Journal of East China Normal University(Educational Sciences) ›› 2023, Vol. 41 ›› Issue (8): 79-89.doi: 10.16382/j.cnki.1000-5560.2023.08.008

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Thinking Training Oriented: Analysis and Application of Intelligent Classroom Teaching Based on Accurate Labeling Technology

Yu Song1, Changliang Xu2, Jia Zhu3, Shaoming Chai4   

  1. 1. South China Normal University, Research Center of Artificial Intelligence and Classroom Teaching, Guangzhou 510631, China
    2. Guangzhou Overseas Chinese Foreign Language School, Guangzhou 510095, China
    3. Zhejiang Normal University, Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Jinhua 321004, China
    4. South China Normal University, International Business College, 510631, China
  • Online:2023-08-01 Published:2023-07-25


Classroom teaching is the main position of talent training. Improving the quality of classroom teaching is important to promote the high-quality development of basic education and cultivate innovative talents. This study systematically puts forward a classroom teaching evaluation system for thinking training. Based on this, an automatic labeling method of classroom teaching based on audio and video transcripts has been created. With the help of the hybrid neural network model combining CNN and BiLSTM model, the rapid and accurate annotation of large-scale classroom data is realized, which can effectively refine the thinking characteristics in classroom teaching. At the same time, sequential pattern mining technique suitable for evaluation of classroom teaching has been developed, which can reveal the sequential pattern of high-quality classroom teaching and the advanced law of implicit thinking. This paper takes a school in Guangdong Province as an example to conduct a one-year experiment. By comparing the first and last monitoring results, it is found that with the blessing of intelligent analysis technology, the proportion of classroom dialogue involving high-level thinking has been significantly increased, the thinking chain is longer, and it can reflect the law of advancing from low-level thinking to high-level thinking, Among them, the more significant long chain dialogue is the advanced mode of basic knowledge acquisition→ personal opinion expression→analysis and interpretation→summary and induction → migration and innovation. The future intelligent classroom teaching analysis should focus on the following three aspects: developing technology based on classroom dialogue analysis and multi-modal data cooperation; the selection and application of intelligent technology should serve the education and teaching objectives, so as to effectively create a high-quality and efficient class.

Key words: classroom teaching, high level thinking, intelligent technology, automatic labeling, sequential pattern mining.