Can AI Assistance Aid in the Grading of Handwritten Answer Sheets?

TL;DR

This paper presents an AI-assisted grading pipeline that uses text detection to identify question regions and highlight keywords in handwritten answers, significantly reducing grading time in real-world settings.

Contribution

It introduces a novel AI-assisted grading system with a practical implementation and evaluation on real exams, demonstrating substantial time savings for graders.

Findings

Grading time reduced by 31% per response

Overall grading time reduced by 33% per answer sheet

Effective in real-world educational settings

Abstract

With recent advancements in artificial intelligence (AI), there has been growing interest in using state of the art (SOTA) AI solutions to provide assistance in grading handwritten answer sheets. While a few commercial products exist, the question of whether AI-assistance can actually reduce grading effort and time has not yet been carefully considered in published literature. This work introduces an AI-assisted grading pipeline. The pipeline first uses text detection to automatically detect question regions present in a question paper PDF. Next, it uses SOTA text detection methods to highlight important keywords present in the handwritten answer regions of scanned answer sheets to assist in the grading process. We then evaluate a prototype implementation of the AI-assisted grading pipeline deployed on an existing e-learning management platform. The evaluation involves a total of 5 different real-life examinations across 4 different courses at a reputed institute; it consists of a total of 42 questions, 17 graders, and 468 submissions. We log and analyze the grading time for each handwritten answer while using AI assistance and without it. Our evaluations have shown that, on average, the graders take 31% less time while grading a single response and 33% less grading time while grading a single answer sheet using AI assistance.