Research on Constructing Student Digital Twins Driven by Digital-Intelligent Integration Based on Disciplinary Knowledge Graphs

DOI

10.2991/978-2-38476-577-5_60How to use a DOI?

Keywords

Student Digital Twin; Disciplinary Knowledge Graphs; Digital-Intelligent Integration

Abstract

Against the backdrop of global educational digital transformation, traditional higher education struggles to meet diverse learning needs and talent market demands. This study proposes constructing a digital-intelligent integration-driven Student Digital Twin (DTS) based on a six-layer disciplinary knowledge graph. The disciplinary knowledge graph provides a semantic core and knowledge foundation, while the DTS integrates real-time academic data, behavioral signals, and competency levels. Through three dynamic coupling cycles—state perception-semantic mapping, intelligent analysis-path reasoning, and intervention feedback-graph evolution—deep integration between the static disciplinary knowledge graph and the dynamic DTS is achieved. This paradigm transforms unified knowledge transmission into personalized competency development and achieves innovations in three key domains of education: Firstly, in the teaching domain, it enables the shift from experience-driven to evidence-driven precision teaching; Secondly, in the learning domain, it facilitates the transition from passive knowledge reception to active personalized growth; Thirdly, in the evaluation domain, it realizes the transformation from outcome-oriented assessment to process-oriented value-added competency certification. These practical innovations in the three domains provide a feasible technical architecture and practical path for the competency-oriented transformation of higher education, reshaping a new talent training ecosystem in the digital era.

Copyright

© 2026 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.

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TY  - CONF
AU  - Tao Zhao
AU  - Dan Wu
AU  - Jun Cao
PY  - 2026
DA  - 2026/05/15
TI  - Research on Constructing Student Digital Twins Driven by Digital-Intelligent Integration Based on Disciplinary Knowledge Graphs
BT  - Proceedings of the 2026 5th International Conference on Social Sciences and Humanities and Arts (SSHA 2026)
PB  - Atlantis Press
SP  - 593
EP  - 600
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-577-5_60
DO  - 10.2991/978-2-38476-577-5_60
ID  - Zhao2026
ER  -