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Titlebook: Artificial Intelligence in Education and Teaching Assessment; Wei Wang,Guangming Wang,Baoju Zhang Book 2021 The Editor(s) (if applicable)

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發(fā)表于 2025-3-21 19:29:07 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Artificial Intelligence in Education and Teaching Assessment
影響因子2023Wei Wang,Guangming Wang,Baoju Zhang
視頻videohttp://file.papertrans.cn/163/162450/162450.mp4
發(fā)行地址Introduces the research results of artificial intelligence technology in education and teaching.Presents a comprehensive study of text, language, video, and other aspects of artificial intelligence te
圖書封面Titlebook: Artificial Intelligence in Education and Teaching Assessment;  Wei Wang,Guangming Wang,Baoju Zhang Book 2021 The Editor(s) (if applicable)
影響因子This book collects papers on education quality assessment based on AI technology and introduces the latest research direction and progress of AI technology in the field of education and teaching, including classroom teaching quality assessment, online education quality assessment, teaching reflection quality assessment, etc. This book promotes the application of artificial intelligence technology in the field of education and teaching, effectively improving the quality of education and teaching. Researchers in artificial intelligence technology, teachers, students, and others benefit from this book.
Pindex Book 2021
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沙發(fā)
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https://doi.org/10.1007/978-3-030-52437-1bout the results. The fifth part is a?summary. The collected data set is used to train each kind of learner, and then the evaluation criteria are used to compare each kind of learner horizontally, and to analyze the advantages and disadvantages of each learner in the teacher award prediction problem
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https://doi.org/10.1007/978-3-030-52437-1ing ability, humanistic, scientific and technological literacy, learning and development ability, and research and innovation ability. Phase of studying had a large effect on teachers’ qualities and abilities, while urban/rural had only a small effect. As the most prominent differences, teacher educ
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發(fā)表于 2025-3-22 22:43:53 | 只看該作者
Classroom Teaching Behavior Analysis Based on Artificial Intelligence, recognition, we fused Mini-XCEPTION network model and the LSTM network model, by extracting features of speech mel-spectrogram, real-time analysis of changes in the classroom atmosphere. Through the final analysis results, teachers can fully grasp the classroom dynamics, create positive emotional c
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Research on the Influence of Quantity and Emotion of Danmaku in Online Instructional Video on Learntions. (2) In terms of learning effects: instructional videos with a large number of bullet comments could significantly improve learners’ retention test scores, transfer test scores and total test scores. (3) Correlation analysis results showed that: the more positive emotion a learner experiences,
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