Article: Digital twin technology for building immersive learning environment for English education Journal: International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL) 2026 Vol.36 No.9 pp.174 - 193 Abstract: The current immersive learning environment for English still cannot meet the practical needs of language transfer and intensive use in terms of the authenticity of language scenes, real-time response of learning behaviour, and semantic continuity of contextual interaction. Therefore, this paper proposes an educational digital twin modelling method. This paper first constructs a learner digital twin model in a synchronous manner based on multi-source data such as speech features, eye movement trajectories, and operational behaviours. Secondly, this paper constructs a dynamic language scene model by mining the spatial structure and semantic paths of typical language tasks, and finally uses context modelling and semantic graph linking algorithms to perform context analysis on learners' inputs. The experimental results show that the average response time for speech input recognition is 434 ms, and the average matching rate of interactive context is over 90%; the satisfaction score of users when activating interactive context is 86.7. Inderscience Publishers - linking academia, business and industry through research

Title: Digital twin technology for building immersive learning environment for English education

Authors: Xiaolin Wu; Qing Ai

Addresses: School of Foreign Languages, Shaoxing University, Shaoxing, 312000, Zhejiang, China ' School of Humanity, Zhujiang College, South China Agricultural University, Guangzhou, 510900, Guangdong, China

Abstract: The current immersive learning environment for English still cannot meet the practical needs of language transfer and intensive use in terms of the authenticity of language scenes, real-time response of learning behaviour, and semantic continuity of contextual interaction. Therefore, this paper proposes an educational digital twin modelling method. This paper first constructs a learner digital twin model in a synchronous manner based on multi-source data such as speech features, eye movement trajectories, and operational behaviours. Secondly, this paper constructs a dynamic language scene model by mining the spatial structure and semantic paths of typical language tasks, and finally uses context modelling and semantic graph linking algorithms to perform context analysis on learners' inputs. The experimental results show that the average response time for speech input recognition is 434 ms, and the average matching rate of interactive context is over 90%; the satisfaction score of users when activating interactive context is 86.7.

Keywords: digital twin modelling; multimodal behaviour perception; semantic scene construction; context-driven interaction; language transfer task.

DOI: 10.1504/IJCEELL.2026.153616

International Journal of Continuing Engineering Education and Life-Long Learning, 2026 Vol.36 No.9, pp.174 - 193

Received: 20 Aug 2025
Accepted: 21 Jan 2026
Published online: 18 May 2026 *

Title: Digital twin technology for building immersive learning environment for English education

Keep up-to-date