Department of Preschool Education, Nanyang Vocational College of Agriculture, Nanyang City, 473000, China.
Department of Command Tactics, Henan Police College, ZhengZhou City, 450000, China.
Sci Rep. 2023 Nov 20;13(1):20273. doi: 10.1038/s41598-023-46060-9.
An ever-growing portion of the economy is dedicated to the field of education, intensifying the urgency of identifying strategies to secure the sector's enduring prosperity and elevate educational standards universally. This study introduces a model for enhancing games and optimizing data analysis within the context of early childhood education (ECE) majors, hinging on deep learning (DL). This approach aims to enhance the quality of instruction provided to ECE majors and refine the effectiveness of their professional pursuits. This study commences by examining the incorporation of DL technologies within the domain of ECE and delving into their fundamental underpinnings. Subsequently, it expounds upon the design philosophy underpinning ECE games operating within the framework of DL. Finally, it outlines the game improvement and data analysis (GIADA) model tailored to ECE majors. This model is constructed upon DL technology and further refined through the integration of convolutional neural networks (CNN). Empirical findings corroborate that the DL-CNN GIADA model achieves data analysis accuracy ranging from 83 to 93% across four datasets, underscoring the pronounced optimization prowess bestowed by CNN within the DL-based GIADA model. This study stands as an invaluable reference for the application and evolution of artificial intelligence technology within the realm of education, thereby contributing substantively to the broader landscape of educational advancement.
经济中越来越大的一部分致力于教育领域，这加剧了确定策略以确保该部门持久繁荣和普遍提高教育标准的紧迫性。本研究提出了一个在幼儿教育（ECE）专业背景下强化游戏和优化数据分析的模型，该模型基于深度学习（DL）。这种方法旨在提高向 ECE 专业学生提供的教学质量，并提高他们专业追求的效率。本研究首先研究了 DL 技术在 ECE 领域的应用，并深入探讨了它们的基本原理。随后，它阐述了在 DL 框架内运行的 ECE 游戏的设计理念。最后，它概述了针对 ECE 专业学生的游戏改进和数据分析（GIADA）模型。该模型建立在 DL 技术的基础上，并通过集成卷积神经网络（CNN）进一步完善。实证研究结果证实，DL-CNN GIADA 模型在四个数据集上的数据分析准确率在 83%至 93%之间，突出了 CNN 在基于 DL 的 GIADA 模型中提供的显著优化能力。本研究为教育领域人工智能技术的应用和发展提供了宝贵的参考，为更广泛的教育进步领域做出了实质性贡献。
