Sharon Zhou, PhD

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Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores, which make high-quality work and workers difficult to find, stem from social pressure to avoid giving negative feedback. We introduce Boomerang, a reputation system for crowdsourcing that elicits more accurate feedback by rebounding the consequences of feedback… Mehr zeigen

[See paper for additional authors and ordering]
Paid crowdsourcing platforms suffer from low-quality work and unfair rejections, but paradoxically, most workers and requesters have high reputation scores. These inflated scores, which make high-quality work and workers difficult to find, stem from social pressure to avoid giving negative feedback. We introduce Boomerang, a reputation system for crowdsourcing that elicits more accurate feedback by rebounding the consequences of feedback directly back onto the person who gave it. With Boomerang, requesters find that their highly rated workers gain earliest access to their future tasks, and workers find tasks from their highly-rated requesters at the top of their task feed. Field experiments verify that Boomerang causes both workers and requesters to provide feedback that is more closely aligned with their private opinions. Inspired by a game-theoretic notion of incentive-compatibility, Boomerang opens opportunities for interaction design to incentivize honest reporting over strategic dishonesty. Weniger anzeigen

Ingenium uses abstract puzzle blocks to communicate grammatical concepts. Engaging students in grammatical reflection, Ingenium succeeds when students are able to effectively decipher the meaning of Latin sentences. We adapted Ingenium to be used for two standard classroom activities: sentence translations and fill-in-the-blank exercises. We evaluated Ingenium with 67 novice Latin students in universities across the United States. When using Ingenium, participants opted to perform more optional… Mehr zeigen

Ingenium uses abstract puzzle blocks to communicate grammatical concepts. Engaging students in grammatical reflection, Ingenium succeeds when students are able to effectively decipher the meaning of Latin sentences. We adapted Ingenium to be used for two standard classroom activities: sentence translations and fill-in-the-blank exercises. We evaluated Ingenium with 67 novice Latin students in universities across the United States. When using Ingenium, participants opted to perform more optional exercises, completed translation exercises with significantly fewer errors related to word order and errors overall, as well as reported higher levels of engagement and attention to grammar than when using a traditional text-based interface. Weniger anzeigen