ARTIFICIAL INTELLIGENCE IN TEACHING AND LEARNING: TRANSFORMING EDUCATION THROUGH INTELLIGENT TECHNOLOGIES AND PERSONALIZED LEARNING

Abstract

Abstract: The integration of Artificial Intelligence (AI) into educational environments has catalyzed a paradigm shift from standardized, traditional instructional frameworks toward dynamic, data-driven, and highly personalized learning ecosystems. This research paper provides a comprehensive synthesis of how intelligent technologies—spanning Intelligent Tutoring Systems (ITS), adaptive learning platforms, learning analytics, and Generative AI—are re-engineering teaching methodologies and learning environments. By analyzing theoretical paradigms, empirical implementations, and pedagogical implications, this study demonstrates that AI enhances knowledge acquisition, automates routine administrative and assessment burdens, and provides tailor-made instructional pacing. However, the adoption of AI in education introduces critical challenges regarding data privacy, algorithmic bias, academic integrity, and digital inequality. This paper concludes by proposing a human-in-the-loop framework that balances technological augmentation with human agency, ensuring ethical, equitable, and effective educational transformation. Keywords: Artificial Intelligence in Education (AIEd), Personalized Learning, Intelligent Tutoring Systems, Generative AI, Learning Analytics, Educational Technology, Human-in-the-Loop.