Abstract
The integration of Artificial Intelligence (AI), particularly Large Language Models (LLMs), into educational practices has become increasingly relevant, influencing pre-service teachers' preparedness and engagement. This study examines the readiness and concerns of pre-service teachers in adopting AI-LLMs for teaching, filling a gap in literature on AI's role in teacher education. Using a cross-tabulation analysis of survey data from 685 respondents across different educational majors and academic levels, the study highlights variations in AI adoption, familiarity, and ethical considerations. Findings indicate that AI engagement grows with academic progression, with Secondary Education majors demonstrating higher adoption rates than Elementary Education majors. While students recognize AI’s potential in lesson planning, content creation, and personalized learning, barriers such as limited access, lack of structured AI training, and ethical concerns—including plagiarism risks and over-reliance—persist. Despite these challenges, most respondents express interest in formal AI training, underscoring the need for targeted curriculum integration. Addressing these concerns through structured teacher preparation programs will be crucial to ensuring responsible AI use while maximizing its benefits in education. The study advocates balancing traditional teaching methods with AI-assisted approaches, fostering critical AI literacy among future educators.
Recommended Citation
Núñez, Jayrome L.; Lived, Wendell A.; Urbano, Jomar M.; Jamisal, Mark Anthony F.; and Hontiveros, Mariecres B.
(2025)
"Integrating AI-LLMs Into Educational Practices: A Study on Pre-Service Teachers' Readiness and Concerns,"
FDLA Journal: Vol. 9, Article 20.
Available at:
https://nsuworks.nova.edu/fdla-journal/vol9/iss1/20