Classroom Teaching Performance Evaluation Model Guided by Big Data and Mobile Computing

• Main Authors: Meng, L. (Author), Wang, L. (Author), Zhu, J. (Author)
• Format: Article
• Language: English
• Published: Hindawi Limited 2022
• Subjects: Benchmarking; Big data; Business performance; Classroom teaching; Computation theory; Data mining; Education computing; Enterprise applications; Human resource management; ITS applications; Mobile computing; Mobile-computing; Performance; Performance evaluation models; Performance management; Practical skill; Quality control; Students; Teaching managements
• Online Access: View Fulltext in Publisher

 Performance management has evolved rapidly in recent years and has become increasingly dominant in enterprise applications, whereas its application in the field of education has progressed slowly. Because performance management focuses on improving business performance and empowering employees, implementing it in schools helps students develop practical skills. This research focuses on evaluating classroom teaching performance using a big data and mobile computing-driven model. In addition, in the era of educational big data, this paper investigates the general process by which teachers acquire, analyze, and use educational data to improve teaching performance. The data mining method and mobile data capture are organically integrated into the benchmarking analysis to evaluate the classroom teaching performance of local universities, enriching the teaching management theories and methods of local universities. The findings show that benchmarking analysis can produce more meaningful results and provide new data for improving teaching management quality. © 2022 Li Meng et al.