Article: Computer learning career path optimisation utilising multi-modal large models and privacy-preserving collaborative computing Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.32 pp.83 - 100 Abstract: As computer technology advances, there is a growing need for personalised learning path planning for learners. Traditional methods fall short in accuracy and adaptability. This study introduces MPCO, a computer course learning path optimisation model powered by a multi-modal large model and privacy computation. The multi-modal large model integrates text, images, and other info to better understand learners' knowledge levels and cognitive preferences. Privacy computation technology ensures the safe storage and compliant sharing of learning data, reducing the risk of data privacy breaches. Experiments show that this method achieves higher accuracy, adaptability, and data security in learning path optimisation tasks through the collaborative driving of multimodal large models and privacy computing, effectively improving the planning effect of computer course learning paths. Inderscience Publishers - linking academia, business and industry through research

Title: Computer learning career path optimisation utilising multi-modal large models and privacy-preserving collaborative computing

Authors: Xuesong Yang

Addresses: College of Electrical Engineering, Northwest Minzu University, Gansu 730000, China

Abstract: As computer technology advances, there is a growing need for personalised learning path planning for learners. Traditional methods fall short in accuracy and adaptability. This study introduces MPCO, a computer course learning path optimisation model powered by a multi-modal large model and privacy computation. The multi-modal large model integrates text, images, and other info to better understand learners' knowledge levels and cognitive preferences. Privacy computation technology ensures the safe storage and compliant sharing of learning data, reducing the risk of data privacy breaches. Experiments show that this method achieves higher accuracy, adaptability, and data security in learning path optimisation tasks through the collaborative driving of multimodal large models and privacy computing, effectively improving the planning effect of computer course learning paths.

Keywords: multi-modal large models; privacy computing; computer courses; learning path optimisation; personalised learning; Java.

DOI: 10.1504/IJICT.2025.148495

International Journal of Information and Communication Technology, 2025 Vol.26 No.32, pp.83 - 100

Received: 22 Jun 2025
Accepted: 15 Jul 2025
Published online: 08 Sep 2025 *

Title: Computer learning career path optimisation utilising multi-modal large models and privacy-preserving collaborative computing

Keep up-to-date