Abstract
In order to solve the problems of long response time and poor application effectiveness of the intelligent education system teaching quality evaluation system, a system for assessing teaching quality under the OBE+CIPP model has been developed. The OBE model is used to simulate the operation process of the intelligent education system. Under the constraint of determining the construction principle of the teaching quality evaluation system, CIPP model is used to select the teaching quality evaluation indicators from four aspects of background, input, process and results. Through the collection of real-time operation data of intelligent education system, determine the specific value of evaluation indicators, and finally complete the construction of teaching quality evaluation system of intelligent education system through the calculation of the weight of each evaluation indicator. After conducting the experimental application test, it has been deduced that upon implementation of the proposed method, the maximum system response time is 20s, and the students’ assessment scores have been significantly improved, which proves that the teaching quality evaluation system of intelligent education system under OBE+CIPP model has good application effect.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Liu, P., Wang, X., Teng, F.: Online teaching quality evaluation based on multi-granularity probabilistic linguistic term sets. J. Intell. Fuzzy Syst. 40(2), 1–20 (2021)
Wang, J.X.: Research on higher vocational teaching quality evaluation model based on RBF network. Wuxian Hulian Keji 19(10), 137–139 (2022)
Huang, H.D.: G C C. research on application of Blockchain technology in teaching quality evaluation system of colleges and universities. Mod. Inf. Technol. 6(02), 160–163 (2022)
Finne, L.T., Gammelgaard, B., Christiansen, F.V.: When the lab work disappears: students’ perception of laboratory teaching for quality learning. J. Chem. Educ. 99(4), 1766–1774 (2022)
Lu, C., He, B., Zhang, R.: Evaluation of English interpretation teaching quality based on GA optimized RBF neural network. J. Intell. Fuzzy Syst. 40(2), 3185–3192 (2021)
Sun, Q.: Evaluation model of classroom teaching quality based on improved RVM algorithm and knowledge recommendation. J. Intell. Fuzzy Syst. 40(2), 2457–2467 (2021)
Wang, Q.: Research on teaching quality evaluation of college English based on the CODAS method under interval-valued intuitionistic fuzzy information. J. Intell. Fuzzy Syst. 41(1), 1499–1508 (2021)
Yuan, T.: Algorithm of classroom teaching quality evaluation based on Markov Chain. Complexity 2021(21), 1–12 (2021)
Huang, W.: Simulation of English teaching quality evaluation model based on Gaussian process machine learning. J. Intell. Fuzzy Syst. 40(2), 2373–2383 (2021)
Hou, J.: Online teaching quality evaluation model based on support vector machine and decision tree. J. Intell. Fuzzy Syst. 40(2), 2193–2203 (2021)
Wu, Y.F., Du, S.G.: Simulation of moving target feature extraction method in indoor space vision. Comput. Simul. 39(10), 234–238 (2022)
Stojadinovic, Z., Bozic, M., Nadadi, A.: Development and implementation of evaluation framework for quality enhancement of outcome-based curriculum. Int. J. Eng. Educ. 37(2), 397–408 (2021)
Peng, T., Luo, Y., Liu, Y.: AI-based equipment optimization of the design on intelligent education curriculum system. Wirel. Commun. Mob. Comput. 2022(4), 1–13 (2022)
Lu, Q.H., Yuan, L.N.: Software named entity recognition simulation based on combined neural network. Comput. Simul. 40(01), 489–492+509 (2023)
Acknowledgement
1. The “Fourteenth Five-Year Plan” of Jiangxi Education and Science in 2022: Research on the five-in-one evaluation system of classroom teaching quality in colleges and universities based on “OBE+CIPP” (Project number: 22YB370).
2. Teaching reform project of Jiangxi Provincial Department of Education in 2020: Strategic Research and Practice of Integrating Socialist Core Values into the Whole Process of Accounting Teaching (Project number: JXJG-20-29-3).
3. 2019 Jiangxi Provincial Department of Education Science and Technology Project: Research on systematic risk identification and countermeasures of industry-university-research cooperation projects (Project number: GJJ191199).
4. 2020 Jiangxi Provincial Culture and Art Science Planning Project: Research on policy paths for Jiangxi cultural enterprises to solve difficulties under COVID-19(Project number: YG2020154).
5. General project of the school-level humanities and social science project of Jiangxi Institute of Applied science and Technology in 2020: Application Research on Fuzzy Risk Calculation of Industry-University-Research Cooperation Project Based on FMEA (Project number: JXYKRW-20-1).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Tang, Y. (2024). Construction of Teaching Quality Evaluation System of Intelligent Education System Under OBE+CIPP Model. In: Gui, G., Li, Y., Lin, Y. (eds) e-Learning, e-Education, and Online Training. eLEOT 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 546. Springer, Cham. https://doi.org/10.1007/978-3-031-51503-3_25
Download citation
DOI: https://doi.org/10.1007/978-3-031-51503-3_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-51502-6
Online ISBN: 978-3-031-51503-3
eBook Packages: Computer ScienceComputer Science (R0)