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dc.contributor.authorBurd, Hannah
dc.contributor.authorBell, Ana
dc.contributor.authorHemberg, Erik
dc.contributor.authorO'Reilly, Una-May
dc.date.accessioned2022-11-09T17:10:04Z
dc.date.available2022-11-09T17:10:04Z
dc.date.issued2020-08-12
dc.identifier.isbn978-1-4503-7951-9
dc.identifier.urihttps://hdl.handle.net/1721.1/146239
dc.publisherACM|Proceedings of the Seventh ACM Conference on Learning @ Scaleen_US
dc.relation.isversionofhttps://doi.org/10.1145/3386527.3406728en_US
dc.rightsArticle is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.en_US
dc.sourceACM|Proceedings of the Seventh ACM Conference on Learning @ Scaleen_US
dc.titleAnalyzing Pre-Existing Knowledge and Performance in a Programming MOOCen_US
dc.typeArticleen_US
dc.identifier.citationBurd, Hannah, Bell, Ana, Hemberg, Erik and O'Reilly, Una-May. 2020. "Analyzing Pre-Existing Knowledge and Performance in a Programming MOOC."
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
dc.identifier.mitlicensePUBLISHER_POLICY
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
eprint.statushttp://purl.org/eprint/status/NonPeerRevieweden_US
dc.date.updated2022-11-02T18:33:37Z
dc.language.rfc3066en
dc.rights.holderACM
dspace.date.submission2022-11-02T18:33:37Z
mit.licensePUBLISHER_POLICY
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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