Studying in the ‘Bazaar’: An Exploratory Study of Crowdsourced Learning in GitHub

• Main Authors: Yao Lu, Xinjun Mao, Tao Wang, Gang Yin, Zude Li, Wanyuan Wang
• Format: Article
• Language: English
• Published: IEEE 2019-01-01
• Series: IEEE Access
• Subjects: Crowdsourced learning; crowdsourcing; E-learning; GitHub; learning projects; learning community
• Online Access: https://ieeexplore.ieee.org/document/8708224/

In recent years, GitHub, the most popular social coding site, has been increasingly employed for managing learning content, sharing knowledge, imparting experience, and requesting and contributing learning resources in a crowdsourced way. We thus refer to this type of e-learning practices in which people perform learning-related tasks with open calls in an online community to gain knowledge or skills in specific areas as crowdsourced learning (CL). To understand this emerging phenomenon in GitHub, we investigate the popularity of the learning projects and learners' CL activities, first on the extracted GHTorrent learning projects and then on a selected sample of 105 popular learning projects. We then conduct an online survey of 301 learners to qualitatively understand their practices and perceptions of CL in GitHub. Our main findings reveal that the learners' CL practices show some different characteristics from those of open source development, e.g., the learning projects have very few long-term contributors (less than 5% of all contributors). Moreover, although the learners benefit from conducting personalized learning with the high-quality content and contributions made by the community, they encounter challenges in maintaining initiatives to conduct continuous unsupervised learning and in ensuring the quality of content and contributions. Based on the findings, we discuss the reasons behind the growth of CL and provide implications on the CL platform design.