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dc.contributor.authorKravčík, Milos
dc.contributor.authorSchmid, Katharina
dc.contributor.authorIgel, Christoph
dc.contributor.editorAugstein, Mirjam
dc.contributor.editorHerder, Eelco
dc.contributor.editorWörndl, Wolfgang
dc.contributor.editorYigitbas, Enes
dc.date.accessioned2020-04-27T09:35:43Z
dc.date.available2020-04-27T09:35:43Z
dc.date.issued2019
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/32330
dc.description.abstractThe raising demands on qualification increase the importance of technology as a facilitator in the educational process on the side of both receivers and providers. Beside the cognitive aspects, also metacognitive, emotional and motivational ones play a crucial role in learning. A challenge is to recognize the affective status of participants and react to them accordingly, in order to make the learning experience effective and efficient. Various approaches were investigated and reported in the literature. In order to develop mentoring support at the university level in concrete settings, we researched them and tried to identify the key requirements for our solution. Based on these requirements, we plan to design intelligent knowledge services for scalable mentoring processes.en
dc.language.isoen
dc.publisherACM
dc.relation.ispartofProceedings of the 23rd International Workshop on Personalization and Recommendation on the Web and Beyond
dc.titleTowards Requirements for Intelligent Mentoring Systemsen
dc.typeText/Conference Paper
dc.pubPlaceNew York, NY
mci.document.qualitydigidoc
mci.reference.pages19-21
mci.conference.locationHof
mci.conference.date43709
dc.identifier.doi10.1145/3345002.3349290


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