Quality Concerns in Teacher-Delivery and Student - Progression: A Meta-analytic Review of AI Integration in Teaching Pedagogy

The introduction of Artificial Intelligence (AI) in teaching-learning systems has generated significant deliberation regarding its application, efficiency and implications on teaching quality, student progression and the overall quality of education, thereby bringing changes in the nature of school psychology today. This meta-analytic review examines quality concerns related to teacher delivery and student progression amidst AI integration and addresses the challenges arising thereof. Changing dynamics of how students learn, apply theory to practice and integrate teachings to real world challenges were discussed with emphasis on the changing ethos of student progression. The review underscores the necessity for balanced AI adoption, emphasizing the importance of teacher training, ethical guidelines, and the maintenance of human-centric educational approaches. Integrating AI opens up new possibilities, potentials, and challenges in educational practice. As AI simulates human intelligence in arriving at conclusions or predictions, such technology can provide tailored guidance and feedback to students and enhance the teachers’ role as a facilitator and mentor in the educational process. It is concluded that AI must be used as a supplementary tool rather than a substitute for human educators and that responsible AI integration requires continuous oversight, training, and ethical governance.