Classroom Participation Marginalization Diagnosis And Strategy Intervention Of College Students From The Perspective Of Learning Analytics

"Knowledge comes from information,and information comes from data." Learning analysis uses "big data" as a research tool to mine,analyze,characterize,understand,and serve learning from the perspective of big data to make learning happen.Class participation is a tool and method for cultivating students' conceptual understanding,reflecting students' cognitive and emotional investment level,and is an effective guarantee for deep learning.Therefore,we should pay close attention to how to create,share and exchange course content by using new technologies such as Web2.0,how to interpret the mechanism of students' marginalized classroom participation,and how to use learning analysis technology to measure students' participation comprehensively and accurately.On the basis of combing and summarizing relevant documents at home and abroad,this study determines the attributes of classroom participation behavior and the measurement method of attribute values,and performs matrix representation of the number of behavior participation,explores the quality of education from the original perspective,and gains insights into students' classroom participation;Through interviews and questionnaires,using correlation analysis and multiple regression methods,we found six specific variables that affect students' classroom participation: weak foundation,worry about making mistakes,abstract content,fast lectures,habit of independent learning,and embarrassment.According to the factors and relevant theories,it is considered that the marginalization of classroom participation is due to the deep-rooted Chinese traditional culture,the lack of adequate pre class preparation,the neglect of oral English goals,the introverted and reticent personality,the vicious circle of negative participation,the teachers' inadequate control of the classroom rhythm,the inhibition of the negative reactions of the partners and the increasing complexity of the knowledge system are the marginalization of classroom participation.Based on the crowdsourcing platform Wisemapping,combined with self-organization theory and knowledge construction theory,a crowdsourcing self-organizing collaborative knowledge construction intervention model was proposed.Taking the students majoring in educational technology in a university as the research object,a ten week intervention study is conducted.The results show that the model can significantly improve students' academic performance.The knowledge organization behavior pattern shows that students actively participate in the classroom,create more interesting and meaningful learning experience,and invest more intelligence level,effort,attention,persistence and positive behavior in learning activities,learning is a social and communicative process.Knowledge mapping and social network analysis show that students put forward a lot of questions and ideas,thinking becomes clear,the elaboration of the argument is deepened layer by layer,each student can learn in the most suitable way for themselves.It seems that the social interaction through the crowdsourcing platform Wisemapping has fundamentally changed their entire classroom participation restrictions,and fundamentally increased the interaction opportunities of students.The research results can help to improve the participation and knowledge level of college students,and then improve the learning and teaching effect.