Title: Analysis of the digital technology of the e-education platform in practice in tertiary education

Authors: Fei Gu

Addresses: Higher Vocational Education Research Center, Yangzhou Polytechnic Institute, Yangzhou, 225127, China

Abstract: The study collects learners' learning preferences with the help of deep belief networks, allocates and updates course resources with BP neural networks, and introduces the concept of similarity to effectively connect learner resources with teaching resources to better meet learners' cognitive level and logical thinking. The performance of the proposed algorithm model is tested and the results show that the DBN-BP algorithm achieves minimum RMSE and MAPE values of 0.66 and 0.63 in terms of recommendation performance, and achieves 95.23% and 0.72 in terms of resource recommendation accuracy and coverage, effectively improving the teaching recommendation performance. The algorithm can effectively provide new and improved ideas and means for online practical teaching in higher education, and provide guarantee for its teaching quality improvement.

Keywords: e-education platforms; digital technology; higher education; deep belief networks; backpropagation; BP; similarity.

DOI: 10.1504/IJCSYSE.2025.149206

International Journal of Computational Systems Engineering, 2025 Vol.9 No.2/3/4, pp.70 - 80

Received: 10 Apr 2023
Accepted: 11 Jun 2023
Published online: 20 Oct 2025 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article