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

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.