Citation

Law, Check Yee and Li, Yi Ting and Sek, Yong Wee and Chong, Lee Ying and Arrang, Hermin (2026) AI-Powered Study Planner Prototype System. Lecture Notes in Networks and Systems, 2036. pp. 104-120. ISSN 2367-3370

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Abstract

Delays in graduating in higher education not only affect students and parents but also the educational institutions. Time management and academic planning are important aspects for graduating on time in higher education. Besides that, the manual way of lecturers tracking a student’s status of graduating on time is a time-consuming process and is prone to human error, especially when managing many students. With the growing trend of technology, there is a rising need for Artificial Intelligence (AI) systems that can assist students in planning their academic process and studies while supporting lecturers in monitoring student academic progression. This research proposes an intelligent, automated framework that minimizes the gap between static academic documents and dynamic student advisory interventions. A system known as AI-Powered Study Planner is designed and developed to monitor student progress throughout their studies in higher education. The proposed system has integrated Optical Character Recognition (OCR) to extract key information from academic documents, and the extracted data will be processed using the Gemini API to generate a personalized study plan and academic advice for users. By integrating the automated extraction of unstructured documents and generating personalized study plans, the proposed system reduces the manual tracking burden of academic advisors and provides students with correct pathways to ensure graduation on time.

Item Type:	Article
Uncontrolled Keywords:	Academic planning, Advisory system, Graduate On Time (GOT)
Subjects:	L Education > LB Theory and practice of education > LB2300 Higher Education Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	02 Sep 2026 08:51
Last Modified:	02 Sep 2026 08:51
URII:	http://shdl.mmu.edu.my/id/eprint/16552

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