A Study of Artificial Intelligence-Assisted Teaching on the Cultivation of Students’ Creative Ability

[1] Liu, T., Gao, Z., & Guan, H. (2021). Educational information system optimization for artificial intelligence teaching strategies. Complexity, 2021(3), 1-13. Search in Google Scholar

[2] Huang, G. R. X. (2021). Connotation analysis and paradigm shift of teaching design under artificial intelligence technology. Pediatric obesity., 16(5). Search in Google Scholar

[3] Dong, Y. (2022). Application of artificial intelligence software based on semantic web technology in english learning and teaching. Journal of Internet Technology(1), 23. Search in Google Scholar

[4] Liu, Y., & Ren, L. (2022). The influence of artificial intelligence technology on teaching under the threshold of “internet+”: based on the application example of an english education platform. Wireless Communications and Mobile Computing, 2022. Search in Google Scholar

[5] Fan, X., & Zhong, X. (2022). Artificial intelligence-based creative thinking skill analysis model using human–computer interaction in art design teaching. Computers and Electrical Engineering(100-), 100. Search in Google Scholar

[6] Dai, D. D. (2021). Artificial intelligence technology assisted music teaching design. Scientific programming(Pt.14), 2021. Search in Google Scholar

[7] Li, P., Ning, Y., & Fang, H. (2021). Artificial intelligence translation under the influence of multimedia teaching to study english learning mode. International Journal of Electrical Engineering Education, 002072092098352. Search in Google Scholar

[8] Ma, J. (2021). Intelligent decision system of higher educational resource data under artificial intelligence technology. Pediatric obesity., 16(5). Search in Google Scholar

[9] Liu, Y. (2021). Research on the new model of aerobics physical education under the background of artificial intelligence era. Mobile information systems. Search in Google Scholar

[10] Li, Y. (2021). Research on the construction of tcfl resource database system based on artificial intelligence. Journal of Intelligent and Fuzzy Systems(6), 1-12. Search in Google Scholar

[11] Ma, W., Zhao, X., & Guo, Y. (2021). Improving the effectiveness of traditional education based on computer artificial intelligence and neural network system. Journal of Intelligent and Fuzzy Systems, 40(2), 2565-2575. Search in Google Scholar

[12] Zhang, X., & Chen, L. (2021). College english smart classroom teaching model based on artificial intelligence technology in mobile information systems. Mobile information systems. Search in Google Scholar

[13] Wu, S., & Wang, F. (2021). Artificial intelligence-based simulation research on the flipped classroom mode of listening and speaking teaching for english majors. Mobile Information Systems. Search in Google Scholar

[14] Yuanmeng. (2021). On practice and dilemma of artificial intelligence in collaborative teaching of the ideological and political theory course in colleges and universities. Journal of Intelligent and Fuzzy Systems(5), 1-12. Search in Google Scholar

[15] Yunjie, J. (2021). Research on the practice of college english classroom teaching based on internet and artificial intelligence. Journal of Intelligent and Fuzzy Systems(1), 1-10. Search in Google Scholar

[16] Bai, X. J., & Li, J. J. (2021). Applied research of knowledge in the field of artificial intelligence in the intelligent retrieval of teaching resources. Scientific Programming. Search in Google Scholar

[17] Zhang, Y., & Cao, J. (2022). Design of english teaching system using artificial intelligence. Computers and Electrical Engineering. Search in Google Scholar

[18] Tyler H. McCormick, Adrian E. Raftery, David Madigan, & Randall S. Burd. (2011). Dynamic logistic regression and dynamic model averaging for binary classification. Biometrics. Search in Google Scholar

[19] Wang, B., Wang, X. F., Howell, Paul, Qian, X., & Huang, K., et al. (2010). A personalized microrna microarray normalization method using a logistic regression model. Bioinformatics. Search in Google Scholar

[20] Wang, T., Tang, W., Lin, Y., & Su, W. (2023). Semi‐supervised inference for nonparametric logistic regression. Statistics in Medicine, 42(15), 2573-2589. Search in Google Scholar

[21] S Domínguez-Almendros, N Benítez-Parejo, & Gonzalez-Ramirez, A. R. (2011). Logistic regression models. Allergologia et Immunopathologia, 39(5), 295-305. Search in Google Scholar

[22] Hosmer, D. W., Hosmer, T., Le, C. S., & Lemeshow, S. (2015). A comparison of goodness-of-fit tests for the logistic regression model. Statistics in Medicine, 16(9), 965-980. Search in Google Scholar

[23] Mccormick, T. H., Raftery, A. E., Madigan, D., & Burd, R. S. (2012). Dynamic logistic regression and dynamic model averaging for binary classification. Biometrics. Search in Google Scholar