基于BP神经网络的高校教师精准教学能力评价模型构建
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摘要：
通过精准教学以促进学生个性化成长是教育理想和国家政策的不懈追求.高校教师是实施精准教学的“基”,现有关于其教学能力的评价体系中普遍存在概念不清和多采用主观构建评价指标的问题.为此,开展了基于BP神经网络的高校教师精准教学能力评价模型研究.首先,以理论研究为基础,对精准教学能力进行等级划分并构建评价指标框架 ,运用层级分析法建立指标权重;其次,利用BP神经网络智能学习的特性,以不同数据类型的指标值为输入,对应能力综合值为输出,检验精准教学能力分级及指标权重的合理性,进而生成较为客观的评价模型;最后,利用开发的评价系统和调查问卷进行样本数据采集和模型检验,从神经网络对数据的分类、拟合及仿真结果来看,模型能够对高校教师的精准教学能力进行客观评价 ,教师对模型测量结果的准确性也具有较高认可度 .
Precision teaching to promote the personalized growth of students is the unremitting pursuit of educational ideals and nationalpolicies. As the foundation ofthe implementation ofprecision teaching, there are many problems in the ex- isting evaluation system ofteachers'teaching ability, such as unclear concepts and subjective construction of evaluation indica- tors. Therefore, a research on the evaluation modelofcollege teachers'precision teaching abilitybased on BP neuralnetwork is carried out. Firstly, based on the theoreticalresearch, the precision teaching ability is graded and the evaluation index frame- work is constructed, and the index weights areestablished by using the analytichierarchyprocess method. Secondly, using the characteristics ofBP neuralnetwork intelligentlearning, theindexvaluesofdifferentdatatypesaretaken asinputand thecom- prehensive values ofcorresponding abilities are used as output, the rationality of precision teaching ability grading and index weights is tested, and a more objective evaluation model is generated. Finally, the developed evaluation system and question- naire areused to collectsamplesand testthemodel. From theclassification, fitting and simulation resultsofthedata, themod- elcan objectively evaluate the precision teaching ability of college teachers, and teachers also have a high recognition of the accuracy of modelmeasurement.
作者：
魏培文,朱珂,叶海智,张潍杰,张利远,闫娟
WeiPeiwen, Zhu Ke, YeHaizhi , Zhang Weijie, Zhang Liyuan , Yan Juan
机构地区：
betway官方app 教育学部;智能教育河南省协同创新中心 ;信息化建设与管理办公室
引用本文：
魏培文,朱珂,叶海智等. 基于BP神经网络的高校教师精准教学能力评价模型构建[J].
betway官方app 学报(自然科学版),2024,52(5):108-116.
WeiPeiwen,Zhu Ke,YeHaizhi,etal.Construction ofprecision teaching abili- ty evaluation modelfor college teachers based on BP neural network[J] . Journal of Henan Normal University (NaturalScience Edition) ,2024,52(5) :108-116. DOI:10. 16366/j. cnki.1000-2367. 2023. 12. 05. 0001.
基金：
国家社科基金；河南省高校重点科研项目；河南省高校科技创新团队支持计划；河南省普通本科高等学校智慧教学专项研究项目
关键词：
教育数字化转型 ;高校教师 ;精准教学能力 ;评价模型;BP神经网络
digitaltransformation ofeducation; collegeteachers; precision teaching ability; evaluation model; BP neural network
分类号：
G420
