A Free and Open Dataset from a Prototypical Data-driven Study Assistant in Higher Education

DC ElementWertSprache
dc.contributor.authorSchrumpf, J.
dc.contributor.authorWeber, F.
dc.contributor.authorSchurz, K.
dc.contributor.authorDettmer, N.
dc.contributor.authorThelen, T.
dc.contributor.editorCukurova, M.
dc.contributor.editorRummel, N.
dc.contributor.editorGillet, D.
dc.contributor.editorMcLaren, B.
dc.contributor.editorUhomoibhi, J.
dc.date.accessioned2023-02-17T12:15:23Z-
dc.date.available2023-02-17T12:15:23Z-
dc.date.issued2022
dc.identifier.isbn9789897585623
dc.identifier.issn2184-5026
dc.identifier.urihttp://osnascholar.ub.uni-osnabrueck.de/handle/unios/65945-
dc.descriptionConference of 14th International Conference on Computer Supported Education, CSEDU 2022 ; Conference Date: 22 April 2022 Through 24 April 2022; Conference Code:183566
dc.description.abstractDigital study assistants (DSAs) are an as of yet sparsely explored method to build bridges between classical, on-campus higher education and novel digital education opportunities. The DSA we present in this paper (SIDDATA) aims at supporting students to identify, reflect upon and follow their personal educational goals. Over the course of 11 months, students interacted with a prototype version 2.0 of the software, generating data about what features were interacted with, users' study-related data, and which features were deemed as useful. In this data paper, we present a preprocessed version of the DSA database for research in the domain of digital higher education. We present the data model design of the DSA and its relation to its' features. We further expand on the data extraction method used to generate the present dataset from the DSA's database. We discuss potential research paths that can be explored based on the dataset as well as its limitations. Copyright © 2022 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
dc.description.sponsorshipUniversität OsnabrückUniversität Osnabrück,UOS; the University of Osnabrück, the University of Bremen, and the Leibniz University of Hannover, it is part of the “Innovationspotentiale Digitaler Hochschulbildung” (eng: Innovation Potentials in Digital Higher Education) funding line, funded by the BMBF (Bundesministerium für Bildung und Forschung, eng: Federal Ministry of Education and Research).; The authors acknowledge the financial support by the Federal Ministry of Education and Research of Germany for Siddata (project number 16DHB2124). We thank all students who donated their data.; Institute for Systems and Technologies of Information, Control and Communication (INSTICC)
dc.language.isoen
dc.publisherScience and Technology Publications, Lda
dc.relation.ispartofInternational Conference on Computer Supported Education, CSEDU - Proceedings
dc.subjectArtificial Intelligence
dc.subjectData extraction
dc.subjectDataset
dc.subjectDigital Study Assistant
dc.subjectE-learning
dc.subjectEducation computing, Data driven
dc.subjectEducational goals
dc.subjectEducational recommendation engine
dc.subjectEducational Recommendation Engines
dc.subjectHigh educations
dc.subjectHigher Education
dc.subjectModeling designs
dc.subjectPrototype versions
dc.subjectUser study, Students
dc.titleA Free and Open Dataset from a Prototypical Data-driven Study Assistant in Higher Education
dc.typeconference paper
dc.identifier.doi10.5220/0011038800003182
dc.identifier.scopus2-s2.0-85133160914
dc.identifier.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85133160914&doi=10.5220%2f0011038800003182&partnerID=40&md5=d98f92009228bd0682d7d42bd1e2139b
dc.description.volume2
dc.description.startpage155
dc.description.endpage162
dcterms.isPartOf.abbreviationInternational Conference on Computer Supported Education, CSEDU - Proceedings
crisitem.author.deptZentrum VirtUOS-
crisitem.author.deptidorganisation31-
crisitem.author.orcid0000-0002-3337-6093-
crisitem.author.parentorgUniversität Osnabrück-
crisitem.author.netidThTo467-
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