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Назва: Adaptive Testing Model as the Method of Quality Knowledge Control Individualizing
Автори: Shapovalova, Nonna
Rybalchenko, Olena
Dotsenko, Iryna
Bilashenko, Svitlana
Striuk, Andrii
Levan, Saitgareev
Ключові слова: adaptive testing
machine learning
psychological types of personality
Дата публікації: 30-чер-2019
Видавництво: Vadim Ermolayev, Frédéric Mallet, Vitaliy Yakovyna, Vyacheslav Kharchenko, Vitaliy Kobets, Artur Korniłowicz, Hennadiy Kravtsov, Mykola Nikitchenko, Serhiy Semerikov, Aleksander Spivakovsky
Бібліографічний опис: Shapovalova N. Adaptive Testing Model as the Method of Quality Knowledge Control Individualizing [Electronic resource] / Nonna Shapovalova, Olena Rybalchenko, Iryna Dotsenko, Svitlana Bilashenko, Andrii Striuk, Levan Saitgareev // ICTERI 2019: ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer : Proceedings of the 15th International Conference on ICT in Education, Research and Industrial Applications. Integration, Harmonization and Knowledge Transfer. Volume II: Workshops. Kherson, Ukraine, June 12-15, 2019 / Edited by : Vadim Ermolayev, Frédéric Mallet, Vitaliy Yakovyna, Vyacheslav Kharchenko, Vitaliy Kobets, Artur Korniłowicz, Hennadiy Kravtsov, Mykola Nikitchenko, Serhiy Semerikov, Aleksander Spivakovsky. – (CEUR Workshop Proceedings, Vol. 2393). – P. 984-999. – Access mode : http://ceur-ws.org/Vol-2393/paper_328.pdf
Короткий огляд (реферат): The mission of the work is to develop and theorize the efficiency of application of the knowledge control system on the basis of adaptive testing technology, which combines the specifics of the professional and educational activity and the monitoring of the quality of training and the possibility of self-control of students, to develop a set of test assignments in the discipline “Artificial Intelligence Systems”. Object of research is a software tool for monitoring students’ knowledge in higher educational establishment. The subject of research is the development of software for an adaptive knowledge control system using machine learning device. Research goals: to develop a set of test case of different levels of complexity; to determine the structure, architecture and specificity of the application of the machine learning algorithm for the formation of a variable level of testing complexity for each student; develop appropriate software, guidelines and recommendations for adjusting and distributing issues by level of complexity. The result of the work is a complex of split-level application-oriented tasks for current and module control in the discipline “Artificial Intelligence Systems”, web-oriented software that allows you to quickly monitor the quality of students’ knowledge and is appropriate for use in online and mixed mode of training.
URI (Уніфікований ідентифікатор ресурсу): http://elibrary.kdpu.edu.ua/xmlui/handle/123456789/3174
ISSN: 1613-0073
Розташовується у зібраннях:Кафедра інформатики та прикладної математики

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