Crowdlearning: Towards Collaborative Problem-Posing at Scale
Alireza Farasat, Alexander Nikolaev, Suzanne Miller, and Rahul Gopalsamy
This paper presents a new pedagogical paradigm ``Crowdlearning'', where students experience deeper learning through collaboratively creating learning materials for each other. Crowdlearning practice is envisioned to produce large ``banks'' of subject matter problems generated by students themselves, in a crowdsourced way, as the students learn new subjects; these problems can then serve as learning and assessment materials usable at scale. This paper overviews the motivation for the development of Crowdlearning as a teaching practice and the theoretical drivers behind it. The paper then reports on preliminary field studies and experiences suggesting that Crowdlearning has a solid potential for adoption in STEM.