A survival model for course-course interactions in a Massive Open Online Course platform.
Massive Open Online Course (MOOC) platforms incorporate large course catalogs from which individual students may register multiple courses. We performed a network-based analysis of student achievement, considering how course-course interactions may positively or negatively affect student success. Ou...
Main Authors: | , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2021-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0245718 |
id |
doaj-9ed6f19ce126459e83f6f03831e95638 |
---|---|
record_format |
Article |
spelling |
doaj-9ed6f19ce126459e83f6f03831e956382021-06-19T05:09:05ZengPublic Library of Science (PLoS)PLoS ONE1932-62032021-01-01161e024571810.1371/journal.pone.0245718A survival model for course-course interactions in a Massive Open Online Course platform.Edwin H WintermuteMatthieu CiselAriel B LindnerMassive Open Online Course (MOOC) platforms incorporate large course catalogs from which individual students may register multiple courses. We performed a network-based analysis of student achievement, considering how course-course interactions may positively or negatively affect student success. Our data set included 378,000 users and 1,000,000 unique registration events in France Université Numérique (FUN), a national MOOC platform. We adapt reliability theory to model certificate completion rates with a Weibull survival function, following the intuition that students "survive" in a course for a certain time before stochastically dropping out. Course-course interactions are found to be well described by a single parameter for user engagement that can be estimated from a user's registration profile. User engagement, in turn, correlates with certificate rates in all courses regardless of specific content. The reliability approach is shown to capture several certificate rate patterns that are overlooked by conventional regression models. User engagement emerges as a natural metric for tracking student progress across demographics and over time.https://doi.org/10.1371/journal.pone.0245718 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Edwin H Wintermute Matthieu Cisel Ariel B Lindner |
spellingShingle |
Edwin H Wintermute Matthieu Cisel Ariel B Lindner A survival model for course-course interactions in a Massive Open Online Course platform. PLoS ONE |
author_facet |
Edwin H Wintermute Matthieu Cisel Ariel B Lindner |
author_sort |
Edwin H Wintermute |
title |
A survival model for course-course interactions in a Massive Open Online Course platform. |
title_short |
A survival model for course-course interactions in a Massive Open Online Course platform. |
title_full |
A survival model for course-course interactions in a Massive Open Online Course platform. |
title_fullStr |
A survival model for course-course interactions in a Massive Open Online Course platform. |
title_full_unstemmed |
A survival model for course-course interactions in a Massive Open Online Course platform. |
title_sort |
survival model for course-course interactions in a massive open online course platform. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2021-01-01 |
description |
Massive Open Online Course (MOOC) platforms incorporate large course catalogs from which individual students may register multiple courses. We performed a network-based analysis of student achievement, considering how course-course interactions may positively or negatively affect student success. Our data set included 378,000 users and 1,000,000 unique registration events in France Université Numérique (FUN), a national MOOC platform. We adapt reliability theory to model certificate completion rates with a Weibull survival function, following the intuition that students "survive" in a course for a certain time before stochastically dropping out. Course-course interactions are found to be well described by a single parameter for user engagement that can be estimated from a user's registration profile. User engagement, in turn, correlates with certificate rates in all courses regardless of specific content. The reliability approach is shown to capture several certificate rate patterns that are overlooked by conventional regression models. User engagement emerges as a natural metric for tracking student progress across demographics and over time. |
url |
https://doi.org/10.1371/journal.pone.0245718 |
work_keys_str_mv |
AT edwinhwintermute asurvivalmodelforcoursecourseinteractionsinamassiveopenonlinecourseplatform AT matthieucisel asurvivalmodelforcoursecourseinteractionsinamassiveopenonlinecourseplatform AT arielblindner asurvivalmodelforcoursecourseinteractionsinamassiveopenonlinecourseplatform AT edwinhwintermute survivalmodelforcoursecourseinteractionsinamassiveopenonlinecourseplatform AT matthieucisel survivalmodelforcoursecourseinteractionsinamassiveopenonlinecourseplatform AT arielblindner survivalmodelforcoursecourseinteractionsinamassiveopenonlinecourseplatform |
_version_ |
1721371398806437888 |