66 citations · 120 across the 6 of their papers we have counts for
6 papers
Towards Teachable Conversational Agents
Nalin Chhibber, Edith Law
The traditional process of building interactive machine learning systems can be viewed as a teacher-learner interaction scenario where the machine-learners are trained by one or mo…
Using Conversational Agents To Support Learning By Teaching
Nalin Chhibber, Edith Law
Conversational agents are becoming increasingly popular for supporting and facilitating learning. Conventional pedagogical agents are designed to play the role of human teachers by…
Boomerang: Rebounding the Consequences of Reputation Feedback on Crowdsourcing Platforms
Snehalkumar, S. Gaikwad, Durim Morina +35
Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores,…
Human Perception of Surprise: A User Study
Nalin Chhibber, Rohail Syed, Mengqiu Teng +3
Understanding how to engage users is a critical question in many applications. Previous research has shown that unexpected or astonishing events can attract user attention, leading…
Prototype Tasks: Improving Crowdsourcing Results through Rapid, Iterative Task Design
Snehalkumar "Neil" S. Gaikwad, Nalin Chhibber, Vibhor Sehgal +26
Low-quality results have been a long-standing problem on microtask crowdsourcing platforms, driving away requesters and justifying low wages for workers. To date, workers have been…
Crowd Guilds: Worker-led Reputation and Feedback on Crowdsourcing Platforms
Mark E. Whiting, Dilrukshi Gamage, Snehalkumar S. Gaikwad +25
Crowd workers are distributed and decentralized. While decentralization is designed to utilize independent judgment to promote high-quality results, it paradoxically undercuts beha…