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ERIC Number: EJ1248025
Record Type: Journal
Publication Date: 2020
Pages: 12
Abstractor: As Provided
ISSN: ISSN-1939-1382
Knowledge Tracing to Model Learning in Online Citizen Science Projects
Crowston, Kevin; Ă˜sterlund, Carsten; Lee, Tae Kyoung; Jackson, Corey; Harandi, Mahboobeh; Allen, Sarah; Bahaadini, Sara; Coughlin, Scott; Katsaggelos, Aggelos K.; Larson, Shane L.; Rohani, Neda; Smith, Joshua R.; Trouille, Laura; Zevin, Michael
IEEE Transactions on Learning Technologies, v13 n1 p123-134 Jan-Mar 2020
We present the design of a citizen science system that uses machine learning to guide the presentation of image classification tasks to newcomers to help them more quickly learn how to do the task while still contributing to the work of the project. A Bayesian model for tracking volunteer learning for training with tasks with uncertain outcomes is presented and fit to data from 12,986 volunteer contributors. The model can be used both to estimate the ability of volunteers and to decide the classification of an image. A simulation of the model applied to volunteer promotion and image retirement suggests that the model requires fewer classifications than the current system.
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Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Grant or Contract Numbers: 1547880