Exploring Scalability in Interfaces that Support Student Contributions within Online Learning Systems

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Recent years have seen a dramatic rise in technologies that support crowdsourced or peer learning, enabling communities of users to work together to improve and personalize learning resources. Continuing our collaboration with D2L Corporation (formerly Desire2Learn), this research will explore ways to allow this type of community-supported digital learning in the specific context of online learning systems. Building on our successful Engage research, our focus in this next phase of the collaboration between our research team and D2L will be on ways to enable students to contribute to instructor-posted learning content (e.g., through refinements, comments or suggestions) in ways that scale as the number of student contributions increases. Through this research, we will design and implement alternative software proof-of-concepts. We will also explore potential tradeoffs among the most promising approaches through empirical evaluations with end users. This project will help solidify an establishing partnership between Human-Computer Interaction (HCI) researchers at the University of Manitoba, and D2L, a Canadian-based company specializing in online learning systems. Through the collaboration, D2L will be able to experiment with cutting-edge HCI methods and techniques in crowdsourced learning, and the University of Manitoba researchers will gain valuable experience in adapting and/or extending these techniques in the face of real-world constraints. The expected outcomes of this project include techniques and interfaces for this type of peer-driven peer-driven online learning, along with empirically validated design guidelines. Improvements to D2L's products through research-based results will help D2L continue to be successful in a highly competitive market, benefiting the Canadian economy as well as providing future employment opportunities for HQP trained in Human-Computer Interaction.