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Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC

Malaysia and many other developing countries progressively adopting massively open online course (MOOC) in their national higher education approach. We have observed an increasing need for facilitating MOOC monitoring that is associated with the rising adoption of MOOCs. Our observation suggests tha...

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Main Authors: Mohammad Fadhli Asli, Muzaffar Hamzah, Ag Asri Ag Ibrahim, Enna Ayub
Format: Article
Language:English
English
Published: Elsevier Ltd 2020
Subjects:
QA Mathematics
Online Access:https://eprints.ums.edu.my/id/eprint/27413/1/Problem%20characterization%20for%20visual%20analytics%20in%20MOOC%20learner%27s%20support%20monitoring%20abstract.pdf
https://eprints.ums.edu.my/id/eprint/27413/2/Problem%20characterization%20for%20visual%20analytics%20in%20MOOC%20learner%27s%20support%20monitoring%20Fulltext.pdf
https://eprints.ums.edu.my/id/eprint/27413/
https://doi.org/10.1016/j.heliyon.2020.e05733
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spelling my.ums.eprints.274132021-06-25T03:17:53Z https://eprints.ums.edu.my/id/eprint/27413/ Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC Mohammad Fadhli Asli Muzaffar Hamzah Ag Asri Ag Ibrahim Enna Ayub QA Mathematics Malaysia and many other developing countries progressively adopting massively open online course (MOOC) in their national higher education approach. We have observed an increasing need for facilitating MOOC monitoring that is associated with the rising adoption of MOOCs. Our observation suggests that recent adoption cases led analyst and instructors to focus on monitoring enrollment and learning activities. Visual analytics in MOOC support education analysts in analyzing MOOC data via interactive visualization. Existing literature on MOOC visualization focuses on enabling visual analysis on MOOC data from forum and course material. We found limited studies that investigate and characterize domain problems or design requirements of visual analytics for MOOC. This paper aims to present the empirical problem characterization and abstraction for visual analytics in MOOC learner’s support monitoring. Detailed characterization and abstraction of the domain problem help visualization designer to derive design requirements in generating appropriate visualization solution. We examined the literature and conducted a case study to elicit a problem abstraction based on data, users, and tasks. We interviewed five Malaysian MOOC experts from three higher education institutes using semi-structured questions. Our case study reveals the priority of enabling MOOC analysis on learner’s progression and course completion. There is an association between design and analysis priority with the pedagogical type of implemented MOOC and users. The characterized domain problems and requirements offer a design foundation for visual analytics in MOOC monitoring analysis. Elsevier Ltd 2020 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/27413/1/Problem%20characterization%20for%20visual%20analytics%20in%20MOOC%20learner%27s%20support%20monitoring%20abstract.pdf text en https://eprints.ums.edu.my/id/eprint/27413/2/Problem%20characterization%20for%20visual%20analytics%20in%20MOOC%20learner%27s%20support%20monitoring%20Fulltext.pdf Mohammad Fadhli Asli and Muzaffar Hamzah and Ag Asri Ag Ibrahim and Enna Ayub (2020) Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC. Heliyon, 6 (12). e05733. ISSN 2405-8440 https://doi.org/10.1016/j.heliyon.2020.e05733
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA Mathematics
spellingShingle QA Mathematics
Mohammad Fadhli Asli
Muzaffar Hamzah
Ag Asri Ag Ibrahim
Enna Ayub
Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC
description Malaysia and many other developing countries progressively adopting massively open online course (MOOC) in their national higher education approach. We have observed an increasing need for facilitating MOOC monitoring that is associated with the rising adoption of MOOCs. Our observation suggests that recent adoption cases led analyst and instructors to focus on monitoring enrollment and learning activities. Visual analytics in MOOC support education analysts in analyzing MOOC data via interactive visualization. Existing literature on MOOC visualization focuses on enabling visual analysis on MOOC data from forum and course material. We found limited studies that investigate and characterize domain problems or design requirements of visual analytics for MOOC. This paper aims to present the empirical problem characterization and abstraction for visual analytics in MOOC learner’s support monitoring. Detailed characterization and abstraction of the domain problem help visualization designer to derive design requirements in generating appropriate visualization solution. We examined the literature and conducted a case study to elicit a problem abstraction based on data, users, and tasks. We interviewed five Malaysian MOOC experts from three higher education institutes using semi-structured questions. Our case study reveals the priority of enabling MOOC analysis on learner’s progression and course completion. There is an association between design and analysis priority with the pedagogical type of implemented MOOC and users. The characterized domain problems and requirements offer a design foundation for visual analytics in MOOC monitoring analysis.
format Article
author Mohammad Fadhli Asli
Muzaffar Hamzah
Ag Asri Ag Ibrahim
Enna Ayub
author_facet Mohammad Fadhli Asli
Muzaffar Hamzah
Ag Asri Ag Ibrahim
Enna Ayub
author_sort Mohammad Fadhli Asli
title Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC
title_short Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC
title_full Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC
title_fullStr Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC
title_full_unstemmed Problem characterization for visual analytics in MOOC learner's support monitoring: A case of Malaysian MOOC
title_sort problem characterization for visual analytics in mooc learner's support monitoring: a case of malaysian mooc
publisher Elsevier Ltd
publishDate 2020
url https://eprints.ums.edu.my/id/eprint/27413/1/Problem%20characterization%20for%20visual%20analytics%20in%20MOOC%20learner%27s%20support%20monitoring%20abstract.pdf
https://eprints.ums.edu.my/id/eprint/27413/2/Problem%20characterization%20for%20visual%20analytics%20in%20MOOC%20learner%27s%20support%20monitoring%20Fulltext.pdf
https://eprints.ums.edu.my/id/eprint/27413/
https://doi.org/10.1016/j.heliyon.2020.e05733
_version_ 1760230618818412544
score 13.211869

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