The Application of Knowledge Graph in Online Educational Assessment Systems
- DOI
- 10.2991/978-2-38476-462-4_46How to use a DOI?
- Keywords
- Knowledge graph; Personalized learning paths; Online educational assessment systems
- Abstract
Online educational assessment systems plays a crucial role in promoting and enhancing students’ learning quality by providing students with continuous learning feedback and personalized academic support. Knowledge graph is a powerful tool for organizing and utilizing complex datasets, enabling more intelligent and context-aware applications across various domains. The application of a knowledge graph in online educational assessment systems offers a powerful way to enhance the accuracy, depth, and personalization of assessments by structuring and interlinking diverse educational data. In this paper, the author discusses various aspects of the application in detail, identifies the critical factors affecting learning outcomes. With the maturation of technology and the emergence of successful case studies, the application of knowledge graphs in online educational assessment systems will play a crucial role in shaping the future of online education.
- Copyright
- © 2025 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Junbo Zhao PY - 2025 DA - 2025/09/12 TI - The Application of Knowledge Graph in Online Educational Assessment Systems BT - Proceedings of the 2025 9th International Seminar on Education, Management and Social Sciences (ISEMSS 2025) PB - Atlantis Press SP - 420 EP - 425 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-462-4_46 DO - 10.2991/978-2-38476-462-4_46 ID - Zhao2025 ER -