article

Mining Individual Learning Topics in Course Reviews Based on Author Topic Model

Authors:

Hercy N.H. ChengAuthors Info & Claims

International Journal of Distance Education Technologies, Volume 15, Issue 3

Pages 1 - 14

https://doi.org/10.4018/IJDET.2017070101

Published: 01 July 2017 Publication History

Abstract

Nowadays, Massive Open Online Courses MOOC has obtained a rapid development and drawn much attention from the areas of learning analytics and artificial intelligence. There are lots of unstructured data being generated in online reviews area. The learning behavioral data become more and more diverse, and they prompt the emergence of big data in education. To mine useful information from these data, we need to use educational data mining and learning analysis technique to study the learning feelings and discussed topics among learners. This paper aims to mine and analyze topic information hidden in the unstructured reviews data in MOOC, a novel author topic model based on an unsupervised learning idea is proposed to extract learning topics for the each learner. According to the experimental results, we will analyze and focuses of interests of learners, which facilitates further personalized course recommendation and improve the quality of online courses.

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Cited By

Zankadi HIdrissi ADaoudi NHilal I(2023)Identifying learners’ topical interests from social media content to enrich their course preferences in MOOCs using topic modeling and NLP techniquesEducation and Information Technologies10.1007/s10639-022-11373-128:5(5567-5584)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s10639-022-11373-1
Zhou XWu X(2022)Teaching Mode Based on Educational Big Data Mining and Digital TwinsComputational Intelligence and Neuroscience10.1155/2022/90719442022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/9071944

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Published In

cover image International Journal of Distance Education Technologies

International Journal of Distance Education Technologies Volume 15, Issue 3

July 2017

103 pages

ISSN:1539-3100

EISSN:1539-3119

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IGI Global

United States

Publication History

Published: 01 July 2017

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Cited By

Zankadi HIdrissi ADaoudi NHilal I(2023)Identifying learners’ topical interests from social media content to enrich their course preferences in MOOCs using topic modeling and NLP techniquesEducation and Information Technologies10.1007/s10639-022-11373-128:5(5567-5584)Online publication date: 1-May-2023
https://dl.acm.org/doi/10.1007/s10639-022-11373-1
Zhou XWu X(2022)Teaching Mode Based on Educational Big Data Mining and Digital TwinsComputational Intelligence and Neuroscience10.1155/2022/90719442022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/9071944

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