Revolutionizing Educational System: An AI-Driven Framework for Automated Grading and Feedback

Revolutionizing Educational System: An AI-Driven Framework for Automated Grading and Feedback

Darshan Madhani

PhD Research Scholar, Department of Computer Science,
Atmiya University, India

1.Abstract

As digital learning platforms become more common, so does the need for intelligent scaling solutions that can help screen and assess candidates quickly and efficiently. Conventional assessments based on coffee-stained papers can be tedious, impersonal, and not seamlessly optimized to fine-tune the feedback efficacy across the range of evaluative functions. We present a novel paradigm of AI assessment models that support automation of marking as an observation with personalized feedback specifically at the scale for each learner. This paper presents an intelligent framework that employs Natural Language Processing (NLP), machine learning algorithms, and educational data mining (EDM) techniques to reduce instructor workload along with improving students’ engagement and learning success. Furthermore, it provides detailed analysis of current AI grading systems only to expose their lack of supporting adaptive feedback mechanisms and suggests a hybrid AI grading system with real-time feedback generation capability. Our preliminary experiments with publicly-available data shows that it has shown positive grades accuracy and meaning of the feedback is adaptive.

Keywords: Artificial Intelligence (AI), Automated Grading, Adaptive Feedback, Higher Education, Educational Assessment, Machine Learning, Personalized Learning, Learning Analytics, Intelligent Tutoring Systems, Technology-Enhanced Learning.