APPLYING TEXT QUESTIONS GENERATION ALGORITHMS FOR AUTOMATIC TEST GENERATION
https://doi.org/10.35266/1999-7604-2023-3-17-22
Abstract
The article presents findings of manual, semi-automatic, and automatic approaches to generate test questions based on such methods as annotation, keyword extraction, and learning datasets for compiling tests for studying material, along with a description of each method algorithm, examples of generated questions, and their quality assessment. These examples demonstrate the advantages of an algorithm for generating a method using a dataset and a combination of methods, as well as their possible practical application.
Supporting agencies: the study is conducted in the framework of a State task No. 071-03-2023-001.
About the Authors
Aleksey A. Vasilyev
Siberian State University of Telecommunications and Information Science, Novosibirsk
Russian Federation
Russian Federation
Lecturer
Andrey S. Nesterov
Siberian State University of Telecommunications and Information Science, Novosibirsk
Russian Federation
Russian Federation
Candidate of Sciences (Engineering), Lecturer
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Review
For citations:
Vasilyev A.A., Nesterov A.S. APPLYING TEXT QUESTIONS GENERATION ALGORITHMS FOR AUTOMATIC TEST GENERATION. Proceedings in Cybernetics. 2023;22(3):17-22. (In Russ.) https://doi.org/10.35266/1999-7604-2023-3-17-22
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