Research On The Process Analysis Method And Application Of Collaborative Knowledge Construction In Teacher Workshop

At present,a new round of scientific and technological and industrial revolution is taking shape.The wave of new technologies,represented by AI,VR and 5G,is pushing forward industrial change,technology update and post change.Educational institutions and departments are constantly exploring the potential advantages of AI,big data and other technologies,actively expanding channels to improve learning quality,and trying to cultivate innovative talents with innovative education.The emergence of new technology also puts forward higher requirements for teachers’ professional knowledge and skills,and reshapes the way of teachers’ professional development.Teachers’ online learning community provides a distributed and flexible learning environment,which weakens the limitation of time and region,and provides convenience for teachers’ autonomous learning and communication.Teacher workshop is an effective form of network learning,which can effectively support teachers to carry out collaborative discussion,and promote the development of collaborative knowledge construction,problem solving and higher-order thinking.However,in the process of network training,there are still some problems,such as insufficient user participation,weak knowledge sharing and communication atmosphere,lack of effective guidance from organizers,and insufficient depth of discussion on Problems and knowledge.The real-time analysis and monitoring of the learning process will be conducive to the regulation and intervention of the learning process,and promote the improvement of the learning quality.This study attempts to use artificial intelligence technology to dynamically track the interactive behavior and the change of discussion topics in the process of learning,so as to provide scientific and effective data support for the real-time monitoring,intervention and adjustment of the learning process.This research is mainly carried out from the following four aspects:Firstly,the analysis model of collaborative knowledge construction process in teacher workshop is constructed.Based on the in-depth understanding of the learning characteristics and collaborative knowledge construction theory of teacher workshop,combined with the technical characteristics of artificial intelligence,this paper constructs a multi perspective,technology enhanced collaborative knowledge construction process analysis model and framework in teacher workshop.This paper discusses the importance of analyzing and interpreting the process of collaborative knowledge construction in teacher workshops from the perspectives of teaching interaction theory and idea improvement theory.It also discusses the feasibility of using artificial intelligence technology to realize the automatic coding of knowledge construction behavior and the mining and evolution analysis of discussion topics.It provides an important theoretical support for the realization,result analysis and application of the method.Secondly,it explores the analysis method of knowledge construction behavior intelligence in teacher workshop.It is an important method to analyze the interaction of collaborative knowledge construction process by analyzing the knowledge construction behavior and the behavior sequence generated by the post.In order to realize the dynamic tracking and analysis of knowledge construction behavior in Teachers’ workshops,this study draws on the method of text classification,analyzes the relevant characteristics of network research activities,and combines with the relevant principles of code table construction and the relevant requirements of classification model training for data sets,designs and creates the "coding scheme of knowledge construction behavior of teachers’ workshop".Based on the coding scheme,the data set is coded and used as the training set to construct the classification model.By extracting the text LIWC features of the training set and the discussion situation features,the feature space is greatly compressed.In the experimental stage,SMOTE method is used to balance the training set,and the parameters of the random forest algorithm are adjusted and optimized,and a better classification model is obtained.The model is applied to cross context test data sets,and good classification results are achieved.In addition,the importance analysis of features in random forest algorithm is used to further deepen the understanding of collaborative knowledge construction process in teacher workshop through the analysis of post related features.Based on the results of automatic coding,we can quickly analyze the behavior sequence of knowledge construction,and bring more convenience to the use of lag sequence analysis method.Thirdly,it explores the analysis method of topic evolution in teacher workshop.In the process of collaborative knowledge construction,the growth and change of learning community topics reflect the improvement and development process of ideas.This paper explores the analysis method of topic evolution in teacher workshop.By constructing the framework of topic evolution analysis in teacher workshop,the integrated analysis process from data acquisition,topic mining and analysis to result application is realized in teacher workshop.In the experimental process,LDA topic modeling method is used to find the hidden topic structure and content in the data set;the topic similarity calculation is used to identify and establish the correlation between topics,and then deduce the evolution of topics in the process of collaborative knowledge construction.Through the analysis of the calculation results,the improvement of the ideas and the development process of the teacher learning activities are well reflected,and the effect of the method is verified.Finally,the teaching application of the analysis method.In this paper,knowledge construction behavior analysis technology and opinion evolution analysis technology in teacher workshop are combined with metacognition theory and learning intervention theory,and applied to the teacher learning activities.Further explore the method of combining technology with theory.By using the automatic coding analysis method and lag sequence analysis method of knowledge construction behavior in teacher workshop,we can obtain the interaction behavior sequence of teachers and the interactive behavior transformation in each stage of teacher learning activities;by using the topic evolution analysis method,we can obtain the evolution of topic content in teacher workshop.The visualization of the experimental results provides support for the teacher’s personal metacognitive process and the sharing and adjustment of the teacher’s workshop.In addition,by combining the theory of teaching intervention in the process of collaborative knowledge construction with the analysis results,this paper puts forward the possible intervention opportunities and discovery methods in the process of collaborative knowledge construction of teachers’ workshops,so as to improve the scientificity and accuracy of the intervention in the process of teacher learning and training,so as to improve the quality of teacher learning and promote the professional development of teachers.