Design and Implementation of Knowledge Graph-based AI Assistant for Assisted Teaching and Quizzing

DOI: https://doi.org/10.62517/jike.202604137

Author(s)

Yiting Ju, Junfeng Chen, Shengbo Shi, Jingzhen Wang, Fuqiang Chu, Lujiang Hao*

Affiliation(s)

School of Bioengineering, Qilu University of Technology (Shandong Academy of Sciences), China *Corresponding Author

Abstract

Since the rapid development of Internet technology, a variety of assisted teaching tools have been gradually introduced in the field of education, which have achieved extensive sharing of educational resources and personalised learning experience. However, due to the complexity of the knowledge graph and the dynamics of the educational content, the current assisted teaching system is still facing the dilemma of low answer accuracy, long response time and poor user experience, and how to improve the intelligence level of the system is imminent. Based on this, this paper briefly discusses the design and implementation of an AI assistant for assisted teaching and answering based on knowledge graph, analyses the key technologies and applications of the system, and puts forward a targeted approach to performance evaluation and optimization, with a view to providing a reference and reference for the development of future educational technology.

Keywords

Knowledge Graph; Assisted Teaching; Question and Answer System

References

[1] Li Mei, Cai Guanyin, Ma Xian, et al. Research on virtual reality technology based on artificial intelligence to assist college basketball teaching [J]. Sports goods and technology, 2024, (20):157-159. [2] Dong Fang. Analysis of personalised recommendation system for teaching resources based on artificial intelligence assistance [J]. Electronic Technology, 2024, 53(10):148-149. [3] Xing C, Yun L, Feng S. Predict, pretrained, select and answer: Interpretable and scalable complex question answering over knowledge bases [J]. Knowledge-Based Systems, 2023, 278. [4] V. S T, C. P R R. A novel technique using graph neural networks and relevance scoring to improve the performance of knowledge graph-based question answering systems [J]. Journal of Intelligent Information Systems, 2024, 62(3):809-832. [5] Zhou, X., Zhang, Z., Xie, X. et al. Deep learning based knowledge tracing in intelligent tutoring systems. Sci Rep [J]. 15, 21395(2025). [6] Zheng Yao, Xia Tingting. Design and implementation of an AI assistant for assisted teaching and answering questions based on knowledge graph [J]. Information and Computer (Theoretical Edition), 2024, 36(02):235-237. [7] Chen Fei. Data security opportunities and challenges in the AI era [J]. China Science and Technology Information, 2025, (15):156-158. [8] Wang L, Wang T, Zhou H T, et al. Course-Oriented Knowledge Service-Based AI Teaching Assistant System for Higher Education Sustainable Development Demand [J]. Sustainability, 2026, 18(2):807-807.