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Grading Multiple Choice Exams with Low-Cost and Portable Computer-Vision Techniques

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Abstract

Although technology for automatic grading of multiple choice exams has existed for several decades, it is not yet as widely available or affordable as it should be. The main reasons preventing this adoption are the cost and the complexity of the setup procedures. In this paper, Eyegrade, a system for automatic grading of multiple choice exams is presented. While most current solutions are based on expensive scanners, Eyegrade offers a truly low-cost solution requiring only a regular off-the-shelf webcam. Additionally, Eyegrade performs both mark recognition as well as optical character recognition of handwritten student identification numbers, which avoids the use of bubbles in the answer sheet. When compared with similar webcam-based systems, the user interface in Eyegrade has been designed to provide a more efficient and error-free data collection procedure. The tool has been validated with a set of experiments that show the ease of use (both setup and operation), the reduction in grading time, and an increase in the reliability of the results when compared with conventional, more expensive systems.

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Notes

  1. http://www.gravic.com/remark/officeomr/ (accessed 10-1-2011).

  2. Available at http://www.it.uc3m.es/jaf/eyegrade.

  3. http://www.gradecam.com (accessed 10-1-2011).

  4. http://www.python.org/ (accessed 10-1-2011).

  5. http://opencv.willowgarage.com/ (accessed 10-1-2011).

  6. http://laurikari.net/tre/ (accessed 10-1-2011).

  7. http://www.pygame.org/ (accessed 10-1-2011).

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Acknowledgments

This work was partially funded by the EEE project, “Plan Nacional de I+D+I TIN2011-28308-C03-01” and the “Emadrid: Investigación y desarrollo de tecnologias para el e-learning en la Comunidad de Madrid” project (S2009/TIC-1650).

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Authors and Affiliations

  1. Department of Telematic Engineering, University Carlos III of Madrid, Avenida Universidad 30, 28911, Leganés (Madrid), Spain

    Jesus Arias Fisteus, Abelardo Pardo & Norberto Fernández García

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  1. Jesus Arias Fisteus
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  2. Abelardo Pardo
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  3. Norberto Fernández García
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Correspondence to Abelardo Pardo.

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Fisteus, J.A., Pardo, A. & García, N.F. Grading Multiple Choice Exams with Low-Cost and Portable Computer-Vision Techniques. J Sci Educ Technol 22, 560–571 (2013). https://doi.org/10.1007/s10956-012-9414-8

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  • DOI: https://doi.org/10.1007/s10956-012-9414-8

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