An Efficient Read and Mark Mechanism for Multiple-choice Questions Using Optical Character Recognition

Muhammad Usman; Shah Khalid; Aftab Alam; Muhammad Ubaid; Fakhrud Din; Muhammad Raees

Authors

Muhammad Usman Department of Computer Science and IT, University of Malakand, Chakdara, Pakistan
Shah Khalid Department of Computer Science and IT, University of Malakand, Chakdara, Pakistan
Aftab Alam Department of Computer Science and IT, University of Malakand, Chakdara, Pakistan
Muhammad Ubaid Department of Computer Science and IT, University of Bahria, Islamabad, Pakistan
Fakhrud Din Department of Computer Science and IT, University of Malakand, Chakdara, Pakistan
Muhammad Raees Governament Degree College Totakan, Higher Education Department, Kim Pakistan

Keywords:

Multiple Choice Questions, Optical Mark Recognition, Optical Character Recognition, International Business Machines, Computer Vision 2, Identification, Pakistani Rupee, Personal Computers

Abstract

This research paper focuses on modifying the grading of multiple-choice questions (MCQs) to better the efficiency and incorrectness of educational tests. Conventional grading systems, such as optical mark recognition (OMR), have fundamental drawbacks, excluding the necessity for precise shading, time-wasting, and the use of special OMR sheets and OMR scanners. This conceptualization can be expensive and error-prone, especially if the MCQs papers are folded or unmarked. In comparison, the suggested OCR-based approach gives fundamental benefits in all necessary areas. It is less costly to use a simple scanner and software alternatively to costly OMR equipment. The method is motivated to be simple to set up and use. It importantly reduces error rates and marking time by employing precise OCR algorithms and processing greater amounts of answer sheets quickly. Moreover, the system is extremely accurate and scalable, allowing it to handle a rising amount of paper efficiently. It also has limited trust in external tools and is highly flexible and adaptable to different MCQ formats and grading settings. In General, the OCR-based approach outperforms existing methods by eliminating their shortcomings and delivering a trustworthy, time-saving alternative for automated MCQ grading.

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