Interactive Online Video Teaching System Based On Educational Agent

Online education has abundant educational resources and is not limited by time and space.It has become one of the important ways for students to acquire knowledge,playing a good role during the epidemic and also helping to solve the problem of lack of educational resources in remote mountainous areas and other areas.Compared to traditional offline education where teachers and students can interact and communicate naturally face-to-face,current online education usually only plays recorded teaching videos,lacking teacher-student interaction,often resulting in students’ lack of concentration and enthusiasm for learning,making it difficult to guarantee learning outcomes.Although online classes such as Tencent conferences can solve the above problems to some extent,it is necessary to organize teachers and students to attend classes on time in advance.For those who are not very free in time,they cannot independently arrange classes according to their own time.It is worth researching whether various teaching materials can be recorded in advance,and the system can selectively play the content based on students’ learning situation.This article preliminarily explores the introduction of the concept of educational agents to solve the above problems.For this purpose,this article has developed an interactive online video teaching system based on educational agents.The system arranges courses for students according to their mastery of the course and learning progress,and monitors their learning status in real-time during the learning process.After the course is completed,the learning effect of students is detected,and students are supported to interact with the system,thereby improving learning efficiency.This article first conducts a requirement analysis,outline design,and detailed design of an interactive online video teaching system based on educational agents.In the requirements analysis section,the requirements of the interactive online video teaching system based on educational agents were analyzed,the system overview was summarized,and the functional and non functional requirements of the interactive online video teaching system based on educational agents were described;In the summary design section,the physical devices used in the interactive online video teaching system based on educational agents,the system architecture design,the system functional architecture design,and the system functional modules are described;In the detailed design section,the logical design of the system functional modules and the functions of each module were described.Then,this article implements and tests the system based on the above analysis and design.The system includes two parts:the teaching system client and the cloud management platform.When students open the teaching system client,an intelligent agent teacher will guide them throughout the learning process,arrange courses for students,supervise their learning,arrange exercises for students after class,and finally record their learning situation to generate a learning report for this study.This system can create a learning atmosphere for students,improve their learning focus and effectiveness.After completing their studies,students can receive feedback on their learning outcomes timely and grasp the learning process.The resources in the system are stored on cloud servers,and administrators can use the cloud management platform to manage system resources.They can also manage course resources,exercise resources,and users in the system.The main functional modules of the teaching system client include:login and registration module,course learning module,learning status monitoring module,exercise module,learning record module,and coordinate mapping module.The main functional modules of the cloud management platform include:login module,course management module,exercise management module,and user management module.The client application of the system is developed using C#language,the front-end of the cloud management platform is developed using Vue framework,and the backend is developed using the.NET Core framework.JSON is used for communication between the front-end and back-end data.To achieve the interaction between body movements and the system,the system uses Kinect DK devices for human interaction positioning.To analyze students’ level of focus,the system uses BrainLink EEG headbands to collect users’ EEG data.To perform facial recognition login and analyze facial status,this system uses the Baidu Face AI platform.To achieve data cloud storage,the system uses Tencent Cloud Server.This article organized a comparative analysis of testing with traditional video teaching systems,comparing the scores of the two systems in terms of focused learning atmosphere,fatigue,learning motivation,interface quality,comprehensibility,interactivity,and personal preference indicators.The experimental results demonstrate that this system can create a better learning atmosphere for students,and to some extent the use of body action interaction can alleviate students’ learning fatigue.Compared to traditional video teaching systems,it has a better learning experience.