The problem of academic dishonesty in the global and Russian research discourse: The bibliometric analysis based on science databases
https://doi.org/10.33186/1027-3689-2023-5-15-38
Abstract
The findings of bibliometrical study are discussed to asses and compare the arrays of scholarly publications on the subject of academic dishonesty in Russia and in the world. The research method is based on interlinking the degree of scientific discourse maturity with terminological system sophistication. The dynamics of terminological system development in the area of academic dishonesty is examined with the search tools of Scopus as the largest reviewed scientific database, and Russian Science Citation Index. The title terms making the core of the terminological system for “academic dihonetsy” are identified, as well as the variants of their translation into the Russian language in the context of the problem. Based on the list of the title terms, the strategy for searching of scientific texts on the topic is built; the search results are visualized in the tables and graphs included. The author concludes that the array of the studies on the topic of academic dishonesty have been intensively developing in the academic community since 2000; she also argues that the stable long-term growth of publication is the trend in this area. However, based on RSCI, the scientific discourse of academic dishonesty in Russia has been developing just for the recent decade, with the trend of acceleration in the recent few years, though with insignificant accumulation of scientific texts array. The originality of the paper lies in the application of the approach of terminological system analysis with bibliometrical tools to estimate the maturity of research discourse in the individual subject area.
About the Author
T. V. EremenkoRussian Federation
Tatiana V. Eremenko – Dr. Sc. (Pedagogy), Professor.
Ryazan
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Review
For citations:
Eremenko T.V. The problem of academic dishonesty in the global and Russian research discourse: The bibliometric analysis based on science databases. Scientific and Technical Libraries. 2023;(5):15-38. (In Russ.) https://doi.org/10.33186/1027-3689-2023-5-15-38