인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
The application of visualization technology in education helps to promote information technology in education and enhances learners’ ability to perceive information. Therefore, this study builds an online, self-directed learning visualization teaching system that includes a data input layer, a visualization coding layer, a logical recommendation layer, and a view presentation layer. In addition, to enhance visualization of web data, the teaching system optimizes the visual experience by using the U-Net algorithm and an immersive network with a 3D layout. The results show that for the LIME dataset test, this study’s proposed algorithm obtained the highest mean image entropy at 7.67, which is an improvement of 0.05 and 0.32 over the MBLLEN and RetinexNet algorithms, respectively. Therefore, this algorithm is more advantageous in enhancing the richness of image information. In addition, in the validation of the rationality of the online selfdirected learning model, the visualization technique was fully supported by students, helping them to adapt to the learning system quickly. This indicates that the visualization system proposed in this study is effective in improving students’ self-directed learning skills.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-25-02-090985639