Research on the Construction and Practice of Intelligent Courses from the Perspective of Knowledge Graph: A Case Study of English Lexicology

Huan Cao

doi:10.63313/ESW.9066

Authors

Huan Cao School of English Studies, Zhejiang Yuexiu University, Shaoxing 312000, China Author

DOI:

https://doi.org/10.63313/ESW.9066

Keywords:

English Lexicology, Teaching Reform, Artificial Intelligence (AI), Knowledge Graph, Intelligent Course, Personalized Learning

Abstract

The course English Lexicology was previously developed into a high-quality online course and implemented blended online and offline teaching. However, two rounds of teaching practice revealed persistent issues, including low utili-zation of online resources, insufficient feedback mechanisms, and sub-optimal personalized learning effectiveness. To address these challenges, guided by the OBE (Outcome-Based Education) concept, the author constructed an intelligent course system based on a knowledge graph. Utilizing the knowledge graph, the course content was decomposed into 11 knowledge modules and further divided into 97 atomic knowledge points (each with a granularity of 5-6 minutes), es-tablishing a logical association network among them (comprising 447 knowledge nodes). By integrating Artificial Intelligence (AI) technology, dy-namic learning path recommendations, real-time feedback, and multi-round questioning functions were implemented, forming a synergistic teaching loop of “knowledge + question + goal”. Practice demonstrates that this system signifi-cantly enhances students’ depth of understanding of English lexicology theories and their knowledge transfer ability, effectively resolving structural contradic-tions inherent in blended teaching. It provides a replicable implementation pathway for transforming traditional blended courses into intelligent courses.

References

[1] Aliyu, I., Kana, A., & Aliyu, S. (2020). Development of Knowledge Graph for university courses management. International Journal of Education and Management Engineering, 10(2), 1. https://doi.org/10.5815/ijeme.2020.02.01

[2] Anusooya, D. S., Kamali, S. M., & Ramamoorthy, S. K. (2024). KGCD: Leveraging Knowledge Graphs for intelligent curriculum design in education. Recent Trends in Cloud Computing and Web Engineering, 7(1), 1-9. https://doi.org/10.5281/zenodo.13756521

[3] Bai, Y., & Liao, X.(2024) Research and application of Knowledge Graph design for in-terac-tive teaching platform based on artificial intelligence. Applied Mathematics and Non-linear Sciences, 9(1), 1-15. https://doi.org/10.2478/amns-2024-2173

[4] Chandar, V., & Thangamani, M. (2022). False alarm reduction in ICU using ensemble clas-si-fier approach. Intelligent Automation & Soft Computing, 34(1), 165-181. https://doi.org/10.32604/iasc.2022.022339

[5] Dai, Y., Wang, S., Chen, X., Xu, C., & Guo, W. (2020). Generative adversarial networks based on Wasserstein distance for Knowledge Graph embeddings. Knowledge-Based Systems, 190, 105-165. https://doi.org/10.1016/j.knosys.2019.105165

[6] Deng Shuo, Yan Yan. Teaching Innovation and Role of Knowledge Graph in the Era of Di-gi-tal Intelligence [J]. Journal of Hebei Normal University (Educational Science Edition), 2024, 26(05): 100-102.

[7] Fan Jia-rong, Zhong Shaochun. Research on Subject Knowledge Mapping:from Knowledge Learning to Thinking Development. e-Education Research, 2022, 43(1): 32-38.

[8] Fensel, D., Şimşek, U., Angele, K., Huaman, E., Kärle, E., Panasiuk, O., & Wahler, A. (2020). Introduction: What is a knowledge graph? Knowledge Graphs: Methodology, Tools and Se-lected Use Cases, 1-10. https://doi.org/10.1007/978-3-030-37439-6_1

[9] Jia Junzhi, Cui Xiyan, Zhang Guixiang. Impact of Artificial Intelligence Technology on Knowledge Organization: A Knowledge Graph Perspective. Library Tribune, 2024, 44(02): 1-8.

[10] Khan, U. A., Kauttonen, J., Aunimo, L., & Alamäki, A. (2024). A system to ensure information trust worthiness in artificial intelligence enhanced higher education. Journal of In-for-mation Technology Education: Research, 23(13), 1-35. https://doi.org/10.28945/5295

[11] Ko, H., Witherell, P., Lu, Y., Kim, S., & Rosen, D. W. (2021). Machine learning and Knowledge Graph based design rule construction for additive manufacturing. Additive Manufacturing, 37, 101-620. https://doi.org/10.1016/j.addma.2020.101620

[12] Kong, Y., Liu, X., Zhao, Z., Zhang, D., & Duan, J. (2022). Bolt defect classification algorithm based on Knowledge Graph and feature fusion. Energy Reports, 8, 856-863. https://doi.org/10.1016/j.egyr.2021.11.127

[13] Li Chao, Xiao Ling-ping, Wang Caiyin, et al. Evolution of Color Science Course in the Context of Classification Education. Printing and Digital Media Technology Study, 2024, (3): 169-175.

[14] Li Junfeng, Xiao Gensheng, Wei Chun'ao, et al. Construction and Practice of Knowledge Graph-based "Chromatics" Intelligent Course. Printing Technology, 2025, (03): 142-148. DOI: 10.19370/j.cnki.cn10-1886/ts.2025.03.018.

[15] Li Zheng, Qiao Baojun, Yang Wei, et al. Practice of Multi-Dimensional Fusion Teaching Mode of Data Structure Based on OBE [J]. Software Guide, 2024, 23(2): 162-166.

[16] Pan Manman. Artificial Intelligence Technology to Promote the Practical Path of Teaching Students in Accordance with Their Aptitude. Journal of Hubei Open Vocational College, 2024, 37(23): 162-164.

[17] Peng, C., Xia, F., Naseriparsa, M., & Osborne, F. (2023). Knowledge Graphs: Opportunities and challenges. Artificial Intelligence Review, 56(11), 13071-13102. https://doi.org/10.1007/s10462-023-10465-9

[18] Shen Liyan, Li Meng, Zhang Zihui, et al. Construction and Application of AI-based Smart Teaching Ecosystem in Universities: A Case Study of Zhejiang University. Modern Edu-ca-tional Technology, 2022, 32(12): 85-92.

[19] Wang Jian-ming, Zhu Ke. From “Digitization” to “Intelligentization”: the Supposed Destina-tion and Its Approaches to the Development of Digital Resources in Higher Educa-tion. Heilongjiang Researches on Higher Education, 2024, 42(11): 155-160.

[20] Wang Jiru, Zhu Jing, Wang Jian, et al. Role of Data-Driven Knowledge Graph in Under-grad-uate Teaching Informatization Reform. Research in Higher Engineering Education, 2024, (03): 121-128.

[21] Xie Youru, Lu Yi, Peng Zhiyang, et al. Inquiry on the Integration of “Teach-ing-Learning-Evaluating” of College Courses Empowered by Knowledge Graph. China Educational Technology, 2024, (12): 1-7.

[22] Zhang Meng. Construction of Subject Knowledge Graph for AI Education. Xi'an Tech-nolog-ical University, 2021.

[23] Zheng, L., Long, M., Chen, B., & Fan, Y. (2023). Promoting knowledge elaboration, socially shared regulation, and group performance in collaborative learning: An automated as-sessment and feedback approach based on knowledge graphs. International Journal of Educational Technology in Higher Education, 20(46), 1-20. https://doi.org/10.1186/s41239-023-00415-4

[24] Zheng Zhihong, Ma Tao, Kong Xinmei, et al. Research on Subject Knowledge Graph Con-struction and Macro-Unit Design Based on Zone of Proximal Development. Journal of Dis-tance Education, 2024, 42(02): 56-64.