{"title":"智能评估之路:利用电源BI增强性能洞察","authors":"Xiaojun Li, Yueke Dong, Zhi Ai","doi":"10.1016/j.caeo.2025.100271","DOIUrl":null,"url":null,"abstract":"<div><div>This paper aims to enhance the performance evaluation process for university faculty by tackling the shortcomings of current assessment methods, including the “one-size-fits-all” approach, the excessive focus on research over teaching, and the absence of automated and intelligent data analysis. The study utilizes performance data from 869 faculty members and employs Microsoft Power BI along with its various components to facilitate comprehensive and categorical assessments, improving both the intelligence of the evaluation process and the visualization of the assessment results.</div></div>","PeriodicalId":100322,"journal":{"name":"Computers and Education Open","volume":"9 ","pages":"Article 100271"},"PeriodicalIF":5.7000,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Path to intelligent evaluation: Utilizing power BI for enhanced performance insights\",\"authors\":\"Xiaojun Li, Yueke Dong, Zhi Ai\",\"doi\":\"10.1016/j.caeo.2025.100271\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper aims to enhance the performance evaluation process for university faculty by tackling the shortcomings of current assessment methods, including the “one-size-fits-all” approach, the excessive focus on research over teaching, and the absence of automated and intelligent data analysis. The study utilizes performance data from 869 faculty members and employs Microsoft Power BI along with its various components to facilitate comprehensive and categorical assessments, improving both the intelligence of the evaluation process and the visualization of the assessment results.</div></div>\",\"PeriodicalId\":100322,\"journal\":{\"name\":\"Computers and Education Open\",\"volume\":\"9 \",\"pages\":\"Article 100271\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2025-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers and Education Open\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666557325000308\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Education Open","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666557325000308","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
摘要
本文旨在通过解决当前评估方法的缺陷,包括“一刀切”的方法,过度关注研究而不是教学,以及缺乏自动化和智能的数据分析,来改进大学教师的绩效评估过程。该研究利用了来自869名教师的绩效数据,并采用Microsoft Power BI及其各种组件来促进全面和分类的评估,提高了评估过程的智能性和评估结果的可视化。
Path to intelligent evaluation: Utilizing power BI for enhanced performance insights
This paper aims to enhance the performance evaluation process for university faculty by tackling the shortcomings of current assessment methods, including the “one-size-fits-all” approach, the excessive focus on research over teaching, and the absence of automated and intelligent data analysis. The study utilizes performance data from 869 faculty members and employs Microsoft Power BI along with its various components to facilitate comprehensive and categorical assessments, improving both the intelligence of the evaluation process and the visualization of the assessment results.