Download pdf
The Application and Potential of Artificial Intelligence Participating in College Teaching Evaluation
- 1 Hubei University of Education
- 2 Zhengzhou Foreign Language School
* Author to whom correspondence should be addressed.
Abstract
The dominance could be applied to many more areas as new artificial intelligence (AI) advances. There are great defects in the traditional evaluation methods of higher education. The evaluation of people is dominant, resulting in excessively subjective results and wasting human resources. These issues adversely affect many stakeholders. Therefore, the combination of the objectivity of artificial intelligence and the traditional method of teaching evaluation has an exploratory significance for the development of teaching and emphasizes the technical ability that the new artificial intelligence can realize. The purpose of this study is to explore the potential of a new method for artificial intelligence in higher education evaluation. Based on the analysis of existing experimental case reports and related studies by the method of literature synthesis, it is certain that the new artificial intelligence will help improve the quality of teaching evaluation in higher education. This has a positive impact on all fields, including schools, teachers, and students. The teaching objectives of the school can be better and more efficiently accomplished under the evaluation system. This study confirms the feasibility of incorporating artificial intelligence into university evaluation.
Keywords
education evaluation, artificial intelligence, higher education
[1]. Chinese ministry of education. (2020-10-13). The Central Committee of the Communist Party of China and the State Council, ‘ Overall Plan for Deepening the Reform of Educational Evaluation in the New Era’.[OL].<http://www.moe.gov.cn/jyb_xxgk/moe_1777/moe_1778/202010/t20201013_494381.html>
[2]. Wang, Y. (2018).The construction of the evaluation system of university teachers’ post competency from the perspective of big data. China Higher Education(18),54-56.
[3]. Zhang, H., Chen , J., Li, X.& Cheng, W. (2023).Research on the construction and implementation of regional education monitoring and evaluation system - - Taking Luohu District of Shenzhen City as an example. Journal of The Chinese Society of Education(02),17-23.
[4]. Zhou, H., Lu, J., Huang, Y., & Chen, Y. (2021). Research on key technology of classroom teaching evaluation based on artificial intelligence. In Journal of Physics: Conference Series (Vol. 1757, No. 1, p. 012014). IOP Publishing.
[5]. Hu, J. (2021). Teaching evaluation system by use of machine learning and artificial intelligence methods. International Journal of Emerging Technologies in Learning (iJET), 16(5), 87-101.
[6]. Li, B., Fei, Y., & Liu, H. (2021). An artificial intelligence based model for evaluation of college students’ ability and characteristics through teaching evaluation. Journal of Intelligent & Fuzzy Systems, 40(2), 3397-3407.
[7]. Hu, Q., Wu, W., Feng, G., Pan, T., Chen, Z., & Qiu, K. (2021).The key technology and practice of higher education teaching evaluation in the era of artificial intelligence. Open Education Research(05),15-23. doi:10.13966/j.cnki.kfjyyj.2021.05.002.
[8]. Lu, Y., Chen, Z., Chen, R., Shi, Y., & Zheng, Q.(2022).Research on the application framework of intelligent technology to promote the evaluation of teachers ‘ classroom teaching behavior . Modern Educational Technology(12),76-84.
[9]. Wu, L., Cao, Y., & Cao, Y. (2021).The framework construction of artificial intelligence empowering classroom teaching evaluation reform and technology realization. China Educational Technology(05),94-101.
[10]. Cai, H., & Yang, C.(2023).Research on the reform of college teachers ‘ evaluation driven by the integration of mathematics and intelligence. Modern Educational Technology(01),91-98.
[11]. Yan, C. (2019).The risks and countermeasures of artificial intelligence applied to school safety management. Journal of Teaching and Management(10),18-20.
[12]. Xu, X., & Diao, W. (2022).Social risks of face recognition technology and its collaborative governance. Academic Exchange(01),126-139.
[13]. Rybinski, K., & Kopciuszewska, E. (2021). Will artificial intelligence revolutionise the student evaluation of teaching? A big data study of 1.6 million student reviews. Assessment & Evaluation in Higher Education, 46(7), 1127-1139.
Cite this article
Hua,Z.;Liu,Y. (2023). The Application and Potential of Artificial Intelligence Participating in College Teaching Evaluation. Lecture Notes in Education Psychology and Public Media,24,211-216.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
Disclaimer/Publisher's Note
The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of EWA Publishing and/or the editor(s). EWA Publishing and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
About volume
Volume title: Proceedings of the International Conference on Global Politics and Socio-Humanities
© 2024 by the author(s). Licensee EWA Publishing, Oxford, UK. This article is an open access article distributed under the terms and
conditions of the Creative Commons Attribution (CC BY) license. Authors who
publish this series agree to the following terms:
1. Authors retain copyright and grant the series right of first publication with the work simultaneously licensed under a Creative Commons
Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this
series.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the series's published
version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial
publication in this series.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and
during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See
Open access policy for details).