Tang Ming, Sun Yutong, Chen Jiajun, Zhong Qianyi
Department of Educational Technology, College of Humanities and Education, Foshan University, Foshan, 523800, China
In order to explore the problems in technology path, social value and key technologies of intelligent teaching system in the era of artificial intelligence 2.0, this paper takes four modules of intelligent teaching system in the era of artificial intelligence 2.0 as objects , and discusses the application path and social value of intelligent teaching system, and carries out in-depth research on the key technologies of natural language processing, question answering system, expression recognition and educational data mining corresponding to the four modules. This paper also analyzes the status, role and development trend of four key technologies in the application and development process of intelligent teaching system in the era of artificial intelligence 2.0. The research in this paper can provide the basis for the development and application of intelligent teaching system in the era of artificial intelligence 2.0, and promote the better integration and development of new information technology and education & teaching.
artificial intelligence 2.0; intelligent teaching system (ITS); social value technology Path; key technology
Tang Ming, Sun Yutong, Chen Jiajun, Zhong Qianyi. Analysis and Research on Technology Path, Social Value and Key Technologies of Intelligent Teaching System in the Age of Artificial Intelligence 2.0. Frontiers in Educational Research (2021) Vol. 4, Issue 6: 43-49. https://doi.org/10.25236/FER.2021.040609.
 Chen Tianyun, Zhang Jianping. Research status of Intelligent teaching system (ITS) and ITS development in China [J]. China audio visual education, 2007, (02): 95-99.
 Yan Y U, Yu-Xi L, Xiao-Hong Y U, et al. Prospect on intelligent teaching system under educational artificial intelligence [J]. Heilongjiang Science,2019.
 Lin H, Xie S, Xiao Z, et al. Adaptive Recommender System for an Intelligent Classroom Teaching Model [J]. International Journal of Emerging Technologies in Learning (iJET), 2019, 14 (05).
 Rathore A S, Arjaria S K. Intelligent Tutoring System[M]. Utilizing Educational Data Mining Techniques for Improved Learning. 2020.
 Wu L. Student model construction of intelligent teaching system based on Bayesian network[J]. Personal and Ubiquitous Computing, 2020, 24(3):419-428.
 Yang Y. Research on Modeling and Simulation of Agent-based Intelligent Teaching System[J]. 2020.
 Man-Fei Q I, Dong-Mei H, Wan-Sen W. Research on intelligent teaching system based on web and data-mining[J]. Computer Engineering and Design, 2008.
 Latham A, Crockett K, Mclean D. An adaptation algorithm for an intelligent natural language tutoring system [J]. Computers & Education, 2014, 71(feb.):97-110.
 Shen H, Liu G, Wang H, et al. Social Q&A: An Online Social Network Based Question and Answer System [J]. IEEE Transactions on Big Data, 2016, PP (99):1-1.
 Xingjing D U, Ling X U, Department C. Analysis of Micro-expression Recognition Technology[J]. Computer & Digital Engineering, 2017.