Crowdlearning: Towards Collaborative, Self-Sustaining Learning Environments and Practices

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Nikolaev, Alexander
Miller, Suzanne M.
Farasat, Alireza
SUNY , State University of New York , IITG , Innovative Instructional Technology Grants , Collaborative Learning Technologies , Cloud-Based teaching and Learning Environments , Adaptive Learning Technologies
This project explores the utility of socio-technical pedagogical paradigm Crowdlearning in physical and virtual classrooms, across academic disciplines. The vision of Crowdlearning is that of a self-sustaining collaborative learning environment, where the participants - students of a given subject - intermittently take on the roles of (1) the creators of subject-focused problems (problem statements/formulations with answer alternatives, hints, correct answers with explanations, etc.), (2) problem quality evaluators, and (3) problem solvers, all on an anonymized gamified online platform. The PIs work to foster a self-regulated process, where student-initiated contributions feed into the growth and refinement of problem banks for academic subjects, with the evaluator responsibilities being crowdsourced to the students themselves. The resulting problem banks then enable gamified personalized learning. This project encompasses development, implementation and data analysis efforts in two physical (STEM and Graduate Education) classrooms and in one online course, exploring pathways to wider adoption of the Crowdlearning practice.
The IITG project revealed both opportunities and challenges of successful implementation and dissemination of the products per the PI's vision. More research is needed, and it is underway. A link to this paper published in the 2017 Conference on Learning at Scale: "CROWDLEARNING: Towards Collaborative Problem-Posing at Scale" is available in the Project Outcome Report.