GAZE DIRECTION MONITORING MODEL IN COMPUTER SYSTEM FOR ACADEMIC PERFORMANCE ASSESSMENT
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Keywords

remote education
testing
credibility
academic performance assessment
gaze
contract on the provision of educational services

How to Cite

[1]
O. Barkovska, Y. Liapin, T. Muzyka, I. Ryndyk, and P. Botnar, “GAZE DIRECTION MONITORING MODEL IN COMPUTER SYSTEM FOR ACADEMIC PERFORMANCE ASSESSMENT”, ITLT, vol. 99, no. 1, pp. 63–75, Feb. 2024, doi: 10.33407/itlt.v99i1.5503.

Abstract

This paper focuses on the research and application of eye movement and gaze direction analysis in online testing systems. The practical novelty of the proposed model of monitoring the direction of gaze in a computer-based knowledge control system lies in the possibility of automated remote control over a large audience of students. The practical significance lies in creating the same conditions for computer testing for all students and increasing the correspondence of knowledge level to the received test results. The implemented and tested system is relevant and necessary in higher educational institutions, particularly in Ukraine, where remote education has emerged as the safest means of acquiring knowledge. This is especially true for fields of study where practical tasks and laboratory work do not necessitate a student's physical presence at the institution. That is why the application of the latest information technologies is extremely important. The dynamic authentication based on the sequence of eye movements proposed in the model allows error-free user's eye area detection for further analysis of the test subject's behavior. The proposed authentication method excludes the need to enter passwords or CAPTCHAs, ensures the speed of determining the user's presence. Further analysis of the user's direction of vision includes responding to the information received, such as skipping a question or the need for re-authorization. Question skipping occurs when the system decides that the user has not been looking at the screen for an extended period (looking sideways, down, up for more than 30 seconds). Re-authentication becomes necessary if the user exits the test or if there is a user replacement. Real-time gaze control capability is implemented by using massive parallel processing system (NVIDIA GeForce GTX 1650 graphics card) for calculations. The analysis of the results obtained shows that the proposed approach allows gaze detection at different illumination ranges (from 0.3 lux to 10,000 lux), as well as to detect states of the user's eyes that violating test rules for further system response (skipping a question or re-authentication request).

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References

Verkhovna Rada of Ukraine. 7th session. (2017, Sept. 5). Law 2145-VIII, On Education. [Online]. Available: https://zakon.rada.gov.ua/laws/show/2145-19#Text. (in Ukrainian)

Verkhovna Rada of Ukraine. 4th session. (2014, Jul. 1). Law 1556-VII, On Higher Education. [Online]. Available: https://zakon.rada.gov.ua/laws/show/1556-18#Text. (in Ukrainian)

P. H. Luzan, Methods and Forms of Organization of Studies in Higher Agricultural School. Kyiv, Ukraine: Agricultural Education. 2003. (in Ukrainian)

I. Mintii, T. Vakaliuk, S. Ivanova, O. Chernysh, S. Hryshchenko and S. Semerikov, “Current state and prospects of distance learning development in Ukraine,” in CEUR Workshop Proc., 2021, pp. 41-55. (in English)

S. Voloshinov, V. Kruglyk, V. Osadchyi, K. Osadcha and S. Symonenko, “Realities and prospects of distance learning at higher education institutions of Ukraine,” in Ukr. J. of Educ. Stud. and IT, vol. 8, no. 1, 2020. (in English)

V. Banyoi, O. Kharkivska, H. Shkurko, and M. Yatskiv, “Tools for Implementing Distance Learning during the War: Experience of Uzhhorod National University, Ukraine,” in AWEJ, 2023. (in English)

O. V. Ovcharuk et al., “The use of digital tools by secondary school teachers for the implementation of distance learning in the context of digital transformation in Ukraine,” in CTE Workshop Proc., vol. 9, 2022, pp. 16-27. (in English)

H. Polianovskyi, T. Zatonatska, O. Dluhopolskyi and I. Liutyi, “Digital and technological support of distance learning at universities under COVID-19 (case of Ukraine),” in RREM, vol. 13, no. 4, 2021, pp. 595-613, Dec. 2021. (in English)

Ministry of Education and Science of Ukraine. (2013, Apr. 25). Order 466, On on the approval of the Regulations on distance learning. [Online]. Available: https://zakon. rada.gov.ua/laws/show/z0703-13. (in Ukrainian)

A. G. Spatioti, I. Kazanidis, J. Pange, “A comparative study of the ADDIE instructional design model in distance education,” in Inf., vol. 13, no. 9, 2022, p. 402. (in English)

M. Mayfield, “Creating training and development programs: using the ADDIE method,” in Develop. and Learn.in Org., vol. 25, no. 3, 2011, pp. 19-22. (in English)

R. Rabiman, M. Nurtanto, N. Kholifah, “Design and development e-learning system by Learning Management System (LMS) in vocational education,” in Online Submission, vol. 9, no. 1, 2020, pp. 1059-1063. (in English)

T. Elias, “Universal instructional design principles for Moodle,” in The Int. Rev. of Res. in Open and Distrib. Learn., vol. 11, no. 2, 2010, pp. 110-124. (in English)

A. M. Winsor, G. F. Pagoti, D. J. Daye, E. W.Cheries, K. R.Cave, E. M. Jakob, “What gaze direction can tell us about cognitive processes in invertebrates”, Biochemical and Biophysical Research Communications, 564, 2021, pp.43-54. (in English)

C.Katsini, Y.Abdrabou, G.E.Raptis, M.Khamis, F.Alt, “The role of eye gaze in security and privacy applications: Survey and future HCI research directions”, In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 2020, pp. 1-21. (in English)

N.Modi, J.Singh, “A review of various state of art eye gaze estimation techniques”, Advances in Computational Intelligence and Communication Technology: Proceedings of CICT 2019, pp.501-510. (In English)

I.S.Shehu, Y.Wang, A.M.Athuman, X. Fu, “Remote eye gaze tracking research: a comparative evaluation on past and recent progress”, Electronics, 10(24), 2021,3165. (in English)

B.Vijayalaxmi, C.Anuradha, K. Sekaran, M.N. Meqdad, S. Kadry,”Image processing based eye detection methods a theoretical review”, Bulletin of Electrical Engineering and Informatics, 9(3), 2020, pp.1189-1197. (in English)

B. Ngoc Anh, N. Tung Son, P.Truong Lam, L. Phuong Chi, N. Huu Tuan, N.Cong Dat, T. Van Dinh, “A computer-vision based application for student behavior monitoring in classroom”, Applied Sciences, 9(22), 2019, 4729. (in English)

S. Hutt, K. Krasich, C. Mills, N. Bosch, S. White, J.R. Brockmole, S.K. D’Mello, “Automated gaze-based mind wandering detection during computerized learning in classrooms”, User Modeling and User-Adapted Interaction, 29, 2019, 821-867. (in English)

A. Kaehler, G. R. Bradski, Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library, Japan, 2017. (in English)

J. Howse, J. Minichino, Learning OpenCV 4 Computer Vision with Python 3: Get to Grips with Tools, Techniques, and Algorithms for Computer Vision and Machine Learning, 3rd Ed, U.K.: Packt Publishing, 2020. (in English)

A. D. Moore, Python GUI Programming with Tkinter: Design and Build Functional and User-friendly GUI Applications. India: Packt Publishing, 2021. (in English)

M. Smart, Introduction to Data Science with Python: Basics of Numpy and Pandas. N.p.: Amazon Digital Services LLC - KDP Print US, 2018. (in English)

Cabinet of Ministers of Ukraine. (2020, Dec. 2). Order 1556, On the approval of the Concept of the development of artificial intelligence in Ukraine. [Online]. Available: https://zakon.rada.gov.ua/laws/show/1556-2020-%D1%80#Text. (in Ukrainian)

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Copyright (c) 2024 Олеся Барковська, Ярослав Ляпін, Тетяна Музика, Ігор Риндик, Павло Ботнар

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