The computer programming course has always been considered a difficult course to get started, especially the teaching quality of computer programming courses in higher vocational schools is relatively poor, which has been a problem and challenge for schools and teachers. This paper designs a teaching evaluation method of computer programming course in higher vocational colleges based on big data. Firstly, the paper analyzes the application of big data in the computer programming course of higher vocational college, and confirms the promoting effect of big data on the teaching of computer programming course of higher vocational college. Based on the evaluation results, the author puts forward some strategies to improve the teaching quality. The research results provide valuable reference for the teaching of computer programming courses and the application of big data in higher vocational schools.

He Ying, Fu Dajie, Zhang Xiaobo. Teaching Evaluation of Computer Programming Course in Higher Vocational Colleges Based on Big Data. Frontiers in Educational Research (2024) Vol. 7, Issue 1: 113-118. https://doi.org/10.25236/FER.2024.070116.

[1] Fortes, Sergio, et al. "The campus as a smart city: University of Málaga environmental, learning, and research approaches." Sensors 19.6 (2019): 1349.

[2] Xiu-Hua, Zhang, J. Dong , and  S. Xiao-Yan . "An Analysis of Learning Behavior of Higher Vocational College Students Based on Open Assessment Model." Value Engineering (2018).

[3] Bosse, Yorah, and Marco Aurélio Gerosa. "Why is programming so difficult to learn? Patterns of Difficulties Related to Programming Learning Mid-Stage." ACM SIGSOFT Software Engineering Notes 41.6 (2017): 1-6.

[4] Savage, Simon, and Paul Piwek. "Full report on challenges with learning to program and problem solve: an analysis of first year undergraduate Open University distance learning students' online discussions." (2019).

[5] He, Shouwu, Xiaoying Li, and Jia Chen. "Application of data mining in predicting college graduates employment." 2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD). IEEE, 2021..

[6] Chen, Xiao. "Design of a hybrid classroom teaching quality evaluation system based on information technology." Journal of Physics: Conference Series. Vol. 1852. No. 3. IOP Publishing, 2021.

[7] Li, Xueyan. "Research on higher vocational network teaching quality evaluation system based on big data analysis." Contemporary Education and Teaching Research 2.1 (2021): 38-41.

[8] Essa, Alfred, and Hanan Ayad. "Student success system: risk analytics and data visualization using ensembles of predictive models." Proceedings of the 2nd international conference on learning analytics and knowledge. 2012.

[9] Kotsiantis, Sotiris B. "Use of machine learning techniques for educational proposes: a decision support system for forecasting students’ grades." Artificial Intelligence Review 37 (2012): 331-344.

[10] Bruce, Christine S., et al. "Information literacy and informed learning: Conceptual innovations for IL research and practice futures." The Journal of Information Literacy 11.1 (2017): 4.

[11] Horton, Joann. "Identifying at-risk factors that affect college student success." International Journal of Process Education 7.1 (2015): 83-101.

[12] Veerasamy, Ashok Kumar, et al. "Using early assessment performance as early warning signs to identify at-risk students in programming courses." 2020 IEEE Frontiers in Education Conference (FIE). IEEE, 2020.

[13] Xu, Dacheng, and Theodore S. Rappaport. "Construction on teaching evaluation index system of track and field general course for physical education major in light of wireless network technology." Journal of Intelligent & Fuzzy Systems 37.3 (2019): 3435-3443.

[14] Luo, Gang, and Zhiyuan Chen. "Adaptive entropy theory polymerization method for path optimization in edge computing educational systems." Journal of Intelligent & Fuzzy Systems 40.2 (2021): 2941-2951.