<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-26T20:24:17Z</responseDate><request verb="GetRecord" identifier="oai:uvadoc.uva.es:10324/24890" metadataPrefix="mods">https://uvadoc.uva.es/oai/request</request><GetRecord><record><header><identifier>oai:uvadoc.uva.es:10324/24890</identifier><datestamp>2021-06-23T13:29:26Z</datestamp><setSpec>com_10324_1191</setSpec><setSpec>com_10324_931</setSpec><setSpec>com_10324_894</setSpec><setSpec>col_10324_1381</setSpec></header><metadata><mods:mods xmlns:mods="http://www.loc.gov/mods/v3" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
<mods:name>
<mods:namePart>Bote Lorenzo, Miguel Luis</mods:namePart>
</mods:name>
<mods:name>
<mods:namePart>Gómez Sánchez, Eduardo</mods:namePart>
</mods:name>
<mods:extension>
<mods:dateAvailable encoding="iso8601">2017-08-17T11:09:40Z</mods:dateAvailable>
</mods:extension>
<mods:extension>
<mods:dateAccessioned encoding="iso8601">2017-08-17T11:09:40Z</mods:dateAccessioned>
</mods:extension>
<mods:originInfo>
<mods:dateIssued encoding="iso8601">2017</mods:dateIssued>
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<mods:identifier type="citation">Bote-Lorenzo, M.L.,  Gómez-Sánchez, E. Predicting the decrease of engagement indicators in a MOOC.  Proceedings of the 7th International Conference on Learning Analytics and Knowledge, LAK 2017, 143-147, Vancouver, Canada, March 2017</mods:identifier>
<mods:identifier type="uri">http://uvadoc.uva.es/handle/10324/24890</mods:identifier>
<mods:identifier type="doi">10.1145/3027385.3027387</mods:identifier>
<mods:abstract>Predicting the decrease of students’ engagement in typical MOOC tasks such as watching lecture videos or submitting assignments is key to trigger timely interventions in order to try to avoid the disengagement before it takes place. This paper proposes an approach to build the necessary predictive models using students’ data that becomes available during a course. The approach was employed in an experimental study to predict the decrease of three different engagement indicators in a MOOC. The results suggest its feasibility with values of area under the curve for different predictors ranging from 0.718 to 0.914.</mods:abstract>
<mods:language>
<mods:languageTerm>eng</mods:languageTerm>
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<mods:accessCondition type="useAndReproduction">info:eu-repo/semantics/openAccess</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">http://creativecommons.org/licenses/by-nc-nd/4.0/</mods:accessCondition>
<mods:accessCondition type="useAndReproduction">Attribution-NonCommercial-NoDerivatives 4.0 International</mods:accessCondition>
<mods:titleInfo>
<mods:title>Predicting the decrease of engagement indicators in a MOOC</mods:title>
</mods:titleInfo>
<mods:genre>info:eu-repo/semantics/conferenceObject</mods:genre>
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