Research on the predictive model based on the depth of problem-solving discussion in MOOC forum

A discussion forum is an indispensable part of a massive open online course (MOOC) environment as it enables knowledge construction through learner-to-learner interaction such as discussion of solutions to assigned problems among learners. In this paper, a machine prediction model is built based on...

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Detalles Bibliográficos
Autores principales: Li, Jiansheng, Li, Linlin, Zhu, Zhixin, Shadiev, Rustam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034900/
https://www.ncbi.nlm.nih.gov/pubmed/37361840
http://dx.doi.org/10.1007/s10639-023-11694-9
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author Li, Jiansheng
Li, Linlin
Zhu, Zhixin
Shadiev, Rustam
author_facet Li, Jiansheng
Li, Linlin
Zhu, Zhixin
Shadiev, Rustam
author_sort Li, Jiansheng
collection PubMed
description A discussion forum is an indispensable part of a massive open online course (MOOC) environment as it enables knowledge construction through learner-to-learner interaction such as discussion of solutions to assigned problems among learners. In this paper, a machine prediction model is built based on the data from the MOOC forum and the depth of discussion of solutions to assigned problems on the topic among students was analyzed. The data for this study was obtained from Modern educational technology course through Selenium with Python. The course has been offered to a total of 11,184 students from China seven times since February, 2016. The proposed model includes the formula of the depth of problem-solving discussion in MOOC forum and its prediction probability. The efficiency of the prediction model and the most important factor of the depth of problem-solving discussion in MOOC are explained in the paper. Based on the results, useful suggestions for effective teaching in MOOC forums are provided in the article.
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spelling pubmed-100349002023-03-23 Research on the predictive model based on the depth of problem-solving discussion in MOOC forum Li, Jiansheng Li, Linlin Zhu, Zhixin Shadiev, Rustam Educ Inf Technol (Dordr) Article A discussion forum is an indispensable part of a massive open online course (MOOC) environment as it enables knowledge construction through learner-to-learner interaction such as discussion of solutions to assigned problems among learners. In this paper, a machine prediction model is built based on the data from the MOOC forum and the depth of discussion of solutions to assigned problems on the topic among students was analyzed. The data for this study was obtained from Modern educational technology course through Selenium with Python. The course has been offered to a total of 11,184 students from China seven times since February, 2016. The proposed model includes the formula of the depth of problem-solving discussion in MOOC forum and its prediction probability. The efficiency of the prediction model and the most important factor of the depth of problem-solving discussion in MOOC are explained in the paper. Based on the results, useful suggestions for effective teaching in MOOC forums are provided in the article. Springer US 2023-03-23 /pmc/articles/PMC10034900/ /pubmed/37361840 http://dx.doi.org/10.1007/s10639-023-11694-9 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Li, Jiansheng
Li, Linlin
Zhu, Zhixin
Shadiev, Rustam
Research on the predictive model based on the depth of problem-solving discussion in MOOC forum
title Research on the predictive model based on the depth of problem-solving discussion in MOOC forum
title_full Research on the predictive model based on the depth of problem-solving discussion in MOOC forum
title_fullStr Research on the predictive model based on the depth of problem-solving discussion in MOOC forum
title_full_unstemmed Research on the predictive model based on the depth of problem-solving discussion in MOOC forum
title_short Research on the predictive model based on the depth of problem-solving discussion in MOOC forum
title_sort research on the predictive model based on the depth of problem-solving discussion in mooc forum
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10034900/
https://www.ncbi.nlm.nih.gov/pubmed/37361840
http://dx.doi.org/10.1007/s10639-023-11694-9
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