Research on the Evaluation Mechanism of Artificial Intelligence-Enabled Education and Teaching Innovation in Colleges and Universities

Kebiao Yuan; Shengyi Li

doi:10.62177/amit.v1i4.549

Authors

Kebiao Yuan School of Economics and Management, Ningbo University of Technology
Shengyi Li School of Economics and Management, Ningbo University of Technology

DOI:

https://doi.org/10.62177/amit.v1i4.549

Keywords:

Artificial Intelligence, Teaching and Learning in Higher Education, Innovation Evaluation, Structural Equation Modeling

Abstract

The report of the 20th National Congress of the Communist Party of China first positioned ‘educational digitization’ as the core path to building a learning-oriented nation. The ‘China Education Modernization 2035’ plan further clarified that artificial intelligence is the key to achieving the organic integration of large-scale education and personalized cultivation. However, the traditional educational evaluation system suffers from static lag and insufficient adaptability, urgently requiring the reconstruction of evaluation mechanisms through artificial intelligence technology. Therefore, analyzing the role of artificial intelligence in empowering innovative evaluation mechanisms for higher education teaching and learning is of great significance. This article takes university students, teachers, and university administrators as the survey subjects and uses structural equation modeling to explore the innovative evaluation mechanisms of university education and teaching empowered by artificial intelligence. The research findings indicate that AI drives innovation in higher education evaluation mechanisms across six dimensions: learning outcomes, teaching processes, feedback on results, data privacy and security, acceptance, and social empowerment. Therefore, this paper suggests that the application of AI in higher education evaluation can be promoted by accelerating the construction of a national intelligent education evaluation standards system and advancing institutional evaluation innovation mechanisms, and provides relevant recommendations.

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