Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis

Massive open online courses (MOOCs) have been touted as an effective way to make higher education accessible for free or for only a small fee, thus addressing the problem of unequal access and providing new opportunities to young people in middle and low income groups. However, many critiques of MO...

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Autor principal:	In Gu Kang
Formato:	article
Lenguaje:	EN
Publicado:	Athabasca University Press 2020
Materias:	MOOC learner behavioral engagement tailored intervention latent class analysis Special aspects of education LC8-6691
Acceso en línea:	https://doaj.org/article/6b8a95aeaf5240ea9639698254c38a80
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spelling	oai:doaj.org-article:6b8a95aeaf5240ea9639698254c38a802021-12-02T17:00:16ZHeterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis10.19173/irrodl.v21i4.46451492-3831https://doaj.org/article/6b8a95aeaf5240ea9639698254c38a802020-06-01T00:00:00Zhttp://www.irrodl.org/index.php/irrodl/article/view/4645https://doaj.org/toc/1492-3831 Massive open online courses (MOOCs) have been touted as an effective way to make higher education accessible for free or for only a small fee, thus addressing the problem of unequal access and providing new opportunities to young people in middle and low income groups. However, many critiques of MOOCs have indicated that low completion rates are a major concern. Using a latent class analysis (LCA), a more advanced methodology to identify latent subgroups, this study examined the heterogeneity of learners’ behavioral patterns in a MOOC, categorized them into distinctive subgroups, and ultimately determined the optimal number of latent subgroups in a MOOC. The five subgroups identified in this study were: completing (6.6%); disengaging (4.8%); auditing (4.6%); sampling (21.1%); and enrolling (62.8%). Results indicated this was the optimal number of subgroups. Given the characteristics of the three at-risk subgroups (disengaging, sampling, and enrolling), tailored instructional strategies and interventions to improve behavioral engagement are discussed. In Gu KangAthabasca University PressarticleMOOClearner behavioral engagementtailored interventionlatent class analysisSpecial aspects of educationLC8-6691ENInternational Review of Research in Open and Distributed Learning, Vol 21, Iss 4 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	MOOC learner behavioral engagement tailored intervention latent class analysis Special aspects of education LC8-6691
spellingShingle	MOOC learner behavioral engagement tailored intervention latent class analysis Special aspects of education LC8-6691 In Gu Kang Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis
description	Massive open online courses (MOOCs) have been touted as an effective way to make higher education accessible for free or for only a small fee, thus addressing the problem of unequal access and providing new opportunities to young people in middle and low income groups. However, many critiques of MOOCs have indicated that low completion rates are a major concern. Using a latent class analysis (LCA), a more advanced methodology to identify latent subgroups, this study examined the heterogeneity of learners’ behavioral patterns in a MOOC, categorized them into distinctive subgroups, and ultimately determined the optimal number of latent subgroups in a MOOC. The five subgroups identified in this study were: completing (6.6%); disengaging (4.8%); auditing (4.6%); sampling (21.1%); and enrolling (62.8%). Results indicated this was the optimal number of subgroups. Given the characteristics of the three at-risk subgroups (disengaging, sampling, and enrolling), tailored instructional strategies and interventions to improve behavioral engagement are discussed.
format	article
author	In Gu Kang
author_facet	In Gu Kang
author_sort	In Gu Kang
title	Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis
title_short	Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis
title_full	Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis
title_fullStr	Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis
title_full_unstemmed	Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis
title_sort	heterogeneity of learners’ behavioral patterns of watching videos and completing assessments in massive open online courses (moocs): a latent class analysis
publisher	Athabasca University Press
publishDate	2020
url	https://doaj.org/article/6b8a95aeaf5240ea9639698254c38a80
work_keys_str_mv	AT ingukang heterogeneityoflearnersbehavioralpatternsofwatchingvideosandcompletingassessmentsinmassiveopenonlinecoursesmoocsalatentclassanalysis
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Heterogeneity of Learners’ Behavioral Patterns of Watching Videos and Completing Assessments in Massive Open Online Courses (MOOCs): A Latent Class Analysis

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