Preparing Indonesian Primary School Teachers for Deep Learning: Readiness, Challenges, and Institutional Support

Abstract

The growing influence of deep learning technologies in everyday life has created new demands for educational systems worldwide, prompting efforts to introduce basic concepts of artificial intelligence at earlier stages of learning. In Indonesia, while digital literacy initiatives are gaining momentum, the preparedness of primary school teachers to teach deep learning concepts remains largely unexplored. This study aims to investigate the readiness of Indonesian primary school teachers to teach fundamental deep learning principles, identify the challenges they face, and assess the level of institutional support available to them. A mixed methods design was employed, combining quantitative survey data from 215 teachers with qualitative insights gathered through focus group interviews. The survey measured readiness across technical, pedagogical, and institutional dimensions, while thematic analysis was used to explore deeper experiences and perspectives. The findings reveal that while teachers express strong enthusiasm and recognize the importance of introducing deep learning, their technical understanding and pedagogical confidence remain moderate. Access to training opportunities and digital infrastructure emerged as critical enablers, whereas a lack of curricular guidance and institutional support was cited as major barriers. Teacher motivation is not lacking; rather, systemic support must be strengthened to turn readiness into effective practice. Preparing teachers for deep learning education requires comprehensive strategies that integrate professional development, curriculum design, and infrastructure improvement. This study enriches the limited literature on AI education at the primary level in developing countries and offers practical recommendations for policymakers and educational stakeholders seeking to build future-ready classrooms.