Enhancing Customs Administration Education through AI-Driven Personalized Learning: A Case Study at Mariners Polytechnic Colleges Foundation of Canaman

Abstract

As education strives for sustainable development, innovative approaches are crucial for enhancing teaching practices and student outcomes. AI-driven personalized learning offers a promising solution by tailoring educational experiences to individual needs, potentially revolutionizing teacher-student collaboration. This study aims to explore the impact of AI-driven personalized learning on teacher-student collaboration and its contribution to sustainable educational development. It seeks to identify how AI enhances collaborative learning environments and what challenges arise during implementation.A mixed-methods approach will be employed, combining surveys, interviews with educators and students, and observations of AI-integrated classrooms. Quantitative data will be analyzed statistically to assess changes in collaboration metrics, while qualitative data will undergo thematic analysis to explore perceptions and experiences. Preliminary findings suggest that AI-driven personalized learning significantly enhances teacher-student collaboration by providing real-time feedback, automating routine tasks, and fostering more inclusive learning environments. However, challenges such as digital literacy gaps and infrastructure limitations are also anticipated. This research contributes to the discourse on sustainable development in education by highlighting AI's potential to create future-ready educational systems. It offers insights for educators, policymakers, and technology developers on how to leverage AI for more effective and sustainable teacher-student collaboration.