Article
Mathematical Statistics Technology in the Educational Grading System of Preschool Students
Authors
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Abstract
The current education system for preschool students has relatively small differences and cannot fully reflect the true mastery of students. The article designs a cognitive system for preschool students’ educational scoring based on mathematical statistics. The article uses the attention vector and knowledge acceptance in children’s teaching as a multi-scale convolution level to analyze the effect of education. The study results found that the evaluation system can analyze the quality of children’s education while also considering children’s learning emotions.
Keywords
Mathematical statistics, Early childhood education, Teaching system rating, 92B20
Citation
Yang, L. & Ali, B. (2022). Mathematical statistics technology in the educational grading system of preschool students. Applied Mathematics and Nonlinear Sciences, 7(2), 593–602. https://doi.org/10.2478/amns.2022.2.0044
L. Yang and B. Ali, “Mathematical statistics technology in the educational grading system of preschool students,” Applied Mathematics and Nonlinear Sciences, vol. 7, no. 2, pp. 593–602, 2022, doi: 10.2478/amns.2022.2.0044.
Yang L, Ali B. Mathematical statistics technology in the educational grading system of preschool students. Applied Mathematics and Nonlinear Sciences. 2022;7(2):593–602. doi:10.2478/amns.2022.2.0044.
Yang, L. and Ali, B. (2022), ‘Mathematical statistics technology in the educational grading system of preschool students’, Applied Mathematics and Nonlinear Sciences, 7(2), pp. 593–602. Available at: https://doi.org/10.2478/amns.2022.2.0044.
Yang, Long, and Basel Ali. “Mathematical Statistics Technology in the Educational Grading System of Preschool Students.” Applied Mathematics and Nonlinear Sciences, vol. 7, no. 2, 2022, pp. 593–602. https://doi.org/10.2478/amns.2022.2.0044.
Yang, Long, and Basel Ali. “Mathematical Statistics Technology in the Educational Grading System of Preschool Students.” Applied Mathematics and Nonlinear Sciences 7, no. 2 (2022): 593–602. https://doi.org/10.2478/amns.2022.2.0044.
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Published by: Engineering Journals


