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Research And Implementation Of Learning Status Early Warning System Based On Mobile Teaching APP

Posted on:2020-06-24Degree:MasterType:Thesis
Country:ChinaCandidate:Z P WangFull Text:PDF
GTID:2428330575487083Subject:Software engineering
Abstract/Summary:PDF Full Text Request
With the rapid development of information technology,especially wireless Internet,mobile terminal applications have become an integral part of people's daily life.Mobile terminal applications provide new opportunities for higher education.The application of mobile education has a strong impact on the traditional classroom teaching mode and concept,especially the continuous promotion and influence of the concept of teaching and the concept of "Internet + education",which makes the new mobile teaching mode gradually improve,and a large number of educational APP appear on the market,such as "Net Ease cloud classroom" and "fluent reading".Throughout these educational APPs,we will find that most of these educational APPs are online,that is,teachers and students only interact online.For College students,most of their study time is in the traditional classroom,and students will produce a large number of behavior data in the traditional classroom.Collecting and data mining these data,analyzing the correlation between the data,and then feeding back the discovered rules to the traditional classroom will help to assist teachers in teaching and improve the quality of teaching.Help.Based on the prototype development of the "Flip Classroom" mobile teaching assistant system software,this paper redesigns the software and develops it across platforms,adding the functions of "homework publishing" and "classroom testing".This software aims to use an APP to realize the traditional teaching method and obtain the behavior data of students' users.Then,on the basis of data acquisition by the software of the "Flip Classroom" Mobile Instruction Assistant System,an early warning system for students' learning state is designed and developed.The idea of machine learning is introduced.The data are mined and analyzed by using Adaboost machine learning algorithm,and the students' recent learning state is predicted to achieve the effect of academic early warning.Finally,the early warning results are displayed to teachers and classmates.At the same time,it can also provide data reference for teachers to adjust teaching plans.This paper presents a learning status early warning system based on mobile teaching APP.In the process of putting it into use,students and teachers have good feedback.The application of the system improves the teaching quality and efficiency of teachers,at the same time gives students learning warnings,and promotes students to better engage in learning,to meet the needs of the system design.
Keywords/Search Tags:Flipping Class, Student Warning, Teaching Assistance, Adaboost
PDF Full Text Request
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