Open AccessDevelopment of an adaptive mass open online course in the framework of training in artificial neural network technologies
Author(s) -
Dmitry V. Bordachev
Publication year - 2021
Publication title -
vestnik rossijskogo universiteta družby narodov. seriâ informatizaciâ obrazovaniâ
Language(s) - English
Resource type - Journals
eISSN - 2312-864X
pISSN - 2312-8631
DOI - 10.22363/2312-8631-2021-18-1-100-106
Subject(s) - computer science , online course , process (computing) , artificial neural network , massive open online course , training (meteorology) , course (navigation) , moment (physics) , artificial intelligence , online learning , multimedia , mathematics education , world wide web , psychology , engineering , physics , classical mechanics , meteorology , aerospace engineering , operating system
Problem and goal. The development of mass open online courses contributes to the increasing attention of students to them. At the moment, there are many large services that provide online training, but there are no clearly defined universal requirements for such courses. Also, along with this problem, there is a fairly high level of rejection of the course at various stages due to the loss of motivation to continue training. Methodology. A variant of solving these problems by using adaptive learning technologies on the example of a course on learning artificial neural network technologies was considered. Results. In the process of reviewing the issue, the topics of the online course sections were determined. As a result, a work plan was drafted and the most relevant ways to solve the identified problems were formulated. Conclusion. The developed strategy can help with further elaboration and testing of the designed course and can be applied to any mass open online course.