Abstract—Teachers should not only understand the basic knowledge of the course, but also master the overall structural characteristics of the course, grasp the important and difficult point of the course, and optimize the knowledge structure of the course. This paper mainly applies complex network to the analysis of course knowledge structure to construct and optimize the knowledge network of Educational Technology course. Firstly, the textbook and syllabus of Educational Technology course are used as a data source, and the course knowledge network model is constructed. Secondly, the knowledge nodes and their relationships are determined, and the course knowledge network is constructed. Thirdly, by using topological sorting based on directed graph, the course knowledge structure is optimized. And the pre-optimized and optimized course knowledge network are compared and analyzed, it shows the optimized course knowledge structure has superiority. It proves that the optimized course knowledge structure is more hierarchical, sequential and structural, which can highlight the main line of knowledge and clear the learning ideas. Finally, according to the results of comparative analysis of the pre-optimized and optimized course knowledge network, the teaching suggestions are proposed, and it is to realize the aim of optimizing teaching.
Index Terms—Course knowledge network, construction and optimization, course knowledge structure, teaching suggestions.
Jingxia Liu and Bin Wen (Corresponding author) are with School of Information Science and Technology, Yunnan Normal University, Kunming, Yunnan, China (e-mail: 179988079@qq.com, ynwenbin@163.com).
Cite:Jingxia Liu and Bin Wen, "Construction and Optimization of Educational Technology Course Knowledge Network," International Journal of Information and Education Technology vol. 10, no. 9, pp. 694-703, 2020.
Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).