Korea University · Computer Science
Hyeoncheol Kim 교수의 연구실은 인공지능 기반 교육 기술 도구와 스마트 개인 보조자료의 수용성에 초점을 맞추며, 교사와 학생의 인지적·정서적 요소가 기술 수용에 미치는 영향을 심층적으로 탐구하고 있습니다. 특히 기술 수용 모델을 발전시켜 교육 현장에서의 AI 도구 활용을 위한 실질적 인사이트를 제공하고자 하며, 데이터 기반의 지능형 시스템 설계와 사용자 신뢰 형성에 초점을 맞추고 있습니다. 연구는 한국의 교육 현장에서 실제 적용 가능한 AI 솔루션의 개발과 확산을 목표로 하고 있습니다.
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Advancements in artificial intelligence (AI) have stimulated the development of educational AI tools (EAIT). EAITs intelligently assist teachers in formulating better pedagogical decisions or actions for their students. However, teachers are hardly integrating EAITs, and little is known about their perceptions of EAITs. This study seeks to identify human factors that encourage or restrict teachers’ acceptance of EAITs. We propose a revised technology acceptance model incorporating teachers’ peda
Research on converting 2D raster drawings into 3D vector data has a long history in the field of pattern recognition. Prior to the achievement of machine learning, existing studies were based on heuristics and rules. In recent years, there have been several studies employing deep learning, but a great effort was required to secure a large amount of data for learning. In this study, to overcome these limitations, we used 3DPlanNet Ensemble methods incorporating rule-based heuristic methods to lea
Ages of six volcanic and plutonic rocks on Barton Peninsula, King George Island, were determined using 40Ar/39Ar and K-Ar isotopic systems. The 40Ar/39Ar and K-Ar ages of basaltic andesite and diorite range from 48 My to 74 My and systematically decrease toward the upper stratigraphic section. Two specimens of basaltic andesite which occur in the lowermost sequence of the peninsula, however, apparently define two distinct plateau ages of 52-53 My and 119-120 My. The latter is interpreted to repr
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