Title: Research on knowledge tree growth model for intelligent English teaching system based on hypertext structure

Authors: Shixin Sun; Haiyan Li

Addresses: Information Engineering Department, Bozhou Vocational and Technical College, Bozhou, 236800, China ' Basic Teaching Department, Bozhou Vocational and Technical College, Bozhou, 236800, China

Abstract: At present, the knowledge management model of intelligent English teaching system has some problems, such as weak relevance of knowledge points and poor judgment accuracy of precursor knowledge points. This paper proposes a new knowledge tree growth model for intelligent English teaching system based on hypertext structure. The knowledge representation of intelligent English teaching resources is completed through representation of tree of knowledge map, description of knowledge attribute and knowledge relation, and construction of a knowledge tree structure. On this basis, the hypertext structure is used to construct the content model of English teaching resources, package the metadata and content, and thus complete the organisation of English teaching resources. The experimental results show that the proposed knowledge tree growth model greatly improves the relevance of knowledge points and the accuracy of judgment of precursor knowledge points, improves the knowledge base of intelligent English, and improves the efficiency and quality of English teaching.

Keywords: hypertext structure; intelligence; English; teaching; knowledge tree; model.

DOI: 10.1504/IJCEELL.2022.125729

International Journal of Continuing Engineering Education and Life-Long Learning, 2022 Vol.32 No.5, pp.539 - 553

Received: 26 Jun 2019
Accepted: 27 Mar 2020
Published online: 27 Sep 2022 *

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