Fuzzy Logic-Based Clustering of Teacher Digital Pedagogy Using Cybergogy Framework for Sustainable Educational Innovation

Rapid changes in educational technology necessitate innovative approaches to sustainable teacher development. However, implementing learning technologies like Cybergogy faces significant challenges due to imbalances in digital pedagogy competencies and motivation among secondary school mathematics teachers. This study aims to cluster mathematics teachers' profiles based on the Cybergogy model's application using the Fuzzy C-Means (FCM) algorithm. The study involved 88 mathematics teachers from various secondary schools in Yogyakarta, Indonesia. Clustering results converged at the sixth iteration with an objective function value of 620.006, and an optimal two-cluster structure (PCI = 0.5578). Cluster 1 comprises teachers with high digital competencies and effective use of online learning media in understanding Cybergogy. Conversely, Cluster 2 includes teachers with limited online learning experience and low Cybergogy understanding. These findings highlight the lack of appropriate training efforts to support technology implementation and motivate each cluster based on their unique perceptions of Cybergogy. This study contributes to educational technology by offering insights into how the Cybergogy model can enhance digital learning quality, with long-term implications for teacher competency development and the sustainability of digital education innovation in Indonesia.