In-depth Interactive Research On College Teaching Based On Smart Classroom

Smart classroom is an educational product upgraded from flipped classroom,which is a new type of classroom in the context of new education.It is a personalized and intelligent learning environment constructed with emerging technologies such as big data and cloud computing.The smart classroom incorporates more new information technologies,has diverse digital resources,and the interactive forms are more abundant.The interactive development trend of classroom teaching presents complex and diversified characteristics.This article explores the current status,degree,and characteristics of teaching interaction in smart classrooms in universities.This study used a literature review method to summarize the current status of smart classrooms,deep teaching interaction,and smart classroom teaching interaction.The concepts of smart classrooms,smart classroom teaching interaction,and teaching depth interaction were defined.Based on existing teaching interaction behavior coding systems and incorporating constructivist learning theory,Bloom’s symbol interactive theory,teaching interaction level tower theory,and Bloom’s cognitive goal classification theory,a smart classroom teaching depth interaction behavior coding framework was constructed.The framework was tested for reliability,and 10 excellent teaching cases from ordinary undergraduate colleges and universities in Guangxi Zhuang Autonomous Region in 2021-2022 were selected as research objects.Using NVIVO11 qualitative research software,the teaching cases were coded according to the smart classroom teaching depth interaction behavior coding framework,and statistical graphs were generated to analyze the operational interaction,information interaction,emotional interaction,and cognitive interaction between teachers and students.The overall situation of teaching interaction in higher education smart classrooms was obtained,and individual cases were selected for coding to generate coverage statistics graphs and coded graphs,which were analyzed in detail.Research has found that: Firstly,the smart classroom has diverse teaching and interactive forms,which reflect higher teaching efficiency.Secondly,teacher-student and student-student interactions are better in the smart classroom.Thirdly,the cognitive level of teachers and students reaches a certain depth in the smart classroom.Fourthly,the smart classroom tends to adopt a "teacher-guided,student-centered" teaching mode.Fifthly,although the smart classroom is still teacher-led,the status of students as the main body is not sufficiently reflected.Sixthly,there is a formal tendency in the use of technology by teachers and students in the smart classroom.Seventhly,the interaction between people and resource media in the smart classroom is still at a superficial level.In summary,the smart classroom in higher education can effectively promote teacher-student and student-student interactions;the teaching interaction between teachers and students has a certain depth,which is reflected in the depth interaction of cognitive interaction.The smart classroom promotes in-depth interaction through various methods such as combining multimedia resources with teaching content and interactive teaching.In interactive teaching,teachers can lead students to explore new knowledge,listen to their opinions and feedback,and adjust teaching strategies and methods in a timely manner to achieve better teaching results.The two-way interaction and communication between teachers and students effectively promote in-depth interaction.Based on research findings,four optimization suggestions are proposed for addressing the issues of teaching interaction in smart classrooms in universities: Firstly,transform the role of teachers,promote the shift from "teacher-centered" to "student-centered" classroom teaching,and enhance the student’s status as the main body.Secondly,fully explore the value of technology applications,improve the quality of technology use.Teachers can leverage innovative teaching design,develop interactive and cooperative teaching activities,provide personalized learning resources and support,and optimize teaching effects through data analysis to maximize the value of technology applications and improve student engagement and learning outcomes.Thirdly,implement the human-machine cooperation teaching mode,guide teachers and students to interact deeply with resources.Fourthly,strengthen teacher training and guidance,improve teaching level,and provide professional training courses,practical opportunities,and guidance,regular evaluations and feedback,and establish shared resource libraries to enhance the teaching level and technological literacy of teachers,and better utilize the smart classroom platform to improve teaching quality and effectiveness.The smart classroom teaching deep interaction behavior analysis coding framework constructed in this study enriches the analysis methods of teaching interaction behavior and provides ideas and methods for studying the deep interaction of smart classroom teaching in universities.However,there are several limitations.First,although the framework was completed based on the work of previous researchers and can effectively analyze operational interaction,information interaction,and emotional interaction between teachers and students,only reliability analysis was conducted on the framework.Second,since teaching interaction behavior is complex in smart classrooms,some behaviors may be difficult to accurately categorize during recording and coding,or there may be ambiguity in distinguishing similar behaviors,which may result in subjective intervention by coders that cannot be completely avoided.Third,due to time constraints and limited research ability,a small number of smart classroom teaching cases were selected and may not fully represent the teaching interaction status of smart classrooms in universities.