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Proctoring Solution Using AI and Automation (Semi)

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Data Intelligence and Cognitive Informatics

Part of the book series: Algorithms for Intelligent Systems ((AIS))

Abstract

Most educational institutions, if not all, have adopted a remote learning-based system, which means all the exams or testing process needs to be remote. Analyzing the current situation, remote learning is going to be a huge market in the coming years. The pandemic has led to an unprecedented increase in demand for online applications which implement safe mechanisms to proctor online students. This paper is a documentation of an attempt to solve the same by implementing a semi-automated proctoring software with audio and vision functionalities combined through multithreading along with other features like authentication and portal services. To maintain its technical strength, the proposed research idea needs further study.

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References

  1. Labayen M, Ricardo V, Julián F, Naiara A, Basilio S (2021) Online student authentication and proctoring system based on multimodal biometrics technology. IEEE Access 9:72398–72411

    Google Scholar 

  2. Atoum Y, Chen L, Liu AX, Hsu SDH, Liu X (2020) Automated online exam proctoring. IEEE Trans Multimedia 19(7)

    Google Scholar 

  3. Mukhanbet AA, Nurakhov ES, Imankulov TS, Al-Farabi (2021) Hybrid architecture of face and action recognition systems for proctoring on a graphic processor. In: 2021 IEEE smart information systems and technologies (SIST), 28–30 April, 2021

    Google Scholar 

  4. Asep Hadian SG, Bandung Y (2019) A design of continuous user verification for online exam proctoring on M-learning. In: 2019 international conference on electrical engineering and informatics (ICEEI), July 2019, 9–10, Bandung, Indonesia

    Google Scholar 

  5. Muzaffar AW, Tahir M, Anwar MW, Chaudry Q, Mir SR, Rasheed Y. A systematic review of online exams solutions in e-learning: techniques, tools, and global adoption. IEEE Access. http://doi.org/10.1109/ACCESS.2021.3060192

  6. Boussakuk M, Ghazi ME, Bouchboua A, Ouremchi R (2019) Online assessment system based on IMS-QTI specification. In: Proceedings of 7th Mediterranean Congress of telecommunications (CMT), Oct 2019, pp 1–4

    Google Scholar 

  7. Wagstaff B, Lu C, Chen X (2019) Automatic exam grading by a mobile camera: snap a picture to grade your tests. In: Proceedings of 24th international conference on intelligent user interfaces: companion, pp 3–4

    Google Scholar 

  8. Chen Q (2018) An application of online exam in a discrete mathematics course. In: Proceedings of ACM Turing celebration conference (China), May 2018, pp 91–95

    Google Scholar 

  9. Lemantara J, Dewiyani Sunarto MJ, Hariadi B, Sagirani T, Amelia T (2018) Prototype of online examination on MoLearn applications using text similarity to detect plagiarism. In: Proceedings of 5th international conference on information technology, computer, and electrical engineering (ICITACEE), Sept 2018, pp 131–136

    Google Scholar 

  10. Fan Z, Xu J, Liu W, Cheng W (2016) Gesture-based misbehavior detection in online examination. In: Proceedings of 11th international conference on computer science and education (ICCSE), Aug 2016, pp 234–238

    Google Scholar 

  11. Allen IE, Seaman J (2019) Grade change: tracking online education in the United States, 2013, vol 3, no 5. Babson Survey Research Group, Quahog, pp 3–18

    Google Scholar 

  12. Guo P, Feng Yu H, Yao Q (2018) The research and application of online examination and monitoring system. In: Proceedings of IEEE international symposium on IT in medicine and education, Dec 2018, pp 497–502

    Google Scholar 

  13. Bashier HK, Abdu Abusham E, Khalid F (2012) Face detection based on graph structure and neural networks. Trends Appl Sci Res 7:683–691

    Article  Google Scholar 

  14. Jain V, Patel D (2016) A GPU based implementation of robust face detection system. Procedia Comput Sci 156–163

    Google Scholar 

  15. King DL, Case CJ (2019) E-cheating: incidence and trends among college students. Issues Inf Syst 15(1):20–27

    Google Scholar 

  16. Cluskey G Jr, Ehlen CR, Raiborn MH (2021) Thwarting online exam cheating without proctor supervision. J Acad Bus Ethics 4:1–7

    Google Scholar 

  17. Tesfamikael HH, Fray A, Mengsteab I, Semere A, Amanuel Z (2021) Simulation of eye tracking control based electric wheelchair construction by image segmentation algorithm. J Innov Image Process (JIIP) 3(01):21–35

    Google Scholar 

  18. Jung I, Yeom H (2019) Enhanced security for online exams using group cryptography. IEEE Trans Educ 52(3):340–349

    Article  Google Scholar 

  19. Wahid A, Sengoku Y, Mambo M (2015) Toward constructing a secure online examination system. In: Proceedings of the 9th international conference on ubiquitous information management and communication, Art. no 95

    Google Scholar 

  20. Rosen W, Carr M (2013) An autonomous articulating desktop robot for proctoring remote online examinations. In: Proceedings of IEEE frontiers in education conference, Oct 2013, pp 1935–1939

    Google Scholar 

  21. Das I, Sharma B, Rautaray SS, Pandey M (2019) An examination system automation using natural language processing. In: Proceedings of international conference on communication and electronics systems (ICCES), July 2019, pp 1064–1069

    Google Scholar 

  22. Potapov A (2017) Automatic image analysis and pattern recognition. LAP Lambert Academic Publishing, 292 p

    Google Scholar 

  23. Hamdan YB, Sathesh A (2021) Construction of efficient smart voting machine with liveness detection module. J Innov Image Process 3(3):255–268

    Google Scholar 

  24. Reale M, Canavan S, Yin L, Hu K, Hung T (2021) A multi-gesture interaction system using a 3-D iris disk model for gaze estimation and an active appearance model for 3-D hand pointing. IEEE Trans Multimedia 13(3):474–486

    Article  Google Scholar 

  25. Xiao B, Georgiou P, Baucom B, Narayanan S (2018) Head motion modeling for human behavior analysis in dyadic interaction. IEEE Trans Multimedia 17(7):1107–1119

    Article  Google Scholar 

  26. Abisado MB, Gerardo BD, Vea LA, Medina RP (2018) Towards academic affect modeling through experimental hybrid gesture recognition algorithm. In: Proceedings of international conference on data science and information technology (DSIT), pp 48–52

    Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Hindustan Institute of Technology and Science, Chennai, Tamil Nadu, India

    Ravi Sridharan, Linda Joseph & B. Sandhya Reddy

Authors
  1. Ravi Sridharan
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  2. Linda Joseph
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  3. B. Sandhya Reddy
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Corresponding author

Correspondence to Ravi Sridharan .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, GITAM University, Bangalore, Karnataka, India

    I. Jeena Jacob

  2. Department of Mathematics and Computer Science, Ashland University, River Forest, IL, USA

    Selvanayaki Kolandapalayam Shanmugam

  3. Department of Artificial Intelligence, Lviv Polytechnic National University, Lviv, Ukraine

    Ivan Izonin

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Sridharan, R., Joseph, L., Reddy, B.S. (2023). Proctoring Solution Using AI and Automation (Semi). In: Jacob, I.J., Kolandapalayam Shanmugam, S., Izonin, I. (eds) Data Intelligence and Cognitive Informatics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-19-6004-8_18

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