Research on Application and Quality Evaluation of Intelligent Teaching Model of AI Three Teachers in the Course of Motion Control Technology
DOI:
https://doi.org/10.54097/v4ppp550Keywords:
Motion Control Technology, Teaching Mode, Intelligent Teaching Model, AI Three TeachersAbstract
Motion control technology is an important branch of automation, and is one of the important development directions of the emerging industry of high-end equipment manufacturing. As a comprehensive discipline with the intersection of mechanical, electrical and electronic, its teaching mode faces many challenges. There are practical problems that need to be solved, such as teaching content not matching seamlessly with post knowledge and skill literacy requirements, teaching project design is not high in modularity, and teaching evaluation system is not perfect. These problems seriously restrict the cultivation of students' technical practical ability. This project proposes the "intelligent teaching model of AI three teachers for the course of Motion Control Technology", which emphasizes student-centered, builds a core curriculum system that connects with the technology of field engineers in enterprises, and proposes the three-way collaborative teaching and education strategy of "vocational school Teacher + Al Teacher + enterprise tutor" to enable students to participate in learning in an all-round way. And timely access to feedback information, the formation of continuous improvement of the teaching cycle. Optimize the teaching team and teaching mode, improve the teaching quality, meet the diversified learning needs of students, and promote the continuous innovation and development of education and teaching.
Downloads
References
Burke T. Advancing motion control applications with the right drives, technology[J]. Control engineering: Covering control, instrumentation, and automation systems worldwide, 2023,70(7):26-28.
Du M. Motion Control and Planning Decision-Making Technology[J]. 2023.
Hein T. EMERGING APPLICATIONS IN MOTION CONTROL[J]. Manufacturing automation: Machine Dessig, Systems, Technology, 2023,38(4):10-12.
Xiao Li, Wu Bei. Research on knn Algorithm and Collaborative Filtering Hybrid Algorithm based on kmeans Clustering in the precision teaching of AI dual teachers [J]. Changjiang Information and Communication, 2022(008):35.
Yao Yuanfeng, Tian Litchi. Application and quality evaluation of AI intelligent teaching System for Higher Vocational Education [J]. New Curriculum Research, 2023(30):92-94.
Guerreiro-Santalla S, Crompton H, Bellas F. RoboboITS: A Simulation-Based Tutoring System to Support AI Education Through Robotics[J]. 2023.
Yan S, Yang B. Research on Traffic Safety AI Education System Based on User Portrait and Collaborative Filtering[J]. 2023 IEEE 3rd International Conference on Electronic Communications, Internet of Things and Big Data (ICEIB), 2023:467-470.
Koch K. Putting AI to work in education[J]. 2023.
Wang X, Li L, Tan L L J. Preparing for AI-enhanced education: Conceptualizing and empirically examining teachers' AI readiness[J]. Computers in human behavior, 2023,146(9): 107 791-107798.
Alasadi E, Baiz C R. Generative AI in Education and Research: Opportunities, Concerns, and Solutions[J]. Journal of Chemical Education, 2023.
Giray L. Educators Who Do Not Use AI Will Be Replaced by Those Who Do: Disadvantages of Not Embracing AI in Medical Education[J]. Journal of the Practice of Cardiovascular Sciences, 2024,10(1):43-47.
Li W, Zhang X, Li J, et al. An explanatory study of factors influencing engagement in AI education at the K-12 Level: an extension of the classic TAM model[J]. Scientific Reports, 2024, 14(1).
Fujita Y, Dosaka S, Akiyama Y, et al. AI Education Course using AI Needs Creating Method based on User Experience Design and its Evaluation for Sales Representatives[J]. IEEJ Transactions on Electronics, Information and Systems, 2022, 142(7):719-728.
Fundi M, Sanusi I T, Oyelere S S, et al. Advancing AI education: Assessing Kenyan in-service teachers' preparedness for integrating artificial intelligence in competence-based curriculum[J]. Computers in Human Behavior Reports, 2024, 14.
Porayska-Pomsta K. A Manifesto for a Pro-Actively Responsible AI in Education[J]. International Journal of Artificial Intelligence in Education, 2024,34(1):73-83.
Zhong Huijuan, Da Xinyu, Liu Wenwu, et al. Reform and Exploration of "AI+ Teaching "under the background of" New Engineering "-- A case study of" Signal and System "course [J]. Industry and Information Technology Education, 2022(11):29-33.
Downloads
Published
Issue
Section
License
Copyright (c) 2024 International Journal of Education and Humanities
This work is licensed under a Creative Commons Attribution 4.0 International License.
