Research And Implementation Of CSCL Platform

With the rapid development of computer technology,the increasing needs of learners cannot be met by traditional style of learning alone.The learning environment which relies on the computer technology can provide learners with rich learning resources and intelligent interaction.Therefore,more and more learners prefer online learning platforms such as CSCL(Computer Supported Collaborative Learning).As a collaborative learning platform,how to closer the cooperation among learners,how to enhance their teamwork ability and self-learning awareness,and how to make full use of the resources to help learners study better are always the research hot spots of CSCL.A CSCL platform is designed from the perspective of Person-Post matching.Firstly,we analyzes the overall requirements of the platform,and completes the platform function and database design.Then,based on thepe rsonal ability and note preference of learners,the learner model is established.After that,according to the talent division mechanism,we constructs five roles of the learning group.Then,based on the learner model,we improves the K-means algorithm for the automatic grouping of learners.In view of the features of learning notes,such as timeliness and academic,we define three main features:academic relevance,preference relevance and social relevance,and design a note recommendation algorithm that combines multidimensional features.Finally,this CSCL platform is established by MVC architecture with MyEclipse,and some functions are designed,like automatic grouping,task management,recommendation of study notes,online testing,learning effect evaluation and others.The CSCL platform has been tested,the functions have reached the expected goals.The CSCL platform provides a learner-centric collaborative learning environment,enhances the enthusiasm of the team members by the form of Person-Pos matching,and gives full play to learners'personal characteristics.It achieves the goal of improving learners'learning effectiveness and reducing burdens for teachers.Considering that the number of platform users will continue to increase,the next step of the research is to use the big data computing model to reduce the computational time of the platform and further solve the cold-start problem of the grouping algorithm.