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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Pandidurai, Rishapa
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Computer Science & IT Engineering

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GradeZen: automated grading ecosystem using deep learning for educational assessments Elangovan, Murugavalli; Kaleeswaran, Rajeswari; Mohankumar, Kathirvel; Rangachari, Shreya; Manivannan, Ubasini; Pandidurai, Rishapa; Bellarmin Joel, Maria; Murugesan, Preethi Meenatchi
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 14, No 3: June 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v14.i3.pp1809-1819

Abstract

This study introduces a groundbreaking software solution poised to revolutionize grading procedures in higher education through advanced artificial intelligence and machine learning techniques. Leveraging cutting-edge technologies such as YOLOv8 for real-time object detection, transformer-based optical character recognition (TrOCR), and Mixtral 8x7B transformer models for complex data analysis, the software automates the grading process. By significantly reducing the time and effort required for manual grading, it aims to streamline educational practices while ensuring consistency and scalability. The study provides a comprehensive analysis of use cases, identifies key issues in current grading methods, and elucidates the rationale driving its development. This innovative approach holds immense promise for transforming educational practices, fostering student success through efficient and artificial intelligence assisted automated assessment methodologies.
Co-Authors Bellarmin Joel, Maria Elangovan, Murugavalli Kaleeswaran, Rajeswari Manivannan, Ubasini Mohankumar, Kathirvel Murugesan, Preethi Meenatchi Rangachari, Shreya