Reimagining Educational Psychology and Pedagogical Innovation through AI-Driven Personalized Learning in Global Education Settings - Ricardo S. Jimenez; Aydin Anar Babayev; Zhala Rahman Aliyeva; Kamran Abdullayev (Edu Spectrum: Journal of Multidimensional Education, 2025)
This study examines how AI-driven personalized learning is reshaping educational psychology and pedagogical innovation across global learning environments. Using a qualitative methodology supported by library research and content analysis, the article synthesizes contemporary literature on adaptive learning systems, intelligent tutoring technologies, and real-time feedback mechanisms. Findings reveal that AI significantly reconfigures cognitive processes by providing individualized learning pathways, dynamic assessments, and continuous feedback that strengthen metacognitive skills and learner autonomy. The study further identifies the transformative role of AI in redefining student motivation, reinforcing self-regulated learning, and enhancing engagement through adaptive challenges and gamification elements. Pedagogically, AI shifts teachers’ professional identities toward roles as facilitators, data interpreters, and learning designers, underscoring the need for robust digital literacy and ongoing professional development. Additionally, AI implementation is shaped by cultural nuances and equity concerns, particularly regarding access, inclusivity, and algorithmic fairness. Ethical considerations related to data privacy, transparency, and student well-being are essential for sustainable AI integration. Overall, this study highlights AI’s potential to advance personalized learning while emphasizing the need for ethical, human-centered frameworks that protect learners and ensure equitable educational transformation.