Impact of AI-Driven Curriculum Adaptation on Teacher Agency and Student Engagement in High and Low AI Adoption Education Systems

Abstract

This research investigates the impact of AI-driven curriculum adaptation on teacher agency and student engagement by comparing high and low AI adoption education systems. Utilizing a mixed-methods, comparative cross-national design, the study examines educators and students in Australia (high adoption) and Nigeria (low adoption). Findings indicate that teachers in high adoption systems report greater professional autonomy (mean = 4.032) compared to those in low adoption settings (mean = 3.956), as AI tools like ChatGPT facilitate more dynamic and tailored curriculum design. While AI significantly enhances student engagement through personalization and real-time feedback, challenges such as overstimulation, social isolation, and the need to balance algorithmic recommendations with pedagogical judgment persist. The study reveals that institutional support and clear policy frameworks are critical factors; high adoption systems benefit from structured training and infrastructure, whereas low adoption systems face barriers including resource constraints and limited AI literacy. The research concludes that while AI offers transformative potential for educational efficiency and student-centered learning, its successful integration requires robust policy development and comprehensive professional development to safeguard teacher agency.