Search

Artificial Intelligence Empowers Innovation in Teaching of Public Computer Courses

Author(s)

Ling Zhang*, Chunmei Liao

Affiliation(s)

School of Big Data & Computer Science Engineering, Chongqing College of Mobile Communication, Hechuan, Chongqing, China *Corresponding Author.

Abstract

This paper expounds the core characteristics of artificial intelligence and its application potential in the field of education, analyzes the challenges currently faced by computer public course teaching, and proposes innovative strategies and methods to effectively integrate artificial intelligence into computer public course teaching. It uses large language models for personalized teaching, optimizes teaching content through knowledge graphs, and uses recommendation systems to improve practical operation capabilities. The course teaching system that supports the entire process of" learning - teaching -evaluation- continuous improvement" realizes personalized and customized learning , promotes the advancement of traditional computer public course teaching with the support of artificial intelligence technology and tools , and assists teachers in completing teaching evaluation. Through teaching empirical research, it is shown that it can better support teaching, facilitate the updating of teaching knowledge, help improve practical operation capabilities, and cultivate autonomous learning ability, thereby improving teaching quality and effectiveness.

Keywords

Artificial Intelligence; Public Computer Courses; Teaching Innovation; Personalized Teaching

References

[1] Zhang Yichun, Tang Ling, Ma Chunlan. Research on the paths and countermeasures of artificial intelligence to promote teacher development. Journal of Audio-visual Education Research, 2023(10): 104-111. [2] Jiang Lei, Wang Zhenchong, Ge Shuwei. Discussion on the teaching of artificial intelligence technology integrated into embedded system course. China Modern Educational Equipment, 2023(17): 10-12. [3] Bian Jiang, Cao Hongying, Liu Lifang. Analysis of personalized teaching mode based on big data analysis. Integrated Circuit Applications, 2023, 40(8): 362-363. [4] Li Jingjing, Tang Na, Yu Jianxing. Exploration of multi-level reverse inquiry teaching in artificial intelligence programming course based on practice. Computer Education, 2022(10): 145-149. [5] Lu Jin, Ren Hongliang, Gu Dongyuan, et al. Student-centered programming hierarchical experimental teaching reform. Computer Education, 2020(11): 174-178. [6] Xu Jianjun, Yin Liangze, Chen Liqian. Exploration on the cultivation of problem-solving ability in computer programming teaching. Curriculum Education Research, 2019(13): 243-244. [7] Wei Ying. Programming course teaching reform based on learning community. Computer Education, 2024(2): 37-41. [8] He Yingsheng, Wang Congyin. Practice of flipped classroom teaching of C language programming based on MOOC. Computer Education, 2020(1): 160-163. [9] Zhu Yongxin, Yang Fan. ChatGPT/Generative Artificial Intelligence and Educational Innovation: Opportunities, Challenges and Future. Journal of East China Normal University (Educational Science Edition), 2023, 41(7):1-14. [10] Deng Wei, Yang Xiaodan, Gao Qianqian, et al. Research on classroom teaching evaluation model supported by artificial intelligence. China Education Informatization, 2023, 29(8): 3-14.