Teaching Quality Evaluation Model for Human Resource Development and Management Major Under the Background of Big Data

Bu Lyu, Jianhui Chen, Na Wang
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Abstract

The evaluation of teaching quality in colleges relies on reliable and comprehensive evaluation data, which is also an important basis for educational decision-making. The application of big data technology can realize scientific analysis and in-depth mining of a large number of data, analyze the value and connection implied in the data on a multidimensional level, and enable the evaluation of teaching quality to transform from the previous analysis of segment information and small sample data to the whole process of all-round data decision-making. This paper proposes a learning quality evaluation model based on big data in cloud computing environment, using the structure method, AHP, fuzzy comprehensive evaluation and multi-objective optimization method. It is also combined with a variety of theories such as user perception theory and user experience theory, and the development of this model is studied. Finally, we develop and design the learning quality evaluation system under cloud computing, to test the system and prove the credibility of our scheme.
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大数据背景下人力资源开发与管理专业教学质量评价模型
高校教学质量评价依赖于可靠、全面的评价数据,是教育决策的重要依据。大数据技术的应用可以实现对大量数据的科学分析和深度挖掘,从多维层面分析数据蕴含的价值和联系,使教学质量评价从以往的分段信息、小样本数据分析,转变为全方位数据决策的全过程。本文采用结构法、层次分析法、模糊综合评价法和多目标优化法,提出了云计算环境下基于大数据的学习质量评价模型。并结合用户感知理论、用户体验理论等多种理论,对该模型的发展进行了研究。最后,我们开发并设计了云计算下的学习质量评估系统,并对系统进行了测试,证明了方案的可信性。
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