Abstract
The rapid digital transformation of teacher education requires instructional models that integrate established pedagogical frameworks with emerging Artificial Intelligence (AI) tools. This study investigates the effectiveness of a unified Substitution, Augmentation, Modification, Redefinition-Technological Pedagogical Content Knowledge-Artificial Intelligence (SAMR–TPACK–AI) framework for enhancing learning outcomes among pre-service computer science teachers. A quasi-experimental design was implemented with over 150 participants across control and experimental groups, using validated instruments and mixed-methods analysis (Analysis of Covariance (ANCOVA), Linear Mixed Model (LMM)). Findings demonstrate significant gains in the experimental group: academic performance increased by 12.2 percentage points, motivation by 0.52 points, and digital competencies by 14.9 points. Cross-disciplinary outcomes also improved, including critical thinking and teamwork skills. The results provide empirical validation of the integrated SAMR–TPACK–AI framework as an effective digital learning design. The study offers a novel conceptual contribution to AI-enhanced digital pedagogy and provides practical implications for developing sustainable, future-oriented teacher education programs.