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Frontiers in Educational Research, 2023, 6(9); doi: 10.25236/FER.2023.060923.

Research on Neural Network Prediction System in Loose-leaf Textbook Course Assessment


Liu Xing1,2, Wu Sheng1,2, Chen Li1,2, Mei Jing1,2, Hu Dong1

Corresponding Author:
Liu Xing

1College of Mechanical Engineering, Sichuan Vocational College of Chemical Industry, Luzhou, 646300, China

2The Key Laboratory of Mechanical Structure Optimization & Material Application Technology of Luzhou, Sichuan Vocational College of Chemical Industry, Luzhou, 646300, China


The unique advantages of flexible and novel loose-leaf textbooks have become a new development direction, but the diversified assessment system of loose-leaf textbooks is still relatively imperfect, and the application of traditional curriculum assessment systems in loose-leaf textbooks is subject to certain constraints. Therefore, in order to improve the diversified assessment system of loose-leaf textbooks, this paper proposes a machine learning algorithm applied to the loose-leaf textbook assessment system. By comparing various neural network algorithms, a prediction model suitable for the diversified assessment system was found. The results show that the application of SVM radial basis function neural network in the assessment and prediction system for loose-leaf courses has high prediction accuracy and small error, can effectively play a prediction and reminder role, improve the diversified assessment system, and promote the application and promotion of loose-leaf textbooks.


neural network algorithm; loose-leaf teaching materials; course assessment system

Cite This Paper

Liu Xing, Wu Sheng, Chen Li, Mei Jing, Hu Dong. Research on Neural Network Prediction System in Loose-leaf Textbook Course Assessment. Frontiers in Educational Research (2023) Vol. 6, Issue 9: 139-145. https://doi.org/10.25236/FER.2023.060923.


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