Title: Evaluation method of the impact of AI technology application on the quality of smart teaching

Authors: Lin Zeng

Addresses: Science and Technology College, Nan Chang Hang Kong University, Nanchang, 332020, China

Abstract: Aiming at the problem of high data dimension in the evaluation of the impact of artificial intelligence technology on the quality of wisdom teaching, an evaluation method based on principal component analysis (PCA) was proposed. First, the evaluation index is selected and the evaluation index system is constructed. Then the principal component analysis method is improved by using covariance and sensitivity to reduce the data dimension. Finally, BP neural network (BPNN) is improved by adjusting the steepness factor and weight value, and the evaluation model of the influence of wisdom teaching quality is established. The experimental results show that the evaluation error of this method can reach 0.02, the satisfaction of the respondents is 96%, the goal realisation coefficient is 0.99, and the evaluation effect is good.

Keywords: principal component analysis; PCA; AI technology; quality of smart teaching; impact assessment.

DOI: 10.1504/IJCEELL.2025.143794

International Journal of Continuing Engineering Education and Life-Long Learning, 2025 Vol.35 No.1/2, pp.95 - 111

Received: 15 Mar 2024
Accepted: 09 Sep 2024
Published online: 07 Jan 2025 *

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