On the Development of an Adaptive Educational Platform Using Machine Learning Technologies
DOI:
https://doi.org/10.52575/2687-0932-2022-49-4-810-819Keywords:
artificial neural network, machine learning, adaptive educational platform, educational content, recurrent neural network, natural language processingAbstract
The article discusses the creation of an adaptive automated platform for teaching a foreign language, using the example of the English language. The adaptability of the system lies in the formation of educational content in the form (graphics, sound, text) that is most convenient for the student. To implement the mechanism for determining the most convenient form of educational content, several architectures of artificial neural networks are used, which are trained on prepared data. The data for training artificial neural networks includes a text – an essay written by a student and a student category identified as a result of passing a specialized test. Four categories of students are considered: audial, visual, kinesthetic, digital. Using the developed and trained artificial neural network, a prototype of a web-based software platform was created that "offers" the student to write a short essay in a foreign language, after which this text is processed by a recurrent artificial neural network, which, in turn, refers the student to one from four classes. Further, depending on a certain category of the student, educational content is formed in a form convenient for him. At the same time, testing of trained neural networks shows that the volume of the training sample is not sufficient, so in the future it is planned to form a more saturated training sample to implement better training of the artificial neural network.
Acknowledgements: the article was prepared with the financial support of the Ministry of Science and Higher Education of Russia, state assignment No. 0657-2020-0009.
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