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Analysis and Improvement of Artificial Intelligence Classroom Teaching:The Collaborative Mechanism of Human in the Loop

作者:Cao Junying

院校:Hengshui University

摘要:Classroom teaching analysis is the basis for teaching improvement,and teaching improvement is the key
to improving teaching quality.The two interact and form a loop of classroom teaching research.At present,there are
difficulties in the field of artificial intelligence in classroom teaching research,such as unclear human-machine collaboration
mechanisms,weak correlation between teaching analysis and improvement,and weak guidance for teaching practice
applications.The study draws inspiration from the dual path learning and human in loop design optimization ideas of usage
theory,and proposes a"teaching structure"as the focus of classroom teaching analysis and improvement of the loop.The loop is
divided into high intervention and low intervention areas,and the collaborative mechanism of human intelligence and artificial
intelligence in the loop is discussed.Research has found that constructing a TEST II classroom teaching analysis model and
a 4A improvement model of"structural analysis,problem discovery,strategy improvement,and practical application"can form
a human-machine collaborative classroom teaching analysis and improvement mechanism in the loop,providing feasible
solutions for promoting the transformation of classroom teaching structure and improving the quality of classroom teaching.

关键词

Artificial intelligence; Classroom teaching analysis; Teaching improvement; Dual path learning; Man in the loop

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参考

Reference

[1]Sun Zhong,Lv Kaiyue,Luo Liming,Chen Meiling,Xu Lin,Shi Zhiping Analysis of Classroom Teaching Based on Artificial Intelligence[J]. China Electronic Education,2020(4):15-23. 

[2]Ministry of Education.Opinions on Strengthening and Improving the Teaching and Research Work of Basic Education in the New Era[J]. State Council Bulletin of the People's Republic of China,2020(8):69-72. 、

[3]WATANABE E,OZEKI T,KOHAMA T.Analysis of interactions between lecturers and students[C]//Proceedings of the 8th International  Conference on Learning Analytics and Knowledge.Association for Computing Machinery.New York:United States,2018:370-374. 

[4]SPREEUWENBERG R.Does emotive computing belong in the classroom[J].EdSurge,2017.

[5]ROUAST P V,ADAM M T P,CHIONG R.Deep learning for human affect recognition:Insights and new developments[J].IEEE transactions  on affective computing,2019,12(2):524-543. 

[6]Ma Yuhui,Xia Xueying,Zhang Wenhui Research on the Analysis Method of Teacher Classroom Questions Based on Deep Learning[J]. Research on Electronic Education,2021,42(9):108-114.

[7]Guo Jiong,Rong Qian,Hao Jianjiang Summary of Research on the Application of Artificial Intelligence in Teaching Abroad[J].Research onElectronic Education,2020,41(2):91-98107. 

[8]Cao Yiming,Song Yu,Zhao Wenjun,Li Mingxuan Research on the Construction of Artificial Intelligence Evaluation System for  Mathematics Classroom Dialogue in Education 2030[J]Journal of Mathematics Education,2022,31(1):7-12. 

[9]BLIKSTEIN P,WORSLEY M.Multimodal learning analytics and education data mining:using computational technologies to measure  complex learning tasks[J].Journal of learning analytics,2016,3(2):220-238. 

[10]Mou Zhijia.Multimodal Learning Analysis:New Growth Points in Learning Analysis Research[J].Research on Electronic  Education,2020,41(5):27-32,51. 

[11]MUDRICK N V.Designing adaptive intelligent tutoring systems:fostering cognitive,affective,and metacognitive self-regulated learning  processes using multimodal,multichannel process data[D].Raleigh:North Carolina State University,2018.

[12]BOSCH N,D'MELLO S K,OCUMPAUGH J,BAKER R S,SHUTE V.Using video to automatically detect learner affect in computerenabled classrooms[J].ACM transactions on interactive intelligent systems,2016,6(2):1-26. 

[13]KAPOOR A,BURLESON W,PICARD R W.Automatic prediction of frustration[J].International journal of human-computer  studies,2007,65(8):724-736. 

[14]GRAFSGAARD J F,WIGGINS J B,VAIL A K.The additive value of multimodal features for predicting engagement,frustration,and  learning during tutoring[C]//Proceedings of the 16th International Conference on Multimodal Interaction.Association for Computing  Machinery.New York:United States,2014:42-49. 

[15]EZ-ZAOUIA M,LAVOUÉE.EMODA:a tutor oriented multimodal and contextual emotional dashboard[C]//Proceedings of the Seventh  International Learning Analytics&Knowledge Conference.Association for Computing Machinery.New York:United States,2017:429-438. 

[16]Yan Hanbing,Zhao Jiabin,Wang Wei Diagnosis of classroom teaching empowered by technology:characteristics and development  space[J]Modern Distance Education,2022(2):4-11.

[17]Chris Achilles et al.Action Science:Concepts,Methods,and Skills of Exploration and Intervention[M].Beijing:Education Science  Press,2012. 

[18]Wang Ying,Wang Qiong Design and Practice of Dual Path Learning Based on Moodle-Taking Interactive Electronic Whiteboard Network  Training for Primary and Secondary School Teachers in China as an Example[J]China Electronic Education,2015(11):84-91. 

[19]Chen Xiangming,Zhao Kang From Dewey's pragmatism epistemology to see teachers'practical knowledge[J]Education  Research,2012(4):108-114.

[20]He Kekang.Theoretical Reflection on the Integration of Information Technology and Curriculum[J]Information Technology Education in  Primary and Secondary Schools,2002(Z1):27-36. 

[21]Li Runze,Zhang Yufei,Chen Haixin The evolution and development of the concept of "people in the loop"in aircraft aerodynamic  optimization design[J]Journal of Aerodynamics,2017,35(4):15. 

[22]Yang Yalian,Wang Lei,Yang Guo,Hu Xiaosong Research and development of a human driving simulation experimental system in the  loop[J]Journal of Chongqing University,2015,38(4):38-44. 

[23]Hu Qingfang Reconstruction of classroom teaching diagnosis improvement system[J].Ideological and Theoretical  Education,2009(4):41-47. 

[24]Sun Zhong,Lv Kaiyue,Shi Zhiping,Luo Liming TestII Framework:The Development Trend of Artificial Intelligence Supporting  Classroom Teaching Analysis[J].Research on Electronic Education,2021,42(2):33-39,77.

[25]GAGNÉR M.The conditions of learning[M].4th ed.New York:Holt,Rinehart&Winston,1985. 

[26]JACOBSON M J,KIM B,PATHAK Z,ZHANG B H.To guide or not to guide:issues in the sequencing of pedagogical structure in  computational model-based learning[J].Interactive learning environment,2013,23(6):715-730. 

[27]LEMAHIEU P G,BRYK A S,GRUNOW A,GOMEZ L M.Working to improve:seven approaches to improvement science in education[J]. Quality assurance in education,2017,25(1):2-4. 

[28]LANGLEY G J,MOEN R D,NOLAN K M,et al.The improvement guide:a practical approach to enhancing organizational  performance[M].2nd ed.San Francisco:John Wiley&Sons,2009.

[29]Zhong Qiquan The Characteristics of Teacher Professional Development from the Perspective of SECI Theory[J]Global Education  Outlook,2008(2):7-14.

[30]Tong Yongxin,Yuan Ye,Cheng Yurong Overview of spatiotemporal crowdsourcing data management technology research[J]Journal of  Software Science,2017,28(1):35-58. 

[31]Yang Qiang,Tong Yongxin,Wang Yansheng,Fan Lixin,Wang Wei,Chen Lei,Wang Wei,Kang Yan Overview of federated learning  algorithms in swarm intelligence[J]Journal of Intelligent Science and Technology,2022,4(1):29-44.

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