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A Case Study of Discussion Forums in Two Programming MOOCs on Different Platforms

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Conference

2019 ASEE Annual Conference & Exposition

Location

Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

Technical Session 7: Online and Distributed Learning

Tagged Division

Computers in Education

Page Count

14

Permanent URL

https://peer.asee.org/31942

Download Count

7

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Paper Authors

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David Ray Waller Purdue University-Main Campus, West Lafayette (College of Engineering)

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David Waller is a PhD student in the School of Engineering Education at Purdue University. His research interests are in the field of educational measurement and assessment in engineering, particularly measurement and assessment in the context of engineering design. David earned a Bachelor of Engineering in Aerospace Engineering from Ryerson University in Toronto, Ontario and a Master of Applied Science in Mechanical Engineering at Queen’s University in Kingston, Ontario. His master’s thesis focused on engineering education by investigating how engineering students experience creativity in their engineering design courses.

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Kerrie A. Douglas Purdue University-Main Campus, West Lafayette (College of Engineering)

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Dr. Douglas is an Assistant Professor in the Purdue School of Engineering Education. Her research is focused on improving methods of assessment in large learning environments to foster high-quality learning opportunities. Additionally, she studies techniques to validate findings from machine-generated educational data.

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Gaurav Nanda Purdue University Orcid 16x16 orcid.org/https://0000-0003-1240-8639

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Dr. Gaurav Nanda is a Postdoctoral Researcher at Purdue University. He completed his Ph.D. in Industrial Engineering from Purdue University and Masters and Bachelors from Indian Institute of Technology Kharagpur, India.

His research interests include application of text mining and machine learning methods to analyze real-world data. Currently, he is studying learner experiences in online courses by applying text mining approaches on user generated data such as discussion forums and open-ended feedback.

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Abstract

Social interaction in massive open online courses (MOOCs) can enhance the educational experience by creating learning communities where students teach and learn from one another, as well as generate knowledge together. To facilitate this social interaction, MOOCs often encourage students to post and respond to questions and comments about course material on discussion forums. Research shows that discussion forums can promote a social learning environment which leads to deeper learning and increased student engagement. However, getting learners to participate in discussion forums remains a challenge. Previous studies have shown that different levels of educator involvement can influence the level and nature of participation from learners. Additionally, the design of the MOOC platform can impact how students use the discussion forums. The strategies from both the instructor and the MOOC platform play a large role in how students interact with discussion forums and the extent to which they contribute to learning.

The purpose of this research paper is to investigate how instructor involvement and platform features affect the quantity and quality of discussions in MOOCs that teach computer programming subjects. To the best of our knowledge, no previous study has compared the discussion forums on two different MOOC platforms. Our research questions are: a) how do different approaches to instructor involvement affect participation of learners in discussion forums, and b) what platform features help elicit learner discussion.

To address these questions, we used case study methodology for an in-depth exploration of the discussion forums for two computer programming MOOCs, P1 and P2. Both MOOCs had approximately 4800 enrollees and were offered on different platforms. The platform for P1 was explicitly designed for social learning. Our initial step was a qualitative analysis where we labelled each thread in the discussion forums according to the type of post and the role of the individual making the post. These labels were developed through open coding, allowing for categories to emerge from the data. This resulted in topic labels of “social”, “concept-related”, “assignment-related”, and “other”, and role labels of “information-seeker” and “information-provider”. After comments were labelled, we performed a quantitative analysis to determine the number of posts in each category, thread length, number of users posting and replying, and number of posts and responses by each user. From the “content-related” posts, we qualitatively analyzed the threads for the depth of conversation and educator involvement. To evaluate the features and usability of platforms, we applied the cognitive walkthrough approach to examine the ease of participation.

From our initial analysis, we found that most posts from P1 and P2 were social in nature, and “concept-related” posts did not involve in-depth discussions. While some of the strategies used by P1 and P2 encouraged participation in discussion forums, the nature of the posts did not suggest they contributed to social learning. We suggest that MOOC instructors and platform designers need to think about ways to promote social learning by eliciting more deep and meaningful discussion of course content.

Waller, D. R., & Douglas, K. A., & Nanda, G. (2019, June), A Case Study of Discussion Forums in Two Programming MOOCs on Different Platforms Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. https://peer.asee.org/31942

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