The main objective of the Crowdlearning project is to enable students to collaborate in a new capacity -- as teachers. The premise here is that deeper learning can be achieved once students recognize that, having acquired some skill, they can immediately start helping peers to master the same skill.
The vision of Crowdlearning is that of a self-sustaining problem-posing and problem-solving environment, where the students of a given subject intermittently take on roles as
(A) the creators of subject-focused problems; (B) evaluators of problem quality; and (C) problem solvers. The activities that the students perform in roles (A) and (B) are consensus-driven, wherein students create and ``vote'' in the problems that help them learn, thereby building ``banks'' of subject matter problems to use for learning and assessment.
While Crowdlearning can be adopted as an in-class practice, it is expected to be most useful when implemented as an online platform that will direct collaborative activities across classrooms, campuses and colleges.
For now, I am maintaining several sets of Crowdlearning-created quiz
questions for "Simulation" subject. Instructors interested in using them:
please e-mail me at and I'll share right away!
This project includes the development of online tools that will enable and/or facilitate Crowdlearning, efforts to evaluate the effectiveness of Crowdlearning practices in physical and virtual classrooms, and new advances in intelligent tutoring systems, in particular in student modeling and learning curve optimization.
Alireza Farasat, Alexander Nikolaev, Suzanne Miller, Rahul Gopalsamy “Crowdlearning: Towards Collaborative Problem Posing at Scale”, 4th ACM Conference on Learning at Scale, Cambridge, MA, 2017.
Alireza Farasat*, & Alexander Nikolaev, “Constrained Sparse Optimization for Tensor-Based Modeling Of Student Learning Dynamics”, Technical Report, University at Buffalo, 2016.
Alireza Farasat*, & Alexander Nikolaev, “Parallel Sparse Factor Analysis for Student Modeling at Scale”, Technical Report, University at Buffalo, 2016.
State University of New York, Innovative Instruction Technology Grant Program (Tier 3), “Crowdlearning: Towards Collaborative, Self-sustaining Learning Environments and Practices”, $50,000.00, Alexander Nikolaev (PI), Suzanne Miller (Co-PI), 2016 - 2017.
University at Buffalo Center for Educational Innovation, Seed Grant “Crowdsourcing for Crowdlearning: a New Online Tool for Advanced Peer Assessment”, $3,500.00, Alexander Nikolaev (PI), Suzanne Miller (Co-PI), 2016 - 2017.
University at Buffalo Center for Educational Innovation, Seed Grant “Crowd-Learning: Research Agenda and Supporting Evidence Collection”, $10,000.00, Alexander Nikolaev (PI), Suzanne Miller (Co-PI), 2015 - 2016.