Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups

Many course designers trying to evaluate the experience of participants in a MOOC will find it difficult to track and analyse the online actions and interactions of students because there may be thousands of learners enrolled in courses that sometimes last only a few weeks. This study explores the u...

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Autores principales:	Karsten Lundqvist, Tharindu Liyanagunawardena, Louise Starkey
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2020
Materias:	MOOC teaching programming sentiment analysis target group feedback learner analytics Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/1222558edb994d539321c48f8f348a0a
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id	oai:doaj.org-article:1222558edb994d539321c48f8f348a0a
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spelling	oai:doaj.org-article:1222558edb994d539321c48f8f348a0a2021-12-02T17:16:06ZEvaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups10.19173/irrodl.v21i3.47831492-3831https://doaj.org/article/1222558edb994d539321c48f8f348a0a2020-05-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/4783https://doaj.org/toc/1492-3831Many course designers trying to evaluate the experience of participants in a MOOC will find it difficult to track and analyse the online actions and interactions of students because there may be thousands of learners enrolled in courses that sometimes last only a few weeks. This study explores the use of automated sentiment analysis in assessing student experience in a beginner computer programming MOOC. A dataset of more than 25,000 online posts made by participants during the course was analysed and compared to student feedback. The results were further analysed by grouping participants according to their prior knowledge of the subject: beginner, experienced, and unknown. In this study, the average sentiment expressed through online posts reflected the feedback statements. Beginners, the target group for the MOOC, were more positive about the course than experienced participants, largely due to the extra assistance they received. Many experienced participants had expected to learn about topics that were beyond the scope of the MOOC. The results suggest that MOOC designers should consider using sentiment analysis to evaluate student feedback and inform MOOC design. Karsten LundqvistTharindu LiyanagunawardenaLouise StarkeyAthabasca University PressarticleMOOCteaching programmingsentiment analysistarget groupfeedbacklearner analyticsSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 21, Iss 3 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	MOOC teaching programming sentiment analysis target group feedback learner analytics Special aspects of education LC8-6691
spellingShingle	MOOC teaching programming sentiment analysis target group feedback learner analytics Special aspects of education LC8-6691 Karsten Lundqvist Tharindu Liyanagunawardena Louise Starkey Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups
description	Many course designers trying to evaluate the experience of participants in a MOOC will find it difficult to track and analyse the online actions and interactions of students because there may be thousands of learners enrolled in courses that sometimes last only a few weeks. This study explores the use of automated sentiment analysis in assessing student experience in a beginner computer programming MOOC. A dataset of more than 25,000 online posts made by participants during the course was analysed and compared to student feedback. The results were further analysed by grouping participants according to their prior knowledge of the subject: beginner, experienced, and unknown. In this study, the average sentiment expressed through online posts reflected the feedback statements. Beginners, the target group for the MOOC, were more positive about the course than experienced participants, largely due to the extra assistance they received. Many experienced participants had expected to learn about topics that were beyond the scope of the MOOC. The results suggest that MOOC designers should consider using sentiment analysis to evaluate student feedback and inform MOOC design.
format	article
author	Karsten Lundqvist Tharindu Liyanagunawardena Louise Starkey
author_facet	Karsten Lundqvist Tharindu Liyanagunawardena Louise Starkey
author_sort	Karsten Lundqvist
title	Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups
title_short	Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups
title_full	Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups
title_fullStr	Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups
title_full_unstemmed	Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups
title_sort	evaluation of student feedback within a mooc using sentiment analysis and target groups
publisher	Athabasca University Press
publishDate	2020
url	https://doaj.org/article/1222558edb994d539321c48f8f348a0a
work_keys_str_mv	AT karstenlundqvist evaluationofstudentfeedbackwithinamoocusingsentimentanalysisandtargetgroups AT tharinduliyanagunawardena evaluationofstudentfeedbackwithinamoocusingsentimentanalysisandtargetgroups AT louisestarkey evaluationofstudentfeedbackwithinamoocusingsentimentanalysisandtargetgroups
_version_	1718381185291255808

Evaluation of Student Feedback Within a MOOC Using Sentiment Analysis and Target Groups

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