Design and implementation of web multimedia teaching evaluation system based on artificial intelligence and jQuery

Yawen SU, Guofu CHEN, Moyan LI, Tengfei SHI, Diandian FANG

Research output: Contribution to journalArticlespeer-review

3 Citations (Scopus)

Abstract

It is an important reflection of modern education and an overwhelming way to strengthen the quality of teaching. In the current environment, the traditional multimedia classroom management model can no longer adapt to the current rapidly developing network environment. How to manage more and more campus multimedia classrooms is an urgent problem to be solved. The informatization construction and application of multimedia classrooms is the key to the realization of educational informatization. The traditional multimedia classroom management model has not been able to adapt to the rapidly developing network environment, which is mainly manifested in the following aspects: electronic education management personnel cannot discover and process teaching in a timely manner. Equipment failure has not formed a set of standard troubleshooting procedures and cannot accurately record the status, use time, and maintenance records of various teaching pieces of equipment. This will not only affect the teaching quality of colleges and universities but also slow down the process of education informatization. This paper develops a web-based multimedia teaching equipment management system based on artificial intelligence and jQuery, which realizes the centralized control and management of various multimedia teaching equipment. According to the actual needs of multimedia teaching, this paper follows the design and development of software engineering, using artificial intelligence, jQuery, Ajax, and Spring MVC technology to design and develop a web-based multimedia teaching equipment management system. On the basis of realizing the centralized control and management of multiple multimedia teaching equipment, it can also track and record the use status and maintenance content of the multimedia teaching equipment to form an information knowledge base of the multimedia equipment, which is convenient for later maintenance and management. Through the use of this system, management can be systematized, standardized, and automated, reducing the tedious workload of management and maintenance personnel. It can speed up the information management process of multimedia teaching equipment and improve the work efficiency of related managers. A course can be studied online, and an online teaching system has been developed. According to our survey on Mandarin online course training in Northwest China (N = 343), we found that 81.6% of samples are satisfied with the Mandarin online training courses; 21.6% think that they have learned new teaching methods/teaching concepts from the teacher through the Mandarin training; 36.2% think that they have learned the theoretical knowledge of Mandarin through the Mandarin training. Gender, age, ethnicity, and learning experience are related to the difficulty of learning Mandarin online courses. Therefore, we can satisfy learners of different ages, learning foundations, and cultural backgrounds by designing different online course patterns, so as to enhance the high-quality promotion of Mandarin. Copyright © 2021 Yawen Su et al. +is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Original languageEnglish
Article number7318891
JournalMobile Information Systems
Volume2021
DOIs
Publication statusPublished - Nov 2021

Citation

Su, Y., Chen, G., Li, M., Shi, T., & Fang, D. (2021). Design and implementation of web multimedia teaching evaluation system based on artificial intelligence and jQuery. Mobile Information Systems, 2021. Retrieved from https://doi.org/10.1155/2021/7318891

Keywords

  • PG student publication

Fingerprint

Dive into the research topics of 'Design and implementation of web multimedia teaching evaluation system based on artificial intelligence and jQuery'. Together they form a unique fingerprint.