Toward a Learning Science for Complex Crowdsourcing Tasks

Author:

Doroudi Shayan1,Kamar Ece2,Brunskill Emma1,Horvitz Eric2

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

2. Microsoft Research, Redmond, WA, USA

Funder

U.S. Department of Education

Publisher

ACM

Cited by 49 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. LabelAId: Just-in-time AI Interventions for Improving Human Labeling Quality and Domain Knowledge in Crowdsourcing Systems;Proceedings of the CHI Conference on Human Factors in Computing Systems;2024-05-11

2. Explaining crowdworker behaviour through computational rationality;Behaviour & Information Technology;2024-04-24

3. Enhancing Procedural Writing Through Personalized Example Retrieval: A Case Study on Cooking Recipes;International Journal of Artificial Intelligence in Education;2024-04-22

4. OSINT Research Studios: A Flexible Crowdsourcing Framework to Scale Up Open Source Intelligence Investigations;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

5. Bridging Learnersourcing and AI: Exploring the Dynamics of Student-AI Collaborative Feedback Generation;Proceedings of the 14th Learning Analytics and Knowledge Conference;2024-03-18

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