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Development and research of algorithms for the formation the individual educational trajectories of students in the digital educational platform

At present, the widespread use of modern information technologies in education, including open online courses, ensures the sustainable development of a single digital educational environment. However, one of the key problems of the mass approach to learning is the construction of individual educatio...

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Главные авторы: Lapina, M. A., Лапина, М. А.
格式: Статья
语言:English
出版: CEUR-WS 2019
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在线阅读:https://www.scopus.com/record/display.uri?eid=2-s2.0-85075279549&origin=resultslist&sort=plf-f&src=s&nlo=1&nlr=20&nls=afprfnm-t&affilName=north+caucasus+federal+university&sid=45b9380153f80a0b92c322c16c6d2a47&sot=afnl&sdt=sisr&sl=53&s=%28AF-ID%28%22North+Caucasus+Federal+University%22+60070541%29%29&ref=%28Development+and+research+of+algorithms+for+the+formation+the+individual+educational+trajectories+of+students+in+the+digital+educational+platform%29&relpos=0&citeCnt=0&searchTerm=
https://dspace.ncfu.ru/handle/20.500.12258/9040
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总结:At present, the widespread use of modern information technologies in education, including open online courses, ensures the sustainable development of a single digital educational environment. However, one of the key problems of the mass approach to learning is the construction of individual educational trajectories. Taking into account the individual characteristics of each student is an urgent necessity. Achieving this goal is quite feasible when teaching students on individual learning routes. In this paper we have investigated two approaches to solving this problem. The first approach is based on the use of a genetic algorithm that allows you to form the optimal learning route, designed to meet the personal educational needs and individual capabilities of each student of the online course. The second approach involves the mathematical apparatus of neural networks give recommendations on the further optimal formation of an individual educational trajectory. The paper presents the results of experimental studies and examples of individual trajectories formed on the basis of the proposed algorithms