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Title: Simulation of multimodal education mode based on artificial intelligence

Authors: Ying Bai; Bin Fang; Long Cai; Yanhua Liu

Addresses: School of Art and Design, Guangzhou Institute of Technology, Guangzhou 510000, Guangdong, China ' School of Art and Design, Guangzhou Institute of Technology, Guangzhou 510000, Guangdong, China ' School of Art and Design, Jiangmen Vocational and Technical College, Jiangmen 529000, Guangdong, China ' School of Art and Design, Guangzhou Institute of Technology, Guangzhou 510000, Guangdong, China

Abstract: To promote the technical development of integrating artificial intelligence into education and the continuous progress of society, a multimodal education model based on artificial intelligence is proposed. Under the influence of artificial intelligence, profound changes are taking place in education. The multimodal education model is an urgent and essential research topic. For the teaching-learning-based optimisation (TLBO) algorithm, when solving high-dimensional, complex, multimodal optimisation problems, the population can prematurely fall into local search, leading to the loss of global optimal solutions. This suggests an improved TLBO optimisation algorithm (MTLBO). An improved TLBO optimisation algorithm (MTLBO) is proposed. The algorithm improves the 'teaching' and 'learning' processes in the standard TLBO in a more human-like way and introduces a new 'self-study' mechanism to strengthen students' innovative learning ability, thereby effectively improving the algorithm's global search capability.

Keywords: artificial intelligence; multimodal; education optimisation algorithm; simulation study.

DOI: 10.1504/IJCEELL.2026.153609

International Journal of Continuing Engineering Education and Life-Long Learning, 2026 Vol.36 No.9, pp.264 - 283

Received: 23 Jul 2025
Accepted: 29 Jan 2026
Published online: 18 May 2026 *