Pedagogical Transformation in the Digital Age: An Analysis of AI's Impact on Teacher Strategies in Primary Education

Abstract

The fast adoption of artificial intelligence (AI) in primary education is transforming the past practices of teaching but there is little empirical evidence on the effects of it on the teaching behaviors of teachers. This paper discusses the role of AI technology in changing the teaching techniques in the primary school through the use of the technology acceptance model (TAM) as the theoretical framework. A quantitative methodology was embraced, and a sample size of 466 vocational and basic-stage teachers in various provinces in China was used in gathering data through a five point Likert scale questionnaire. The hybrid Linear Discriminant Analysis-Random Forest (LDA-RF) model was used to categorize and forecast the determinants of the AI-assisted teaching performance. The findings prove that perceived usefulness, perceived ease of use, and ease of learning significantly affect AI adoption with the highest level of accuracy 91.0, precision 88.7, and F1-score 89.5. The results emphasize the great potential of AI to increase the teaching innovation, individual learning, and decision-making processes based on data. But the use of self-reported information and the constraints provided by the context impairs generalizability. Future research ought to assume longitudinal, multi-regional and explainable AI methods to enhance robustness and explainability.