Empowering Teachers for the AI-GenAI Era: Predictors of Digital Competence in Curriculum Innovation

Abstract

Artificial Intelligence (AI) and, more recently, Generative Artificial Intelligence (GenAI), have emerged as innovative technologies with strong potential for educational planning and the creation of learning resources. However, their effective integration into teaching requires teachers to demonstrate sufficient digital competence. This study aimed to analyze and compare teachers’ self-assessment of their digital competence in the use of GenAI tools for curriculum planning, while considering the influence of different sociodemographic and professional variables. Specifically, the objectives were: (1) to determine teachers’ self-perception of digital competence in using GenAI for curriculum planning, according to educa- tional stage, and (2) to examine whether significant differences exist in digital competence across sex, type of territory, prior training in educational technology, and creativity in the development of educational content. A quantitative, ex post facto design was applied, using a non-probabilistic purposive sample of 502 in-service teachers from the Dominican Republic, covering early childhood, primary, secondary, and higher education. The data were collected using an instrument developed by the authors themselves, which measures self-perception in digital competence, based on the Technology Acceptance Model (TAM) framework. The findings revealed a medium–high level of perceived digital competence, with Early Child- hood Education teachers achieving the highest scores. Significant differences were observed in relation to prior training and creativity, whereas no effect was found for territory. In higher education, sex differences emerged in favor of female teachers. These results highlight the importance of fostering continuous training and creativity-oriented strategies to enhance digital competence for GenAI-based curriculum innovation.