Deep Learning Methods Towards a Pedagogical Framework and Implementation Strategy: A Study of Information Technology Education Curriculum Development in Indonesia

The rapid advancement of artificial intelligence (AI), particularly deep learning, presents significant opportunities for transforming higher education curricula. This research aims to develop and implement a pedagogical framework for integrating deep learning into an information technology education program in Indonesia. Employing a design-based research (DBR) methodology, the study involved three iterative phases: needs analysis, framework design, and classroom implementation. Participants comprised 240 undergraduate students from the Department of Information Technology Education across all Indonesian universities. The framework emphasizes project-based learning, interdisciplinary integration, and the use of open-source deep learning tools. Data were collected through surveys, interviews, classroom observations, and pre- and post-tests. The results indicate that the integration of deep learning not only improved students’ technical competencies in machine learning and neural networks but also enhanced their problem-solving, collaboration, and critical thinking skills. Furthermore, both students and instructors reported increased engagement and motivation. This study contributes a replicable model for embedding deep learning in IT teacher education and offers practical guidelines for educators and curriculum developers. Future work will focus on scaling the framework and measuring its long-term impact on graduate preparedness and instructional innovation.