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人工智能赋能课堂教学评价改革与技术实现的框架构建
引用本文:吴立宝,曹雅楠,曹一鸣.人工智能赋能课堂教学评价改革与技术实现的框架构建[J].中国电化教育,2021(5):94-101.
作者姓名:吴立宝  曹雅楠  曹一鸣
作者单位:天津师范大学教育学部;北京师范大学数学科学学院
基金项目:国家社会科学基金“十三五”规划2017年度教育学重点课题“教师核心素养和能力建设研究”(课题编号:AFA170008);2020年天津市研究生科研创新项目“基于人工智能的数学课堂教师行为分析研究”(项目编号:2020YJSS107)研究成果。
摘    要:作为强大技术推动力的人工智能正引发着一场技术革命,推动社会步入智能时代。开展人工智能下的课堂教学评价,能够辅助智慧评价的高效开展、关注情感信息的动态变化、还原真实课堂的精准采集、实现师生成长的轨迹追踪。通过对象层、数据层、技术层和应用层四个层面的系统架构,搭建人工智能下课堂教学评价的实践路径,指向课堂语言分析、课堂行为分析、课堂情感分析与课堂教学评价体系四大应用场景。未来人工智能下课堂教学评价的深度发展与广泛应用还需探索专业化的评价指标构建、加强个性化的教师行为反馈、着眼发展性的未来教育挑战。

关 键 词:人工智能  课堂教学评价  情绪识别  教师行为

Reform and Practical Paths of Classroom Teaching Evaluation Under Artificial Intelligence
Wu Libao,Cao Yanan,Cao Yiming.Reform and Practical Paths of Classroom Teaching Evaluation Under Artificial Intelligence[J].China Educational Technology,2021(5):94-101.
Authors:Wu Libao  Cao Yanan  Cao Yiming
Institution:(Faculty of Education,Tianjin Normal University,Tianjin 300387;School of Mathematical Science,Beijing Normal University,Beijing 100875)
Abstract:As a powerful driving force of technology,Artificial Intelligence is triggering a technological revolution,which promotes the society into the era of intelligence.Carrying out classroom teaching evaluation under Artificial Intelligence can assist the efficient development of wisdom evaluation,pay attention to the dynamic changes of emotional information,restore the accurate collection of real classrooms,and realize growth trajectory tracking of teachers and students.Through the system architecture of object layer,data layer,technology layer and application layer,build the practice path of classroom teaching evaluation under Artificial Intelligence,and points to four application scenarios of classroom language analysis,classroom behavior analysis,classroom emotion analysis and classroom teaching evaluation system.In the future,the in-depth development and wide application of classroom teaching evaluation under Artificial Intelligence still need to explore the construction of professional evaluation indicators,strengthen personalized teacher behavior feedback,and focus on the developmental challenges of future education.
Keywords:Artificial Intelligence  classroom teaching evaluation  emotion recognition  teacher behavior
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