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Energy Consumption of AI in Education: A Case Study

dc.contributor.authorBültemann, Marlene
dc.contributor.authorRzepka, Nathalie
dc.contributor.authorJunger, Dennis
dc.contributor.authorSimbeck, Katharina
dc.contributor.authorMüller, Hans-Georg
dc.contributor.editorRöpke, René
dc.contributor.editorSchroeder, Ulrik
dc.date.accessioned2023-08-30T09:09:36Z
dc.date.available2023-08-30T09:09:36Z
dc.date.issued2023
dc.description.abstractAlthough the utilization of AI in education has grown considerably in the last decade, its environmental impact has been disregarded thus far. In this paper, we examine the energy consumption of Artificial Intelligence (AI) in education, which is employed, for instance, in adaptive learning. We measured the energy requirements of four AI implementations used on the student learning platform orthografietrainer.net. We found that two of the implementations have notably low energy and CPU demands in comparison to the baseline, while in two other implementations, these parameters are significantly higher. We conclude that more attention should be paid to whether the comparable performance of AI in education can be achieved with lower energy consumption.en
dc.identifier.doi10.18420/delfi2023-35
dc.identifier.isbn978-3-88579-732-6
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/42195
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartof21. Fachtagung Bildungstechnologien (DELFI)
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-322
dc.subjectGreen IT
dc.subjectArtificial Intelligence in Education
dc.subjectSustainable Learning Analytics
dc.titleEnergy Consumption of AI in Education: A Case Studyen
dc.typeText/Conference Paper
gi.citation.endPage224
gi.citation.publisherPlaceBonn
gi.citation.startPage219
gi.conference.date11.-13. September 2023
gi.conference.locationAachen
gi.conference.reviewfull
gi.conference.sessiontitleLearning Analytics und Künstliche Intelligenz

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