Hunan First Normal University, Changsha 410205, China.
J Environ Public Health. 2022 Jul 13;2022:4545125. doi: 10.1155/2022/4545125. eCollection 2022.
In order to overcome the problem that learners and teachers cannot find instructional resources to meet their needs and information overload in the massive resources, this article proposes and designs a music instructional resource management platform based on DCNN. This article expounds the overall goal, design principle, overall structure, and interface design of the system. At the same time, the whole construction process of a music instructional resources integration system based on DCNN is discussed in detail from the aspects of configuration of development environment, localization of platform interface, and realization of main functions of the system. In addition, through the demand analysis tool, the demand of college music instructional resources management is analyzed in detail and deeply, and the demand document is formed. This article makes an in-depth study on the categories of music instructional resources and summarizes the resource classification methods that are in line with the actual instructional activities. The experiments show that the accuracy of the proposed algorithm is improved by about 6% compared with the fuzzy clustering algorithm. At the same time, the stability of this system can reach 96.14%. This system is rich in functions and easy to use and can provide a feasible scheme for the management of instructional resources in various disciplines.
为了克服学习者和教师在海量资源中无法找到满足其需求的教学资源和信息过载的问题，本文提出并设计了一个基于 DCNN 的音乐教学资源管理平台。本文阐述了系统的总体目标、设计原则、总体结构和界面设计。同时，从开发环境配置、平台界面本地化和系统主要功能实现等方面详细讨论了基于 DCNN 的音乐教学资源集成系统的整体构建过程。此外，通过需求分析工具，对高校音乐教学资源管理的需求进行了详细深入的分析，形成了需求文档。本文对音乐教学资源的类别进行了深入研究，总结了符合实际教学活动的资源分类方法。实验表明，与模糊聚类算法相比，所提出算法的准确性提高了约 6%。同时，该系统的稳定性可达 96.14%。该系统功能丰富，使用方便，可以为各学科的教学资源管理提供可行的方案。
