Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/6641
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dc.contributor.authorMoore, Steven
dc.contributor.authorNguyen, Huy
dc.contributor.authorStamper, John
dc.date.accessioned2020-07-08T23:53:49Z
dc.date.accessioned2020-07-09T04:31:07Z-
dc.date.available2020-07-08T23:53:49Z
dc.date.available2020-07-09T04:31:07Z-
dc.date.issued2020-06
dc.identifier.citationMoore, S., Nguyen, H., & Stamper, J. (2020). Crowdsourcing Explanations for Improving Assessment Content and Identifying Knowledge Components. In Gresalfi, M. and Horn, I. S. (Eds.), The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020, Volume 5 (pp. 2627-2628). Nashville, Tennessee: International Society of the Learning Sciences.en_US
dc.identifier.urihttps://doi.dx.org/10.22318/icls2020.2627
dc.identifier.urihttps://repository.isls.org//handle/1/6641-
dc.description.abstractRefining assessment items to improve their clarity and identifying the intended knowledge components required to solve them is a time-consuming task. In this study, we present the results of crowdsourcing insights into the underlying concepts of problems in mathematics and English writing, as a step towards leveraging the crowd to expedite the task. This work demonstrates a method to use the crowd’s knowledge that can lead to knowledge component identification and improved assessments.en_US
dc.language.isoenen_US
dc.publisherInternational Society of the Learning Sciences (ISLS)en_US
dc.subjectScaleen_US
dc.titleCrowdsourcing Explanations for Improving Assessment Content and Identifying Knowledge Componentsen_US
dc.typePosteren_US
Appears in Collections:ICLS 2020

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