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Title: Design of sharing model of information-based teaching materials upon deep learning

Authors: Zhou Zhou; Zishuai Zhou; Fangfang Zhang

Addresses: School of Accounting, Anhui Wenda University of Information Engineering, Hefei, 231201, Anhui, China ' School of Mechanics and Civil Engineering, China University of Mining and Technology, Xuzhou, 221116, Jiangsu, China ' School of Accounting, Anhui Wenda University of Information Engineering, Hefei, 231201, Anhui, China

Abstract: The imbalance of the regional economy and the tilt of national policy lead to the degree of development among universities. To help more backward universities improve their academic level and narrow the development gap between universities, we propose a teaching information-based resource-sharing (TIRS) model based on deep learning (DL) for college. Firstly, we analyse the types and characteristics of teaching resources and establish a sharing platform for university teaching resources. Then, we propose a label quantification method for teaching resources upon DL to extract the features of each resource in the sharing platform and assign labels. Finally, we propose a teaching resources retrieval method by the bag of words model to improve the efficiency of the TIRS model. The experiment demonstrates that the TIRS model for colleges by deep learning can provide good teaching services for teachers and students, and the objective accuracy and subjective accuracy of retrieval can reach 87.2% and 86.7% respectively, which provides technical support for resource sharing of colleges.

Keywords: teaching resources; sharing model; deep learning; DL.

DOI: 10.1504/IJICT.2026.154116

International Journal of Information and Communication Technology, 2026 Vol.27 No.64, pp.46 - 60

Received: 26 Dec 2025
Accepted: 27 Feb 2026
Published online: 12 Jun 2026 *