A Comparative Study Of Teacher-Student Interaction Behavior In Primary School Mathematics Classroom Under Intelligent Envionment

With the rapid development of information technology,smart classroom has become an important development trend of modern education.Supported by information technology and with education and teaching as the core,the smart classroom organically combines digitalization,networking,wisdom,personalization and humanistic care,forming a new type of education and teaching mode.Under the environment of smart classroom,mathematics teaching also faces great opportunities and challenges,especially elementary school mathematics teaching.Therefore,it is particularly important to study the classroom teacher-student interaction behaviors of elementary school mathematics teachers in the smart classroom environment and to investigate the reasons behind them.The purpose of this study is to examine and compare the teacher-student interaction behaviors in elementary school mathematics classrooms in a smart learning environment,focusing on the comparative study of novice teachers and expert teachers in classroom interactions in a smart classroom context.Therefore,a total of 20 classroom cases were selected for the study,covering both novice and expert teachers.The cases were carefully selected to represent a variety of teaching methods,student populations,and levels of technology integration.Based on a review of the literature,this paper uses the ITIAS coding system to analyze the classroom videos.The system was used to study four aspects of classroom interaction: classroom climate,teacher-student interaction,student-student interaction,and human-technology interaction.Each aspect includes corresponding behavioral indicators for a detailed analysis of classroom interactions.In this paper,20 classroom instructional case videos were selected from a variety of instructional settings,experiences,and levels of technology integration.Data Analysis: Once the videos were coded,computer vision techniques were used to analyze classroom instructional climate,teacher-student interactions,student-student interactions,and human-technology interactions.This analysis involved quantifying the frequency,duration,and sequence of various behavioral indicators,as well as identifying any patterns or trends in the data.The study revealed that novice teachers often have a lack of self-confidence,tend to exhibit control,and show a lack of reflective practice in classroom interactions.These characteristics hinder their ability to engage effectively with learners and make the most of the potential of an intelligent learning environment.In contrast,expert teachers have a deeper understanding of the subject matter and possess greater pedagogical experience,which enables them to foster a supportive and interactive learning climate.In addition,they have demonstrated excellence in integrating technology into their pedagogy and adapting to the changing requirements of intelligent learning environments.At the same time,it is important to note that both novice and expert teachers encounter challenges related to knowledge and experience,cognitive and verbal expression,and psychological and emotional factors.Addressing these challenges is essential to enhance teacher-student interaction and to improve the overall effectiveness of the teaching and learning process in an intelligent learning environment.Finally,conclusions are drawn from the findings and recommendations are provided for enhancing teacher-student interactions in intelligent learning environments.These recommendations include improving teacher training,developing more effective teaching strategies,and optimizing the use of technology in the classroom.In summary,this study provides valuable insights into teacher-student interaction in elementary mathematics classrooms in an intelligent learning environment.By comparing the practices of novice and expert teachers,the study highlights the importance of effectively integrating technology and fostering a supportive classroom climate to facilitate meaningful interactions.The findings and recommendations of this study can serve as a guide for educators,policy makers,and other stakeholders interested in improving the quality of teaching and learning in the era of smart learning environments.