THE STUDENTS' KNOWLEDGE TESTING SYSTEM WITH GAMIFICATION ELEMENTS
DOI:
https://doi.org/10.28925/2663-4023.2026.33.1177Keywords:
information educational system;, information system for testing students' knowledge with gamification elements;, educational content;, testing student knowledge;, hierarchical model;, gamification elementsAbstract
The described tools can be used to solve practical problems of ensuring the testing of knowledge of educational content provided to students studying in the specialty F2 "Software Engineering", using the appropriate educational information system. Tests on educational content are presented in the form of tables of the system database. The article considers the information system for testing student knowledge, which uses elements of gamification. The proposed system supports testing knowledge in the main academic disciplines of the specialty F2 and contributes to the process of optimizing data processing, which describes the process of testing knowledge. The educational components of the disciplines, from which knowledge testing is carried out, are organized in the form of a hierarchical model. The developed system for testing students’ knowledge operates in the "student" (for testing student knowledge) and "administrator" (for forming test tasks) modes. The work examines in detail the "student" mode and the system database. Analysis of the results of the knowledge test determines the automation of the formation of an appropriate decision to determine the material that the student has not mastered at the required level. The use of a web system contributes to the process of automating the testing of student knowledge. The proposed approach to testing students' knowledge is advisable to use in the future for prototyping subject ontologies of academic disciplines of specialty F2.
Downloads
References
Gómez-Vázquez, M., Cabot, J., & Clarisó, R. (2024). Automatic generation of conversational interfaces for tabular data analysis. In Proceedings of the ACM Conference on Conversational User Interfaces (CUI 2024) (pp. 1-6). https://doi.org/10.1145/3640794.3665577
Tkachenko, K., Tkachenko, O., & Tkachenko, O. (2023). The use of gamification elements in intellectual educational systems: Ontological aspect. Cybersecurity: Education, Science, Technique, 1(21), 32-47. https://doi.org/10.28925/2663-4023.2023.21.3247
Kotsiubivska, K., Tymoshenko, O., Khrushch, S., & Melnyk, I. (2025). Using artificial intelligence tools when developing a personalized learning plan. Digital Platform: Information Technologies in the Sociocultural Sphere, 8(1), 52-60. https://doi.org/10.31866/2617-796X.8.1.2025.335531
Zakrevska, L. (2019). Gamification in education: Methodology, technologies, tools. Osnovy.
Tkachenko, K., Tkachenko, O., & Raihorodskyi, D. (2025). Information system for testing students’ knowledge using gamification elements. Slovak International Scientific Journal, 101, 12-19.
Edutopia: Gamification in Education
Mauruner, O. (2019). Gamification in management and other non-game contexts: Understanding game elements, motivation, reward systems, and user types. Open Journal of Business and Management, 7(4), 1815-1830. https://doi.org/10.4236/ojbm.2019.74125
Werbach, K., & Hunter, D. (2012). For the win: How game thinking can revolutionize your business. Wharton Digital Press.
Gamasutra Gamification Topic
Dangpraserti, S. (2023). The impact of gamification on creative and innovative skills of graduate students. Journal of Theoretical and Applied Information Technology, 101(8), 3077-3087.
Zichermann, G., & Cunningham, C. (2011). Gamification by design: Implementing game mechanics in web and mobile apps. O’Reilly Media.
Yu-kai Chou Gamification & Behavioral Design
Spinify Gamification Examples
Marczewski Gamification Randomness Article
Tkachenko, O., Tkachenko, K., & Tkachenko, O. (2020). Designing complex intelligent systems based on ontological models. In Proceedings of the Third International Workshop on Computer Modeling and Intelligent Systems (CMIS 2020) (pp. 266-277).
Liu, G. Z. (2010). A key step to understanding paradigm shifts in e-learning: Towards context-aware ubiquitous learning. British Journal of Educational Technology, 41(2), E1-E9.
Scherer, M. U. (2016). Regulating artificial intelligence systems: Risks, challenges, competencies, and strategies. Harvard Journal of Law & Technology, 29(2).
Tkachenko, K. O. (2022). Using ontological modeling in the intellectualization of learning processes. Digital Platform: Information Technologies in the Sociocultural Sphere, 5(2), 261-270. https://doi.org/10.31866/2617-796X.5.2.2022.270130
Burov, E. V. (2012). Conceptual modeling of intelligent software systems. Lviv Polytechnic Publishing House.
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Костянтин Ткаченко, Ольга Ткаченко, Олександр Ткаченко

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.