인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
개인구독
소속 기관이 없으신 경우, 개인 정기구독을 하시면 저렴하게
논문을 무제한 열람 이용할 수 있어요.
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
In the post-epidemic era, some colleges and universities in China are still semi-closed. Some courses have adopted a mixed online and offline teaching model. This study attempts to solve the problem that Chinese painting online education is challenging to integrate into emotional education. In particular, this paper proposes an emotion-oriented hybrid-teaching model(Ed note: Compound adjectives that modify a noun are typically hyphenated but not when the first word of the adjective is an adverb ending with “-ly.”) based on an improved convolutional neural network (CNN). This mode can recognize students" movements and expressions online to judge their emotional state and improve the effectiveness of online teaching. After combining the mixed teaching mode and existing research on action recognition, the mainstream long-term and short-term memory network and attention mechanism are ineffective for emotion classification. The research first reduces the dimensionality of the input image. It then introduces an emotion-oriented weight shift module and uses the content analysis method. The experimental results showed that the teaching model proposed in the study does not improve theoretical knowledge and learning attitude significantly, but the emotional development index and emotional development quality are 110.15% and 16.62% higher, respectively, than the general method. Compared to the general teaching method, the method proposed in the research has a better effect on emotional development.
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-ECN-0102-2023-569-001738698