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This research work introduces an innovative approach to educational assessment by development of an automated system for evaluating and ranking answer sheets. Inspired by the recent surge in LLM as a judge strategy, the system leverages the capabilities of the Gemini 1.5 Pro for Optical Character Recognition (OCR) and evaluation for precise and accurate assessment of answer sheets without human interference. The integration of necessary components has been implemented through Python, enhancing the efficiency and reliability of the evaluation process. The automated system significantly reduces human errors and biases, thereby providing a consistent and objective ranking of student performance. The results demonstrate that the system effectively delivers precise scores, addressing the common issues associated with manual evaluation.

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AI-Powered Answer Sheet Assessment and Ranking System

  • 会议论文

  • 发表日期：

    2026年

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  • Sravan Kotta,
  • Aryan Ilake,
  • Shreyas Konidala,
  • Namitha Prakash,
  • Ashika Jain,
  • Bhargavi Joshi,
  • Mrityunjoy Pandey,
  • Neha Sharma

摘要

This research work introduces an innovative approach to educational assessment by development of an automated system for evaluating and ranking answer sheets. Inspired by the recent surge in LLM as a judge strategy, the system leverages the capabilities of the Gemini 1.5 Pro for Optical Character Recognition (OCR) and evaluation for precise and accurate assessment of answer sheets without human interference. The integration of necessary components has been implemented through Python, enhancing the efficiency and reliability of the evaluation process. The automated system significantly reduces human errors and biases, thereby providing a consistent and objective ranking of student performance. The results demonstrate that the system effectively delivers precise scores, addressing the common issues associated with manual evaluation.