Based on knowledge graph and artificial intelligence technology, this paper discusses the design and quality improvement of online and offline hybrid teaching curriculum. In order to realize the accurate matching and personalized recommendation of the teaching content, the knowledge map technology is used to systematically sort out and structuralize the content of curriculum ideological and political education. Firstly, based on the customer satisfaction theory and structural equation model, this paper puts forward the student satisfaction theory model of mixed teaching and carries on fitting revising and testing to the model. The mixed teaching student satisfaction index model includes student expectations, offline teaching, online learning, perceived value, student satisfaction five factors, each variable on the mixed teaching satisfaction path. Then, the introduction of system dynamics method, and use Vensim-PLE to build online and online mixed teaching satisfaction factor chart and stock flow chart, to dynamic simulation of the complex relationship between the factors. Finally, the model is validated and optimized by data analysis. The research shows that knowledge graph can significantly improve the organization and systematicness of curriculum ideological and political content, and artificial intelligence technology can effectively enhance the interaction and feedback of teaching. Affect the satisfaction of online and offline mixed teaching and whether to give full play to students' expectations, Whether to improve the teaching efficiency of teachers and whether to enhance the cohesion of online and offline teaching and whether there is a good external atmosphere and environment are the four factors that students are satisfied with the hybrid teaching model. The following policy proposals are proposed from four levels, namely, to play the role of students' expectations, improve the compatibility of online and offline teaching content, focus on life and create a good external atmosphere and environment to improve the quality and effectiveness of mixed teaching in courses and promote mixed satisfaction.

Junwei Shi, Yang Li, Zhangliang Chen, Jingqi Cui, Jianing Liu. Research on the Path of Ideological and Political Design and Quality Improvement of Online and Offline Hybrid Teaching Course Based on Knowledge Graph and Artificial Intelligence. International Journal of New Developments in Education (2024), Vol. 6, Issue 9: 61-69. https://doi.org/10.25236/IJNDE.2024.060909.

[1] Feng Xiaoying, Wang Ruixue. A review of the current status of blended teaching research at home and abroad: Based on blended teaching[J]. Journal of Distance Education,2018,246(3):13-22.

[2] Xu Menglin. Construction and exploration of the influencing factor model of students' learning satisfaction in blended learning environment[J].College Entrance Examination,2018,(29):128-129.

[3] HUANG Zhifang, ZHOU Ruijie, ZHAO Chengling, et al. Design and empirical research of blended learning mode for deep learning[J].China E-Education,2019,394(11):120-129.

[4] Li Bao. Construction and empirical study of influencing factor model of student learning satisfaction in blended learning environment[D].Xi'an: Shaanxi Normal University,2016.

[5] FORNELL C, JOHNSON M D, ANDERSON EW, et al. The American Customer SatisfactionIndex: Nature Purpose and Findings[J].Journal of Marketing,1996(4):7-18.