Refreshments will be provided.
- Presentation (20 minutes)
- Q&A (40 minutes)
Learning and Assessing in Massive Online Classrooms
Friends and networks have always played an influential role in mediating and enriching learning. Massive online courses represent perhaps the greatest collection of peers assembled in a classroom. How can well-proven classroom techniques inspire new interactions in massive online courses? How can the diversity, multitude and enthusiasm of these peers change how we teach and evaluate? By tapping into networks of peers in online education, we can develop techniques that provide high-quality feedback for open-ended assignments such as design and writing, as well as improve motivation and retention. Chinmay Kulkarni will first introduce peer assessment techniques that enable students in massive online classes provide calibrated, open-ended feedback on each others' assignments. He will share the surprising robustness of this technique at grading thousands of students on open-ended work such as design projects and at providing them with personalized feedback. He will also touch on some in-progress work on providing deeper qualitative feedback through peers.
Chinmay Kulkarni is a PhD student in Stanford’s Computer Science department, advised by Professors Scott Klemmer and Michael Bernstein. Chinmay’s research focuses on peer processes in massive online learning. Before starting at Stanford, Chinmay worked at Microsoft Research India on projects that enabled tools for end-user interactive storytelling, and on search technology for Bing.