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19 December 2021 Design of practical teaching quality evaluation system based on rough set and big data mining
Jingxian Wang, Min Yang
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Proceedings Volume 12128, Second International Conference on Industrial IoT, Big Data, and Supply Chain; 121281L (2021) https://doi.org/10.1117/12.2624205
Event: 2nd International Conference on Industrial IoT, Big Data, and Supply Chain, 2021, Macao, China
Abstract
The article establishes a practical teaching quality evaluation index system from five aspects: practical teaching goal, practical teaching content, practical teaching process, practical teaching implementation guarantee, and practical teaching effect. Through large sample surveys and big data mining, combined with factor analysis to build a complete index system for practical teaching quality evaluation. On this basis, the rough set reduction method is adopted to reduce the complete index system and establish a scientific practical teaching quality evaluation system consisting of 5 first-level indicators, 21 second-level indicators, and 72 observation indicators.
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Jingxian Wang and Min Yang "Design of practical teaching quality evaluation system based on rough set and big data mining", Proc. SPIE 12128, Second International Conference on Industrial IoT, Big Data, and Supply Chain, 121281L (19 December 2021); https://doi.org/10.1117/12.2624205
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KEYWORDS
Quality systems
Data mining
Factor analysis
Analytical research
Logic
Nomenclature
Standards development
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