AI Literacy and Professional Development Engagement as Predictors of Mathematics Teachers’ Readiness for AI-Enhanced Instruction

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Authors: Catherine Cuago Ruiz, Francis Michael Yambao
Cited by: 3

Abstract

This study examined how well AI literacy and professional development (PD) engagement can explain mathematics teachers’ readiness for AI-enhanced instruction. Data were collected through a quantitative correlational design from all mathematics teachers at a private school in Metro Manila using three standardized tools: the AI Literacy Scale, a PD Engagement Survey, and the AI Readiness Questionnaire (RAIS). Results showed that teachers were skilled in using, interpreting, and evaluating AI tools; however, only AI-related training influenced their readiness, largely due to time-related structural constraints. A strong, statistically significant positive correlation was found between AI literacy and AI readiness dimensions using Spearman’s rank correlation. Exploratory multiple regression analysis showed that AI literacy was the greatest contributor to the different domains of teachers’ readiness most of the time (? = 0.59 to 0.66, p < 0.01). PD engagement was shown to have a smaller, but significant impact (? = 0.31 to 0.36, p < 0.05). These findings emphasize the importance of supporting in field-specific professional development to strengthen mathematics teachers’ AI literacy to ready them to use AI in their teaching. The study suggests that embedding AI literacy in teacher education and offering flexible, relevant PD can help teachers adopt AI in mathematics classrooms in a responsible and effective way.

Fields of Study & Subjects

E-Learning and COVID-19 Teaching and Learning Programming Technology-Enhanced Education Studies

Publication details

Journal / source
International Journal of Learning Teaching and Educational Research
Publisher
Society for Research and Knowledge Management
Volume
25
Issue
2
Pages
655–675
Publication date
25 February 2026