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- W3173270265 abstract "AbstractAs a key link in university management, scientific research performance evaluation is a significant guarantee for promoting the orderly development of teachers’ scientific research. However, there still exist some problems in the traditional scientific research performance evaluation of Humanities Teachers in local universities and colleges, such as the lack of independent evaluation of Teachers, the lack of specific evaluation indicators and the malposition of peer experts, Humanities Teachers’ research performance evaluation and the deep integration of big data technology can build a more scientific evaluation system. This study discusses the Enlightenment of big data thinking on the construction of scientific research performance evaluation system of Humanities Teachers in local universities and colleges from three aspects: teacher self-evaluation, index selection and data collection, evaluation process and evaluation method. Through the strategic management tools such as scientific research performance evaluation model and university scientific research performance index database, the perspective evaluation of local universities and colleges is carried out, integrate the most insightful research data and results with the development status of higher education at home and abroad. On the premise of ensuring the security of data and information, let all local universities and colleges benefit from the convenience of big data, in order to gradually move towards a new era of teachers’ scientific research performance evaluation which is based on big data thinking.KeywordsBig dataBig data thinkingHumanities TeachersResearch performance evaluation" @default.
- W3173270265 created "2021-07-05" @default.
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- W3173270265 date "2021-01-01" @default.
- W3173270265 modified "2023-09-24" @default.
- W3173270265 title "Enlightenment of Big Data Thinking on the Construction of Scientific Research Performance Evaluation System for Humanities Teachers in Local Universities" @default.
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- W3173270265 doi "https://doi.org/10.1007/978-3-030-79200-8_132" @default.
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