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ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 3. Vol. 29. 2023
DOI: 10.17587/it.29.136-142
Yu. D. Bogolyubova, Senior Lecturer,
Moscow State University of Geodesy and Cartography,
A. A. Bukvich, Cand. Tech. Sc., Assistant Professor, S. M. Ivanova, Cand. Tech. Sc., Assistant Professor, Z. V. Ilyichenkova, Cand. Tech. Sc., Assistant Professor,
MIREA Russian Technological University, Moscow, Russian Federation
Using Keyboard Handwriting for Control in Learning Systems
The problem of student control with the help of keyboard handwriting is considered in the article. While working in an educational environment (for example, during certification), one of the users can perform tests for another. In this case, it is important to determine who exactly works at a particular moment in the training system. It is necessary to monitor continuously. It is advisable not to use personnel for this, as this is an unproductive waste of time. We assume that the full list of people working with the program at the moment is known. For analysis, data on the keyboard handwriting of each student are used, the characteristics of these data are determined in advance. The available information is represented as a set of vectors. Each of them contains a calculated handwriting characteristic corresponding to a particular user. The decision about the identity of the user is made depending on the similarity of the current and saved handwriting. To do this, the characteristics are compared at the present time with the saved ones. The scalar and vector methods of forming admissible areas for handwriting are considered. In the first case, a spherical region is formed, which simultaneously takes into account all the characteristics. The radius is defined as half of the minimum distance between points, which are vector coordinates that correspond to the characteristics of the keyboard handwriting. In the vector case, several linear regions are defined. Each area corresponds to one characteristic of the keyboard handwriting. The size of the area depends on the distance between the corresponding coordinates of the vector containing the data about the keyboard handwriting. Experimental data are presented to test the performance of the proposed control method. Keyboard handwriting contains the average values and standard deviations of the durations of pressing the keys and intervals of pauses. It is shown that in the scalar case the resulting regions have a larger radius than in the vector one. This reduces the number of type I errors.
Keywords: keyboard handwriting, learning systems, allowable range, user control
P. 136142
References
- Bilchuk M. V., Sosenushkin S. E. Digital transformation of a university: from strategy to implementation, Modern information technologies in the education, Collection of scientific papers of the XXII international scientific-practical conference, Moscow, 2022, pp. 2830 (in Russian).
- Sarkisova I. O. "Impossible" cases in ERP solution studies, Modern information technologies in the education, Collection of scientific papers of the XXII international scientific-practical conference, Moscow, 2022, pp. 4547 (in Russian).
- Kudzh S. A., Golovanova N. B. On improving training mechanisms teaching staff and prospects for targeted learning in the interests of universities, Russian Technological Journal, 2020, vol. 8, no 4 (36), pp. 112128 (in Russian).
- Aleshnikova E. L., Chadina Yu. A. Working with the text as a way to form students key competencies in modern Russian language textbooks, Modern textbook of the Russian language for secondary school: theory and practice, Materials of the international scientific-practical conference, Moscow, 2021, pp. 168175 (in Russian).
- Magomedov Sh. Architecture of a computing complex for web services and portals with multilevel access control over public networks, International Journal of Open Information Technologies, 2021, vol. 9, no 3, pp. 3643 (in Russian).
- Bogolyubova Yu. D., Bukvich A. A., Ivanova S. M., Ilyichenkova Z. V. Information system for determining the main structural characteristics during the construction of modern temple complexes, Industrial Automatic Control Systems and Controllers, 2022, no 1, pp. 4047 (in Russian).
- Chekushin A. V., Kotilevets I. D., Ivanova I. A., Chistyakova M. A. Handling hardware interrupts using the ATME-GA16 microcontroller as an example, Industrial Automatic Control Systems and Controllers, 2022, no 1, pp. 3339 (in Russian).
- Bogolyubova Yu. D., Ivanova S. M., Ilyichenkova Z. V. Using Certification and Motivation Tests in Training IT Specialists, Teaching information technology in Russia: Collection of research papers for the 20th open all-Russian conference (Moscow, Online, May 1920, 2022), Moscow, LLC "1C-Publishing", 2022, pp. 231232 (in Russian).
- Kuftinova N. G., Ostroukh A. V., Karelina M. Yu., Matyukhina E. N., Akhmetzhanova E. U. Enterprise Big Data Hybrid Intelligent Systems, STIN, 2021, no. 3, pp. 69 (in Russian).
- Ivanova S. M., Ilyichenkova Z. V. Authentication of users of mobile devices by keyboard handwriting, Vestnik MSTU Stankin, 2018. no 2 (45), pp. 8589 (in Russian).
- Nikolsky S. N., Antonova I. I., Gazanova N. Sh., Sum-kin K. S. Frame representation of a model-driven decision support system, Proceedings of Nizhny Novgorod State Technical University n.a. R. E. Alekseev, 2021, no 4 (135), pp. 1631 (in Russian).
- Joyce R., Gupta G. Identity Authentication Based on Keystroke Latencies, available at: http://www.cs.cmu.edu/~maxion/courses/JoyceGupta90.pdf
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