Early Elementary School Teachers' Knowledge of Deep Learning in Terms of Certified and Non-Certified Teacher Status - I Wayan Agus Ariasa; Putu Nanci Riastini; Rendy Setyowahyudi (Universitas Pendidikan Ganesha, 2026)
Twenty-first-century learning demands that teachers have a strong conceptual understanding of deep learning. However, empirical mapping of early elementary school teachers' knowledge levels and differences by teacher status remains very limited. This study aims to analyse and evaluate early elementary school teachers' knowledge of deep learning and compare it across teacher status. The study used a quantitative descriptive design. The study subjects were 32 early elementary school teachers, including 16 certified and 16 non-certified teachers. Data were collected using a 15-item multiple-choice objective test and analysed using descriptive statistics. The results showed an average score of 14.59, with 90.625% of teachers in the very high category and 9.375% in the high category. The average score for certified teachers was 14.19, while for non-certified teachers it was 15. In conclusion, early elementary school teachers' knowledge of deep learning falls in the very high category and shows no significant differences by teacher status. The implication is that professional development programs need to focus on strengthening the implementation of deep learning in the classroom, not just on conceptual aspects.