussed in the paper. The work was validated on nineteen real-world education datasets crawled online from university websites in Australia and showed good performance.

Details

Title: Mathematical modeling and mining real-world Big education datasets with application to curriculum mapping
Authors: Kah Phooi Seng (Author) - UNSW Australia
Fenglu Ge (Author) - Pacific Telecom & Navigation Ltd
Li-minn Ang (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
Publication details: Mathematical Biosciences and Engineering, Vol.18(4), pp.4450-4460
Publisher: AIMS Press
Date published: 2021
DOI: 10.3934/mbe.2021225
ISSN: 1551-0018
Copyright note: © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
Organisation Unit: University of the Sunshine Coast, Queensland; School of Science, Technology and Engineering; Engage Research Lab
Language: English
Record Identifier: 99548408102621
Output Type: Journal article

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Collaboration types: Domestic collaboration; International collaboration
Web Of Science research areas: Mathematical & Computational Biology