Перспективы использования языка описания онтологий ONTOL V2 в автоматизации процедуры проверки знаний
Аннотация
В данной работе рассматриваются перспективы использования языка описания онтологий ONTOL V2, являющегося модифицированной версией языка ONTOL V1, который разработан для автоматизации проведения процедуры проверки знаний студентов инженерных специальностей. Обоснована необходимость перехода от моделирования к метамоделированию. Приведён и разобран пример автоматизации лабораторной работы по пользовательским интерфейсам.
Литература
Novikov F. A., Molotkov A. V. Ontology of Discrete Mathematics in Education // Computer Tools in Education. 2021. No. 1. P. 5–16. (in Russian)
Aptukov M. I., Markov M. D., Novikov F. A., Pestryakov D. D., Skvortsov V. S., Khamidullin I. I. Ontology description language ONTOL V1 // Computer Tools in Education. 2025. No. 1. P. 91–107. (in Russian)
Lavrov S. S. Knowledge representation in computerized systems // Microprocessors devices and systems. 1986. No. 3. P. 14–19. (in Russian)
Azarova R. N., Zolotareva N. M. Development of a Competence Passport: Methodological Guidelines for Organizers of Project Work and University Teaching Staff. First Edition. – Moscow: Research Center for Quality Issues in Specialist Training, Coordination Council of Educational and Methodological Associ- ations and Scientific and Methodological Councils of Higher Education, 2010. – 52 p. (in Russian)
Practical Guide for Model Selection for Real-World Use Cases [Online]. Available: https://cookbook. openai.com/examples/partners/model_selection_guide/model_selection_guide (accessed: 01.10.2025).
Novikov F. A., Ivanov D. Yu. Modeling in UML. Theory, Practice, Video Course. — St. Petersburg, Professional Literature, Science and Technology, 2010 - 640 p.
Zorin Yu. A., Posov I. A. Instrumented systems for construction and obtaining multivariate test tasks // Computer Tools in Education. 2014. No. 1. P. 14–25. (in Russian)
MetaObject Facility | Object Management Group [Online]. Available: https://www.omg.org/mof/ (accessed: 01.10.2025).
Kosovskaya T. M. Comparison of Different Knowledge Representations for Complex Structured Objects in Solving AI Problems // Computer Tools in Education. 2021. No. 2. P. 41–57. (in Russian)
Terekhov A. N. Library Preambles and Separate Procedure Translation in the Algol 68 Compiler // Abstracts of Papers and Reports for the All-Union Conference. Part 2. 1980. P. 253-255. (in Russian)
Polyakov K. Yu. Robot Control Using Blockly // Information Technologies in Education. 2020. No. 3. P. 182–186. (in Russian)
terrastruct/d2: D2 is a modern diagram scripting language that turns text to diagrams. [Online]. Avai- lable: https://github.com/terrastruct/d2 (accessed: 01.10.2025).
Carta S. et al. Iterative zero-shot llm prompting for knowledge graph construction // arXiv preprint arXiv:2307.01128. – 2023.
Wang J. et al. Boosting language models reasoning with chain-of-knowledge prompting //arXiv prepri- nt arXiv:2306.06427. – 2023.
Peng B. et al. Graph retrieval-augmented generation: A survey //arXiv preprint arXiv:2408.08921. – 2024.
Luo L. et al. Reasoning on graphs: Faithful and interpretable large language model reasoning //arXiv preprint arXiv:2310.01061. – 2023.
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