基于数据挖掘的高校评价绩效智能分析的设计与应用

Cheng Wei
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引用次数: 0

摘要

由于高校绩效评估计划制定过程中主观因素的深度介入和绩效评估方法的局限,导致高校绩效评估计划在实施过程中往往存在问题。基于大数据的分析方法可以获得数据中存在的自然规律,提高分析效率。利用数据挖掘技术对高校现有教师相关信息进行分析,构建基于多角度、多技术框架的教师绩效评估平台,分析教师信息,优化教师绩效评估方案。该智能平台可以减少绩效考核方案实施过程中主观因素的影响,拓展绩效考核方法,动态监控教学活动和科研成果,为制定更合理的绩效考核方案提供决策支持。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Application of University Evaluation Performance Intelligent Analysis Based on Data Mining
Colleges and universities usually have problems in implementing their performance evaluation plans due to the deep involvement of subjective factors in making the plan and limited performance evaluation methods. Analysis methods based on big data could help get natural rules existing in data and improve the efficiency of analysis. By using data mining technology to analyze existing information related to teachers in higher learning institutions, the author aims to build a performance evaluation platform based on a multi-angle and multi-tech framework for analyzing teachers' information and optimizing teachers' performance evaluation plan. This intelligent platform could help reduce the influence of subjective factors in implementing performance evaluation plans, expand performance evaluation methods, monitor teaching activities and research achievements dynamically, and offer supports in decision-making while developing a more reasonable performance evaluation plan.
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