Elementary School Teachers’ Readiness to Implement Coding and Artificial Intelligence Curriculum - Parulian Silalahi; Yang Agita Rindri; Charlota Agripina (Universitas Pendidikan Ganesha, 2026)
The rapid development of digital technology is driving the integration of coding and artificial intelligence (AI) learning as essential competencies in elementary school education. This study aims to analyze elementary school teachers' readiness to implement coding and AI curricula by examining five key factors: digital competence, digital pedagogical competence, attitudes toward technology, training experience, and external support. This study used a quantitative approach with a survey method involving 645 elementary school teachers in Bangka Regency. Data were collected using a validated questionnaire consisting of 40 Likert-scale statements and analyzed using descriptive statistics and multiple linear regression. The results showed that the level of teacher readiness was in the moderate category (mean = 3.04). The attitude toward technology dimension received the highest score, while training experience received the lowest score. The results of the regression analysis showed that digital competence was the most dominant factor influencing teacher readiness, followed by digital pedagogical competence, training experience, attitudes toward technology, and external support (p < 0.05). These findings indicate that although teachers have positive perceptions of coding and AI learning, their pedagogical and technical capabilities are still inadequate for optimal implementation. Therefore, systematic professional development programs, improved digital infrastructure, and ongoing institutional support are needed to strengthen teachers' readiness to integrate coding and AI in elementary schools.