Unpacking the relationship between discussion forum participation and learning in MOOCs: content is key

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.

[1]  Rebecca Eynon,et al.  Structural limitations of learning in a crowd: communication vulnerability and information diffusion in MOOCs , 2014, Scientific Reports.

[2]  Mark Warschauer,et al.  Predicting MOOC performance with Week 1 Behavior , 2014, EDM.

[3]  Michelene T. H. Chi,et al.  Active-Constructive-Interactive: A Conceptual Framework for Differentiating Learning Activities , 2009, Top. Cogn. Sci..

[4]  Alyssa Friend Wise,et al.  Bringing order to chaos in MOOC discussion forums with content-related thread identification , 2016, LAK.

[5]  A. Wise,et al.  Broadening the notion of participation in online discussions: examining patterns in learners’ online listening behaviors , 2013 .

[6]  Alyssa Friend Wise,et al.  Honing in on social learning networks in MOOC forums: examining critical network definition decisions , 2017, LAK.

[7]  S HoneKate,et al.  Exploring the factors affecting MOOC retention , 2016 .

[8]  Yvonne Belanger,et al.  Bioelectricity: A Quantitative Approach Duke University’s First MOOC , 2013 .

[9]  E. Wenger.  Communities of Practice: Learning, Meaning, and Identity , 1998 .

[10]  Alyssa Friend Wise,et al.  Mining for gold: Identifying content-related MOOC discussion threads across domains through linguistic modeling , 2017, Internet High. Educ..

[11]  Boris Korsunsky,et al.  By Hook or by MOOC: Lessons Learned and the Road Ahead. , 2017 .

[12]  Etienne Wenger,et al.  Communities of Practice: Learning, Meaning, and Identity , 1998 .

[13]  Sara McNeil,et al.  Students' patterns of engagement and course performance in a Massive Open Online Course , 2016, Comput. Educ..

[14]  Matti Nelimarkka,et al.  Alumni & Tenured Participants in MOOCs: Analysis of Two Years of MOOC Discussion Channel Activity , 2015, L@S.

[15]  Dragan Gasevic,et al.  Learning analytics should not promote one size fits all: The effects of instructional conditions in predicting academic success , 2016, Internet High. Educ..

[16]  Eni Mustafaraj,et al.  The Visible and Invisible in a MOOC Discussion Forum , 2015, L@S.

[17]  Omprakash Gnawali,et al.  Language independent analysis and classification of discussion threads in Coursera MOOC forums , 2014, Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014).

[18]  Alyssa Friend Wise,et al.  Humans and Machines Together: Improving Characterization of Large Scale Online Discussions through Dynamic Interrelated Post and Thread Categorization (DIPTiC) , 2017, L@S.

[19]  Ghada R. El Said,et al.  Exploring the factors affecting MOOC retention: A survey study , 2016, Comput. Educ..

[20]  H E Stanley,et al.  Classes of small-world networks. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Carolyn Penstein Rosé,et al.  Investigating How Student's Cognitive Behavior in MOOC Discussion Forum Affect Learning Gains , 2015, EDM.

[22]  Dragan Gasevic,et al.  Translating network position into performance: importance of centrality in different network configurations , 2016, LAK.

[23]  A. Wise,et al.  The Effects of Teacher Social Presence on Student Satisfaction, Engagement, and Learning , 2004, ICLS.

[24]  Rebecca Eynon,et al.  Communication patterns in massively open online courses , 2014, Internet High. Educ..

[25]  Luc Paquette,et al.  A Longitudinal Study on Learner Career Advancement in MOOCs , 2014, J. Learn. Anal..

[26]  K. Hew,et al.  Students’ and instructors’ use of massive open online courses (MOOCs): Motivations and challenges , 2014 .

[27]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[28]  Douglas H. Fisher,et al.  Pass the Idea Please: The Relationship between Network Position, Direct Engagement, and Course Performance in MOOCs , 2017, L@S.

[29]  Ulrik Schroeder,et al.  What Drives a Successful MOOC? An Empirical Examination of Criteria to Assure Design Quality of MOOCs , 2014, 2014 IEEE 14th International Conference on Advanced Learning Technologies.

[30]  Mark Warschauer,et al.  Social Positioning and Performance in MOOCs , 2014, EDM.

[31]  Christian Gütl,et al.  Attrition in MOOC: Lessons Learned from Drop-Out Students , 2014, LTEC@KMO.

[32]  David E. Pritchard,et al.  Studying Learning in the Worldwide Classroom Research into edX's First MOOC. , 2013 .

[33]  Björn Hartmann,et al.  Should your MOOC forum use a reputation system? , 2014, CSCW.

[34]  Alyssa Friend Wise,et al.  Beyond More Versus Less: A Reframing of the Debate on Instructional Guidance , 2009 .