{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,11]],"date-time":"2026-06-11T22:54:49Z","timestamp":1781218489836,"version":"3.54.1"},"reference-count":21,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"6","license":[{"start":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T00:00:00Z","timestamp":1730419200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"The Virtual Simulation Special Project of the Ministry of Education","award":["ZJXF2022035"],"award-info":[{"award-number":["ZJXF2022035"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational Methods in Sciences and Engineering"],"published-print":{"date-parts":[[2024,11]]},"abstract":"<jats:p>The purpose of this study is to explore the method and application of constructing the evaluation standard system of university practice teaching under the background of big data. Based on teaching evaluation theory, combined with big data technology, the paper constructs a practical teaching evaluation model through questionnaire survey and data collection. In the data analysis, the multiple linear regression model is used to predict the practical teaching effect, and the detailed empirical analysis is carried out. It is found that the model can predict the practical teaching effect and explain the variability of the actual data well. However, the study also revealed the existence of problems such as data quality, sample bias, and model limitations, which need further research and verification. 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