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Neural Network Construction Practices in Elementary School

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dc.contributor.authorShamir, Gilad
dc.contributor.authorLevin, Ilya
dc.date.accessioned2021-10-04T12:29:01Z
dc.date.available2021-10-04T12:29:01Z
dc.date.issued2021
dc.description.abstractThis paper describes an artificial intelligence (AI) educational project conducted with a small number of 12-year-old students. It is a preliminary step to add AI learning in a city-wide program consisting of elementary school students who learn computational thinking and digital literacy. Today children grow up in an age of AI which significantly affects how we live, work, and solve problems therefore AI should be taught in schools. Children usually employ AI models as black boxes without understanding the computational concepts, underlying assumptions, nor limitations of AI models. The hypothesis of this study is that to understand how machines learn, students should actively construct a neural network. To address this issue a dedicated curriculum and appropriate scaffolds were created for this study. It includes a programmable learning environment for elementary school students to construct AI agents. Findings show high engagement during the constructionist learning and that the novel learning environment helped make machine learning understandable.de
dc.identifier.doi10.1007/s13218-021-00729-3
dc.identifier.pissn1610-1987
dc.identifier.urihttp://dx.doi.org/10.1007/s13218-021-00729-3
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37482
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 35, No. 2
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectArtificial intelligence
dc.subjectConstructionism
dc.subjectElementary school
dc.subjectMachine learning
dc.subjectProgramming
dc.titleNeural Network Construction Practices in Elementary Schoolde
dc.typeText/Journal Article
gi.citation.endPage189
gi.citation.startPage181

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Künstliche Intelligenz 35(2) - Juni 2021