Volume 2 - Issue 2, March - April 2026

The purpose of this research is to design and implement an AI-powered Adaptive Study Management System (StudyAdaptAI) that dynamically adjusts student learning plans and study schedules based on real-time academic behavior and performance analytics. The system utilizes artificial intelligence algorithms to recommend personalized study sessions, optimize time management, and provide adaptive feedback to enhance student productivity. The developmental approach integrates machine learning models trained to analyze student interactions, predict focus intervals, and recommend learning resources. System testing with IT students evaluated efficiency, usability, and accuracy using the System Usability Scale (SUS). Results indicated a SUS score of 86.8, interpreted as Excellent usability, confirming StudyAdaptAI’s capability to personalize study experiences and improve academic outcomes.

Reginald S. Prudente, John Lloyd Cruz, Regine Mountal, Jan Mark Sorita,"Design and Implementation of an Adaptive Study Management System Using Artificial Intelligence (StudyAdaptAI)" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(1592-1604) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.