基于大数据技术的学前教师人才培养评价模型

Q2 Social Sciences
Fang Wang, Shasha Xu
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引用次数: 0

摘要

提高幼儿教育质量的关键在于高素质的幼儿教师,高素质的幼儿教师又依赖于高素质的教师教育。“加强幼儿园指导员培训”试点项目被教育部推荐。本研究对试点师范院校实施的驻校培训模式进行研究,利用大数据技术收集所需数据,并利用神经网络对幼儿教师人才培养模式进行评估,最终完成以下工作:1)介绍了国内外幼儿教师人才培养模式的研究进展;2)介绍了RBF神经网络的基本思想和算法阶段,建立了幼儿教师培训的评价指标体系;3)实验以确定最佳模型参数,然后将测试数据输入您训练的模型,并将输出与专家评估进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Evaluation Model of Preschool Teacher Talent Training Based on Big Data Technology
The key to improving the quality of preschool education lies in high-quality preschool teachers, and high-quality preschool teachers in turn depend on high-quality teacher education. A pilot project to “strengthen the training of kindergarten instructors” was recommended by the Ministry of Education. This research studies the resident training mode implemented by pilot normal colleges and universities, uses big data technology to collect the required data, and uses neural networks to evaluate the talent training mode of preschool teachers, and finally completes the following work: 1) This article introduces the research progress of the talent training mode of preschool teachers at home and abroad; 2) Introduced are the RBF neural network's fundamental ideas and algorithmic stages, and the evaluation index system for the training of preschool teachers is established; and 3) Experiment to determine the best model parameters, then feed the test data into the model you trained, and compare the output against expert evaluations.
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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
68
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