DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Jong-Hwan | - |
dc.contributor.advisor | 김종환 | - |
dc.contributor.author | Kim, Woo-Hyun | - |
dc.date.accessioned | 2021-05-12T19:40:37Z | - |
dc.date.available | 2021-05-12T19:40:37Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=909408&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/284180 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 전기및전자공학부, 2020.2,[v, 57 p. :] | - |
dc.description.abstract | In recent years, in the field of education technology, artificial intelligence tutors have come to be expected to provide individualized educational services to help learners achieve high levels of academic success. To this end, AI tutors need to be able to understand the current status and preferences of a learner and then suggest appropriate learning contents accordingly. However, it is challenging to monitor learner status and preferences continually and to recommend appropriate educational services. In this paper, we propose an individualized AI tutor as an integrated system of three developmental learning networks (DLNs) by extending a deep adaptive resonance theory (Deep ART) network, a neural network capable of incremental learning. Specifically, the learner status DLN is able to easily add new input channels about learner status without disrupting existing classifiers. The learner preference DLN is to categorize learner preferences based on frequency as well as sequence of events. The learner experience DLN is updated to immediately reflect alteration of the educational effectiveness in the current classification. Our AI tutor is currently embedded in a commercialized mobile application for teaching the Korean language to children. Experimental results show that the AI tutor application efficiently helps children learn the Korean language. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | adaptive resonance theory▼aartificial intelligence tutor▼aindividualized education▼amachine learning▼aonline mobile application | - |
dc.subject | 적응 공명 이론▼a인공지능 교사▼a개별화 교육▼a기계 학습▼a온라인 모바일 어플리케이션 | - |
dc.title | Individualized AI tutor based on developmental learning networks | - |
dc.title.alternative | 발달 학습 네트워크에 기반한 인공지능 개별 교사 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전기및전자공학부, | - |
dc.contributor.alternativeauthor | 김우현 | - |
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