Readiness of Elementary School Teachers in Implementing AI-Based Learning in the Era of Artificial Intelligence
DOI:
https://doi.org/10.62951/icgel.v2i2.191Keywords:
AI-Based Learning, Educational Infrastructure, Educational Technology, Professional Development, Teacher readiness; Artificial intelligence in education; AI-based learning; Elementary school; Educational technologyAbstract
This study examines the readiness of elementary school teachers to implement AI-based learning in the era of artificial intelligence, as technological advancements increasingly influence instructional practices in basic education. Despite the growing potential of artificial intelligence to support teaching and learning processes, empirical evidence regarding teachers’ preparedness at the elementary level remains limited. This study employed a descriptive quantitative research design involving 18 elementary school teachers. Data were collected using a structured questionnaire consisting of 15 Likert-scale items measuring technological skills, knowledge of artificial intelligence, attitudes toward AI, pedagogical readiness, and infrastructure support. Descriptive statistical analysis revealed that the overall mean score of teachers’ readiness was 4.08, indicating that teachers are generally ready to adopt AI-based learning. Technological skills emerged as the strongest aspect of readiness, reflecting teachers’ familiarity with digital tools and instructional technologies, while infrastructure and institutional support obtained the lowest mean score, highlighting challenges related to facilities, access to technology, and policy support. These findings suggest that although elementary school teachers demonstrate positive readiness and attitudes toward AI-based learning, effective and sustainable implementation requires strengthened institutional support, improved infrastructure, and continuous professional development to maximize the educational benefits of artificial intelligence in elementary education.
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