Article: Low-cost smart devices and personalised learning for AI-driven preschool education Journal: International Journal of Continuing Engineering Education and Life-Long Learning (IJCEELL) 2026 Vol.36 No.9 pp.101 - 128 Abstract: This paper develops low-cost intelligent devices and designs personalised learning algorithms to optimise the effectiveness of early childhood education driven by artificial intelligence (AI). Firstly, this paper designs a teacher technical literacy training module and uses a virtual reality simulator to enhance teachers' ability to operate artificial intelligence tools. Secondly, based on children's behavioural data, this paper applies collaborative filtering algorithms and long short-term memory (LSTM) models to construct an adaptive learning system. Finally, with the help of 3D modelling software and spatial audio technology, this paper constructs a virtual reality interactive scene to enhance the immersive learning experience, improves the security and usability of the human-computer interaction interface through natural language processing models and touch interaction optimisation. The research results indicate that in interactive teaching scenarios, the AR rendering delay of high-end devices is only 25 ms, while the AR rendering delay of low-end devices is 40 ms. Inderscience Publishers - linking academia, business and industry through research

Title: Low-cost smart devices and personalised learning for AI-driven preschool education

Authors: Xiaoyu Ou

Addresses: College of Education, Urban Vocational College of Sichuan, Chengdu, 610000, Sichuan, China

Abstract: This paper develops low-cost intelligent devices and designs personalised learning algorithms to optimise the effectiveness of early childhood education driven by artificial intelligence (AI). Firstly, this paper designs a teacher technical literacy training module and uses a virtual reality simulator to enhance teachers' ability to operate artificial intelligence tools. Secondly, based on children's behavioural data, this paper applies collaborative filtering algorithms and long short-term memory (LSTM) models to construct an adaptive learning system. Finally, with the help of 3D modelling software and spatial audio technology, this paper constructs a virtual reality interactive scene to enhance the immersive learning experience, improves the security and usability of the human-computer interaction interface through natural language processing models and touch interaction optimisation. The research results indicate that in interactive teaching scenarios, the AR rendering delay of high-end devices is only 25 ms, while the AR rendering delay of low-end devices is 40 ms.

Keywords: artificial intelligence; preschool education; low-cost smart devices; personalised learning; adaptive learning system.

DOI: 10.1504/IJCEELL.2026.153602

International Journal of Continuing Engineering Education and Life-Long Learning, 2026 Vol.36 No.9, pp.101 - 128

Received: 03 Jul 2025
Accepted: 16 Jan 2026
Published online: 18 May 2026 *

Title: Low-cost smart devices and personalised learning for AI-driven preschool education

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