Design of Auxiliary Teaching System for Preschool Education Specialty Courses Based on Artificial Intelligence

• Published in: Mathematical problems in engineering Vol. 2022; pp. 1 - 9
• Main Author: Weiwei, Sun
• Format: Journal Article
• Language: English
• Published: New York Hindawi 18.03.2022; John Wiley & Sons, Inc
• Subjects: Artificial intelligence; Children & youth; Classrooms; Curricula; Data retrieval; Data storage; Design; Education; Educational technology; Efficiency; Engineering; Information literacy; Learning; Parents & parenting; Personal development; Preschool education; Programming languages; Questionnaires; Response time; Students; Teachers; Teaching; China
• ISSN: 1024-123X; 1563-5147
• DOI: 10.1155/2022/4504707

In order to improve the data retrieval accuracy of preschool education major curriculum, this paper designs an auxiliary teaching system for preschool education specialty courses based on artificial intelligence. 2000 preschool education teachers and 3000 students in M city were selected to conduct a questionnaire survey to analyze the application status of artificial intelligence technology, advantages and disadvantages of assisted teaching, obstacles and training intentions of assisted teaching, and the impact on the personal development of teachers and students. Using artificial intelligence technology to improve the shortcomings of existing preschool education professional courses, through the Vue.js technology in the artificial intelligence method to achieve the MVVM mode sharing of preschool education professional courses, using MySQL database to achieve multiuser multithread operation of preschool education system, using MySQL data to complete data storage, C# was used as the programming language to design the learning module of preschool education professional courses, and the artificial intelligence-based preschool education professional course auxiliary teaching system was designed. The experimental results show that when the retrieval quantity of curriculum resources is 600 GB, the response time of resource retrieval of the designed system is 7 s, and the retrieval accuracy of curriculum data of education major can reach 95%. The performance of the system is good.