Abstract—The Covid-19 pandemic has impacted the world of
education, especially for lower levels of education such as early
childhood education. It has changed its teaching pattern into
innovation by implementing online learning. Therefore,
teachers need to have a good self-regulated strategy to achieve
the online learning goals. This study aims to describe a
conceptual model for representing the self-regulated strategy of
early childhood teachers in digital learning using a quantitative
survey approach. The data collection involved 100 early
childhood teachers in Indonesia with a focus on the analysis of
three aspects of teachers’ behavior in a digital learning
environment: 1) IT experience, 2) IT motivation, and 3) online
self-regulated strategy. The study proposed a conceptual model
for teachers’ self-regulated strategy to implement digital
learning. The study also noted that based on the technology
perspective, both IT experience and IT motivation play a
critical role in affecting teachers’ self-regulated strategy for
digital learning. The main contribution of this study was to
provide an understanding of the importance of a self-regulated
strategy for teachers toward innovation in early childhood
education in a digital learning environment. In doing so, the
results of this study can be regarded as a starting point for
incentive future research for the successful implementation of
digital transformation in early childhood education.
Index Terms—Innovation learning, digital learning, digital transformation, early childhood education.
B. R. Aditya is with School of Applied Science, Telkom University, Indonesia.
Andrisyah is with Fakultas Ilmu Pendidikan, Institut Keguruan dan Ilmu Pendidikan Siliwangi, Indonesia.
Cite: Bayu Rima Aditya* and Andrisyah, "Digital Transformation in Early Childhood Education: Teachers’ Self-regulated Model for Digital Learning," International Journal of Information and Education Technology vol. 13, no. 2, pp. 329-334, 2023.Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).