Authors :
Janardhan Singh K.; Sanjay Kulkarni; Sanket B Patil; Shashank M; Shashanka UN
Volume/Issue :
Volume 9 - 2024, Issue 5 - May
Google Scholar :
https://tinyurl.com/35jrkvxp
Scribd :
https://tinyurl.com/2haje3vm
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAY1072
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
The paper highlights the necessity for a
technologically advanced system capable of efficiently
grading multiple-choice question (MCQ) exams through
webcam-based evaluation. MCQ-style assessments have
gained widespread use in educational and organizational
settings due to their effectiveness and time-saving
advantages. However, manually grading these exams
presents significant challenges. Managing a large number
of answer sheets in a timely manner is labor-intensive and
error-prone, potentially leading to scoring discrepancies.
Additionally, the logistical burden of storing and handling
physical answer sheets is cumbersome, with risks such as
damage from environmental factors like fire or moisture.
While larger institutions may utilize specialized Optical
Mark Recognition (OMR) technology for grading, smaller
educational entities often lack access to such costly
equipment. To address these challenges, the paper proposes
an innovative solution: leveraging webcam technology to
automate the grading process. By capturing images of
answer sheets and employing sophisticated content-filtering
and image processing algorithms facilitated by the OpenCV
library, the system can accurately interpret and evaluate
marked answers. Overall, the proposed system represents a
significant advancement in exam grading methodology,
providing a practical and cost-effective solution to the
longstanding challenges associated with manual grading of
MCQ-based assessments. By integrating webcam
technology into the grading process, the system aims to
enhance efficiency and accuracy while catering to the needs
of various educational and organizational assessments.
References :
- Fairley R. (2002) Software Engineering Concepts (For project size) New York: Tata Mac Graw Hill.
- A. M. Smith, “Optical mark reading - making it easy for users”, In Proceedings of the 9th annual ACM SIGUCCS conference on User services, United States, 1981, pp:257-263.
- Ngo Quoc Tao and Do Nang Toan “Some Charactistical aspects of Markreader Software Package for Automatic Mark Data Entry”, Circuits and Systems, 2002. APCCAS'02, pages 437 - 442 vol.2, 2002
- Palmer, Roger C., The Basics of Automatic Identification [Electronic version] Canadian Datasystems, 21 (9), p. 30-33, Sept 1989.
- Jalote P. (2005) Software Project Management In Practices-3rdEdition, United States of America: Springer Science + Business Media, Inc.
The paper highlights the necessity for a
technologically advanced system capable of efficiently
grading multiple-choice question (MCQ) exams through
webcam-based evaluation. MCQ-style assessments have
gained widespread use in educational and organizational
settings due to their effectiveness and time-saving
advantages. However, manually grading these exams
presents significant challenges. Managing a large number
of answer sheets in a timely manner is labor-intensive and
error-prone, potentially leading to scoring discrepancies.
Additionally, the logistical burden of storing and handling
physical answer sheets is cumbersome, with risks such as
damage from environmental factors like fire or moisture.
While larger institutions may utilize specialized Optical
Mark Recognition (OMR) technology for grading, smaller
educational entities often lack access to such costly
equipment. To address these challenges, the paper proposes
an innovative solution: leveraging webcam technology to
automate the grading process. By capturing images of
answer sheets and employing sophisticated content-filtering
and image processing algorithms facilitated by the OpenCV
library, the system can accurately interpret and evaluate
marked answers. Overall, the proposed system represents a
significant advancement in exam grading methodology,
providing a practical and cost-effective solution to the
longstanding challenges associated with manual grading of
MCQ-based assessments. By integrating webcam
technology into the grading process, the system aims to
enhance efficiency and accuracy while catering to the needs
of various educational and organizational assessments.
