Modeling the Adoption of AI-Powered Learning Tools in Teacher Education

Valerie Jane Fontanilla Viernes; Noel A. Palapuz

doi:10.24036/pedagogi.v25i2.2526

Valerie Jane Fontanilla Viernes Isabela State University, Roxas, Isabela
Noel A. Palapuz Isabela State University, Roxas, Isabela

DOI: https://doi.org/10.24036/pedagogi.v25i2.2526

Keywords: AI adoption, teacher education, learning tools, self-efficacy, institutional support

Abstract

Integrating Artificial Intelligence (AI) in education reshapes teaching and learning, particularly in teacher education. This literature review investigates the adoption of AI-powered learning tools, focusing on pre-service mathematics teachers. It synthesizes cognitive factors such as perceived usefulness (PU), perceived ease of use (PEOU), prior exposure to AI tools, psychological factors like self-efficacy, and social influences like peer support and institutional support. Ethical concerns surrounding perceived trust, technological readiness, and attitudes toward AI in education are examined. Theoretical frameworks like the Unified Theory of Acceptance and Use of Technology (UTAUT) and Bandura’s self-efficacy theory are applied to understand AI adoption dynamics. The review finds that PU, PEOU, and institutional support are key predictors of AI adoption, while ethical barriers and technical readiness remain significant challenges. Recommendations are provided for overcoming these barriers to ensure equitable access to AI in teacher education.

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