A Study of the Internal and External Factors Influencing the Adoption of Artificial Intelligence by Elementary School Math Teachers

Abstract

The variables impacting the adoption and use of Artificial Intelligence (AI) in elementary mathematics education
are thoroughly examined in this research. The study uses a quantitative research approach and incorporates
empirical data obtained from Chinese primary mathematics instructors using the Technology Acceptance Model
(TAM) and Technological Pedagogical and Content Knowledge (TPACK). Teacher attitudes, contextual variables,
educational obstacles, family and community participation, and other relevant dimensions are examined via the use
of Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that there is a strong correlation
between teacher attitudes and the adoption of AI. By narrowing down on AI in elementary math education, this
research adds to the body of knowledge on the topic and calls attention to the need for strategic professional
development programs to improve teachers' comfort with and competence using AI tools. Furthermore, the study
highlights the importance of TPACK via its crucial function in providing educators with the expertise needed to
successfully incorporate AI into mathematics curricula. In addition, the research delves into the intricate interplay
between AI integration and contextual variables and educational hurdles, highlighting the need of systemic
measures that include governmental shifts and institutional backing. We also take a look at the indirect channels by
which TPACK influences AI use, as well as the role of parents and the community, to provide light on the complex
nature of technology adoption in schools. Educators, legislators, and stakeholders may benefit from its practical
consequences, and it adds to the intellectual conversation on technology integration in education.