<abstract xmlns="http://www.w3.org/1999/xhtml"><sec id="j_jdis-2018-0009_s_006_w2aab3b7b4b1b6b1aab1c17b1Aa"><h3>Purpose</h3><p>Compared with traditional course materials used in the classroom, the massive open online course (MOOC) forum that delivers unlimited learning content to students has various advantages. Yet MOOC has also received criticism recently, notably the problem of extremely low participation rates in its discussion forums. This study aims to explore the correlation between forum activity and student course grade in MOOC, and identify more accurately the forum activity levels of participants and the quality of threads in MOOC.</p></sec><sec id="j_jdis-2018-0009_s_007_w2aab3b7b4b1b6b1aab1c17b2Aa"><h3>Design/Methodology/Approach</h3><p>We crawled students’ tests, final exams, exercises, discussions performance data and total scores from a course in Chinese College MOOC from May 2014 to August 2014. And we use the data to analyze the correlation between Forum Participation and Course Performance based on nonparametric tests as well as multiple linear regressions with the software of R. The study provides definitions and algorithms of super degrees based on the supernetwork model to help find high-quality threads and active participants.</p></sec><sec id="j_jdis-2018-0009_s_008_w2aab3b7b4b1b6b1aab1c17b3Aa"><h3>Findings</h3><p>A positive correlation between forum activity and course grade is found in this study. Students who participate in the forum have better performance than those who do not. Using the definitions and algorithms of super degrees in the supernetwork, forum activity levels of participants as well as the quality of threads they employ are identified.</p></sec><sec id="j_jdis-2018-0009_s_009_w2aab3b7b4b1b6b1aab1c17b4Aa"><h3>Research limitation</h3><p>Only limited representative forum participants and threads are used to analyze the activity level and significance of the MOOC forum. Also, the study only investigates one Chinese course on information retrieval. More data and more data sources could be helpful in better understanding the MOOC forum phenomenon.</p></sec><sec id="j_jdis-2018-0009_s_010_w2aab3b7b4b1b6b1aab1c17b5Aa"><h3>Practical implications</h3><p>As super degrees can reveal more latent information and recognize high-quality threads as well as active participants, these parameters can be used to assess needs to improve forum settings and alleviate the problem of low forum participation. The proposed super degrees can be applied in social network domains for further research.</p></sec><sec id="j_jdis-2018-0009_s_011_w2aab3b7b4b1b6b1aab1c17b6Aa"><h3>Originality/Value</h3><p>Definitions and algorithms of super degrees are provided and used for forum analysis. Super degrees can be applied to find high-quality threads and active participants, which is beneficial to guide students to participate in these high-quality threads and have a better understanding of knowledge MOOC provides.</p></sec></abstract>

PurposeCompared with traditional course materials used in the classroom, the massive open online course (MOOC) forum that delivers unlimited learning content to students has various advantages. Yet MOOC has also received criticism recently, notably the problem of extremely low participation rates in its discussion forums. This study aims to explore the correlation between forum activity and student course grade in MOOC, and identify more accurately the forum activity levels of participants and the quality of threads in MOOC.Design/Methodology/ApproachWe crawled students’ tests, final exams, exercises, discussions performance data and total scores from a course in Chinese College MOOC from May 2014 to August 2014. And we use the data to analyze the correlation between Forum Participation and Course Performance based on nonparametric tests as well as multiple linear regressions with the software of R. The study provides definitions and algorithms of super degrees based on the supernetwork model to help find high-quality threads and active participants.FindingsA positive correlation between forum activity and course grade is found in this study. Students who participate in the forum have better performance than those who do not. Using the definitions and algorithms of super degrees in the supernetwork, forum activity levels of participants as well as the quality of threads they employ are identified.Research limitationOnly limited representative forum participants and threads are used to analyze the activity level and significance of the MOOC forum. Also, the study only investigates one Chinese course on information retrieval. More data and more data sources could be helpful in better understanding the MOOC forum phenomenon.Practical implicationsAs super degrees can reveal more latent information and recognize high-quality threads as well as active participants, these parameters can be used to assess needs to improve forum settings and alleviate the problem of low forum participation. The proposed super degrees can be applied in social network domains for further research.Originality/ValueDefinitions and algorithms of super degrees are provided and used for forum analysis. Super degrees can be applied to find high-quality threads and active participants, which is beneficial to guide students to participate in these high-quality threads and have a better understanding of knowledge MOOC provides.

Is Participating in MOOC Forums Important for Students? A Data-driven Study from the Perspective of the Supernetwork

Center for E-commerce Research and Development

Journal of Data and Information Science

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

PurposeCompared with traditional course materials used in the classroom, the massive open online course (MOOC) forum that delivers unlimited learning content...

	N	Minimum	Maximum	Mean	Std. Deviation
Tests/113.0	1,917	0	113	69.23	38.98
Exercises/30.0	2,625	3	30	15.30	7.21
Exams/30.0	1,264	0	30	28.38	2.67
Discussions/30.0	3,231	0	30	22.10	13.21
Posts	804	0	15	0.57	1.46
Comments	804	0	46	0.43	2.29
Replies	804	0	116	3.59	8.02
Total Score/100	3,231	0	99.8	48.15	34.97

	Test Score	Exercises Score	Exam Score	Total Score
Z	-4.439	-5.06	-5.983	-3.918
P-value	.000	.000	.000	.000

	Group	N	Mean Rank	Mean score
Tests	Non-discussion	1,343	798.94	58.97
	Discussion	573	1,332.49	94.31
Exercises	Non-discussion	2,056	1,138.56	13.5
	Discussion	568	1,942.11	21.77
Exams	Non-discussion	755	591.66	28.02
	Discussion	508	691.96	28.87
Scores	Non-discussion	2,599	1,400.70	40.14
	Discussion	631	2,500.22	81.05

Username	Thread 1	Thread 2	Thread 3	Thread 4	Thread 5
Viannn	√	√	√	√	√
Winner	√	√	√	√
Day@4	√	√	√		√
mooc15951364231	√	√		√
Lin Wei ykt1123		√	√	√
Red Fruit mooc4	√	√
Chongqing WZZ	√		√
AYmooc	√			√
Monogram	√				√
SUNSET		√			√

Thread	Edge degree	Super-edge degree
Thread 1	8	6.62
Thread 2	8	6.90
Thread 3	5	3.10
Thread 4	5	2.93
Thread 5	3	1.14

Is Participating in MOOC Forums Important for Students? A Data-driven Study from the Perspective of the Supernetwork

Article Category: Research Paper

Published Online: Jun 22, 2018

Page range: 62 - 77

Received: Dec 16, 2017

Accepted: Mar 22, 2018

DOI: https://doi.org/10.2478/jdis-2018-0009

Keywords
MOOC, Participate, Forum, Supernetwork, Super degrees

© 2018 Walter de Gruyter GmbH, Berlin/Boston, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Descriptive statistics of student scores and forum activities.

Test statistics.

Results of nonparametric tests.

Participants and threads they participate in.

Edge degree and super-edge degree of threads.

Regression analysis results.

Node degree and super-node degree of participants.

	Coefficient		P-value
Comment	0.879		.004
Reply	3.937		.000
Post	1.776		.000
(Constant)	−.900		.242
Adjusted R2		0.657
P-value		0.000

Is Participating in MOOC Forums Important for Students? A Data-driven Study from the Perspective of the Supernetwork

Article Category: Research Paper

Published Online: Jun 22, 2018

Page range: 62 - 77

Received: Dec 16, 2017

Accepted: Mar 22, 2018

DOI: https://doi.org/10.2478/jdis-2018-0009

KeywordsMOOC, Participate, Forum, Supernetwork, Super degrees

© 2018 Walter de Gruyter GmbH, Berlin/Boston, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Figure 1

Descriptive statistics of student scores and forum activities.

Test statistics.

Results of nonparametric tests.

Participants and threads they participate in.

Edge degree and super-edge degree of threads.

Regression analysis results.

Node degree and super-node degree of participants.

Keywords
MOOC, Participate, Forum, Supernetwork, Super degrees