Abstract
This study examined the relationship between discussion forum contributions and course assessment results in a statistics MOOC. An important feature of the study is that it distinguished between discussions that were related to the learning of course material (“content-related”) and those which were not (“non-content”). Another contribution is that the study evaluated the additional usefulness of social centrality measures in predicting course grade after the quantity of forum contributions has been accounted for. Results showed that, overall, 15% of course learners contributed to the forums and these learners had a significantly higher rate of successfully passing the course than non-contributors (64% vs 32% passing). Learners who made posts to both content-related and non-content threads had a higher passing rate than those who only contributed to one type or the other. Among learners who successfully passed the course, there were no differences in course grade when comparing discussion contributors and non-contributors overall; however those who contributed to content-related threads performed slightly better than those who did not (course grade of 87% vs 85%). A predictive model based on the number of posts made to content-related threads explained a small proportion of variance in course grades; addition of social centrality measures did not significantly improve the variance explained by the model.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 8th International Conference on Learning Analytics and Knowledge |
| Subtitle of host publication | Towards User-Centred Learning Analytics, LAK 2018 |
| Publisher | Association for Computing Machinery |
| Pages | 330-339 |
| Number of pages | 10 |
| ISBN (Electronic) | 9781450364003 |
| DOIs | |
| State | Published - Mar 7 2018 |
| Event | 8th International Conference on Learning Analytics and Knowledge, LAK 2018 - Sydney, Australia Duration: Mar 5 2018 → Mar 9 2018 |
Other
| Other | 8th International Conference on Learning Analytics and Knowledge, LAK 2018 |
|---|---|
| Country | Australia |
| City | Sydney |
| Period | 3/5/18 → 3/9/18 |
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Keywords
- Discussion forum
- Learning outcomes
- Massive open online courses
- Social network analysis
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Software
Cite this
Unpacking the relationship between discussion forum participation and learning in MOOCs : Content is key. / Wise, Alyssa; Cui, Yi.
Proceedings of the 8th International Conference on Learning Analytics and Knowledge: Towards User-Centred Learning Analytics, LAK 2018. Association for Computing Machinery, 2018. p. 330-339.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Unpacking the relationship between discussion forum participation and learning in MOOCs
T2 - Content is key
AU - Wise, Alyssa
AU - Cui, Yi
PY - 2018/3/7
Y1 - 2018/3/7
N2 - This study examined the relationship between discussion forum contributions and course assessment results in a statistics MOOC. An important feature of the study is that it distinguished between discussions that were related to the learning of course material (“content-related”) and those which were not (“non-content”). Another contribution is that the study evaluated the additional usefulness of social centrality measures in predicting course grade after the quantity of forum contributions has been accounted for. Results showed that, overall, 15% of course learners contributed to the forums and these learners had a significantly higher rate of successfully passing the course than non-contributors (64% vs 32% passing). Learners who made posts to both content-related and non-content threads had a higher passing rate than those who only contributed to one type or the other. Among learners who successfully passed the course, there were no differences in course grade when comparing discussion contributors and non-contributors overall; however those who contributed to content-related threads performed slightly better than those who did not (course grade of 87% vs 85%). A predictive model based on the number of posts made to content-related threads explained a small proportion of variance in course grades; addition of social centrality measures did not significantly improve the variance explained by the model.
AB - This study examined the relationship between discussion forum contributions and course assessment results in a statistics MOOC. An important feature of the study is that it distinguished between discussions that were related to the learning of course material (“content-related”) and those which were not (“non-content”). Another contribution is that the study evaluated the additional usefulness of social centrality measures in predicting course grade after the quantity of forum contributions has been accounted for. Results showed that, overall, 15% of course learners contributed to the forums and these learners had a significantly higher rate of successfully passing the course than non-contributors (64% vs 32% passing). Learners who made posts to both content-related and non-content threads had a higher passing rate than those who only contributed to one type or the other. Among learners who successfully passed the course, there were no differences in course grade when comparing discussion contributors and non-contributors overall; however those who contributed to content-related threads performed slightly better than those who did not (course grade of 87% vs 85%). A predictive model based on the number of posts made to content-related threads explained a small proportion of variance in course grades; addition of social centrality measures did not significantly improve the variance explained by the model.
KW - Discussion forum
KW - Learning outcomes
KW - Massive open online courses
KW - Social network analysis
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UR - http://www.scopus.com/inward/citedby.url?scp=85045559488&partnerID=8YFLogxK
U2 - 10.1145/3170358.3170403
DO - 10.1145/3170358.3170403
M3 - Conference contribution
SP - 330
EP - 339
BT - Proceedings of the 8th International Conference on Learning Analytics and Knowledge
PB - Association for Computing Machinery
ER -