Design And Implementation Of A Mobile Campus Service Platform Based On Hybrid Model

With the development of Internet and communication technology,and the popularization of mobile terminals,it is an irresistible trend to expand the original digital campus based on PC terminal and develop campus mobile service platform anytime anywhere.Mobile campus applications make information transmission more accurate and efficient,and improve the efficiency of work and study and the feeling of life experience.To build a mobile campus platform,the first step is to solve the technical problems in the face of various types of mobile terminals.Based on reading a large number of literatures,the advantages and disadvantages of the existing several kinds of development patterns,which included web development model,original development model and hybrid model,were analyzed synthetically.The hybrid model was selected to develop the mobile campus application program,because the portability,integrity and good original experience of mobile applications was settled by the Phonegap framework,at the same time,its external interface and plug-ins were expanded in technology.The major functional modules of the platform were determined by iterative surveys and massive questionnaires in the early stage of the project.The original PC functions such as office services,grade management,course selection and course management,all-in-one card,library,work-study and so on were transplanted in mobile terminal,as well as the information release,information inquiry,appointment and other daily services involving teachers and students were implemented.In addition to that,the ancillary function of identification of poor students based on whole connection neural network was added in the work-study module innovatively.Finally,the platform was tested in interface,function,compatibility and other aspects,reaching the expected value.The overall architecture of the mobile campus service platform was mainly included of the server side and the campus application client side.The server side adopted Java EE lightweight framework of SSM with a relatively mature Mysql database for data storage,and the front-end technology adopted HTML5 based on the Phonegap framework.The ancillary function of identification of poor students was based on students’ relevant data about the consumption behavior,study situation and family status,which was the characteristic function in application.The prediction model was achieved by training whole connection neural network using Tensor Flow.The whole process composed of data sampling,data modeling,model training and model estimating was applied into identification of poor students,which was more accurate,scientific and objective than traditional identification of poor students.