Automatic Grading of Scanned Multiple Choice Answer Sheets

  • Authors

    • Jirapond Muangprathub
    • Oatchima Shichim
    • Yuthaya Jaroensuk
    • Siriwan Kajornkasirat
    2018-04-20
    https://doi.org/10.14419/ijet.v7i2.23.11910
  • Optical mark reading, OMR, Automatic grading, Correlation coefficient, Multiple choice answer sheets.

  • Abstract

    The motivations for automatic grading of image-based multiple choice answer sheets include significant time and cost reductions. The proposed method supports any pencils or pens used on thin papers, as well as low-cost gridded paper that is easy to use in a typical test. Fourteen different scenarios pertaining to 560 answer sheets were evaluated with automatic reporting of the final grading and its summary. The result shows that an average accuracy of 100% for the cases with nearly complete pencil or pen markings. In the cases with incomplete markings, such as small markings, overflow, and deleted or unclean markings, the accuracies were 62.42%, 93.16%, 99.57%, respectively. The proposed system operates 2.5 times faster than the conventional manual method.

     

     

  • References

    1. [1] S. Kumar, “A Study on Optical Mark Readerâ€, International Interdisciplinary Research Journal, vol. 3(11). pp. 40-44, 2015.

      [2] H. Deng, F. Wang, B. Liang, “A Low-Cost OMR Solution for Educational Applicationsâ€, In Parallel and Distribut-ed Processing with Applications, ISPA'08. International Symposium on IEEE, pp. 967-970, 2008.

      [3] N.V. Patel, G. I. Prajapati, “Various Techniques for Assessment of OMR Sheets through Ordinary 2D Scanner: A Surveyâ€, International Journal of Engineering Research & Technology, vol.4(9), pp.803-807, 2015.

      [4] S. Gupta, G. Singla, P.S. Sandhu, “A Generalized Approach To Optical Mark Recognitionâ€, In International Con-ference on Computer and Communication Technologies, pp. 26-27,2012.

      [5] N.S. Ratchapaiboon, D. Jetpipattanapong, “Handwritten Digits OCR for Identifying Examinee Number on Objec-tive Test Answer Sheetâ€, Naresuan University Journal: Science and Technology, vol.22(2), pp.94-105, 2014.

      [6] S. Chatree, M. Phayung, S. Sunantha, “Scanner-based optical mark recognitionâ€, Information Technology Journal, vol. 5(1), pp.69-73.2009.

      [7] K. Chinnasarn, Y. Rangsanseri, “An Image-processing Oriented Optical Mark Readerâ€, International Symposium on Optical Science, Engineering, and Instrumentation, International Society for Optics and Photonics, pp. 702-708, 1999.

      [8] J.A. Levi, Y.A. Solewicz, Y. Dvir, Y. Steinberg, “Method of Verifying Declared Identity in Optical Answer Sheetsâ€, Soft Computing, vol.15(3), pp.461-468, 2011.

      [9] N. Sattayakawee, "Test Scoring for Non-Optical Grid Answer Sheet Based on Projection Profile Method," Interna-tional Journal of Information and Education Technology, vol. 3(2), pp. 273, 2013.

      [10] F. A. Zampirolli, J. A. Q. Gonzalez and R. P. O. Neves, "Automatic correction of multiple-choice tests using digital cameras and image processing," In the Proceedings of IX Workshop de Visão Computacional, pp. 1-6, 2013.

      [11] H.M. Parul, M. Kaur, “A novel optical mark recognition technique based on biogeography based optimizationâ€, International Journal of Information Technology, vol. 5(2), pp.331-333, 2012.

      [12] M. Gharavi-Alkhansari, “A Fast Globally Optimal Algorithm for Template Matching Using Low-Resolution Prun-ingâ€, IEEE Transactions on Image Processing, vol. 10(4), pp. 526-533, 2001.

      [13] N.R. Pai, S.K. Vijaykumar, “Design and Implementation of Optical Character Recognition using Template Match-ing for Multi Fonts/Sizeâ€. International Journal of Research in Engineering and Technology, vol. 4(2), pp.398-400, 2015.

      [14] J. P. Lewis, “Fast Template Matchingâ€, In Vision interface, vol. 95(120123), pp. 15-19. 1995.

      [15] J.A. Fisteus, A. Pardo, N.F. García, “Grading Multiple Choice Exams with Low-Cost and Portable Comput-er-Vision Techniquesâ€, Journal of Science Education and Technology, vol.22(4), pp.560-571, 2013.

      [16] A. Spadaccini, V. Rizzo, "A Multiple-Choice Test Recognition System based on the Gamera Framework," arXiv preprint arXiv:1105.3834, 2011.

      [17] A. A. Abbas, “An Automatic System to Grade Multiple Choice Questions paper based examsâ€, Iraqi Academic Scientific Journals, vol. 3(1), pp. 1-8, 2009.

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  • How to Cite

    Muangprathub, J., Shichim, O., Jaroensuk, Y., & Kajornkasirat, S. (2018). Automatic Grading of Scanned Multiple Choice Answer Sheets. International Journal of Engineering & Technology, 7(2.23), 175-179. https://doi.org/10.14419/ijet.v7i2.23.11910

    Received date: 2018-04-22

    Accepted date: 2018-04-22

    Published date: 2018-04-20