Comprehensive Evaluation of Online Experimental Teaching Quality in Colleges and Universities Based on Support Vector Machine

Authors

DOI:

https://doi.org/10.3991/ijet.v18i12.39697

Keywords:

support vector machine, online experimental teaching, teaching quality, quality evaluation

Abstract


Affected by the global COVID-19 epidemic, many universities in China have to carry out online experimental teaching. Online experimental teaching can fully realize retention of experimental teaching data, the maximum sharing of experimental teaching, and improve teachers’ ability to complete experimental teaching by mobile means through good network storage devices. Scientific and systematic evaluation of online experimental teaching quality can promote continuous improvement of online teaching activities, give full play to teachers’ teaching enthusiasm, improve comprehensive training quality of college students, and make online experimental teaching a new trend of experimental teaching reform. Based on existing literature, this study analyzes the factors affecting the quality of online experimental teaching, puts forward evaluation indicators of online experimental teaching quality, and uses support vector machine training evaluation system to establish evaluation model of online experimental teaching quality in colleges and universities. Experimental results show that evaluation indicator of online experimental teaching quality proposed is relatively perfect, and has good applicability and popularization. The method based on the support vector machine has improved evaluation effect of online experimental teaching quality in colleges and universities. Output evaluation results are highly consistent with actual evaluation results. Online experimental teaching quality evaluation results are very objective and comprehensive. Conclusions have important reference value for online experimental teaching behavior analysis, improvement of online experimental teaching quality evaluation indicators, reduction of online teaching quality evaluation errors, and improvement of online teaching quality evaluation effect.

Cover iJET Vol. 18 No. 12 (2023)

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Published

2023-06-21

How to Cite

Ou, J., Lin, D., & Zheng, Z. (2023). Comprehensive Evaluation of Online Experimental Teaching Quality in Colleges and Universities Based on Support Vector Machine. International Journal of Emerging Technologies in Learning (iJET), 18(12), pp. 88–102. https://doi.org/10.3991/ijet.v18i12.39697

Issue

Vol. 18 No. 12 (2023)

Section

Papers

License

Copyright (c) 2023 Jianmeng Ou, Dongdong Lin, Zhitao Zheng

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