Personalized Adaptation of Learning Environments

Filatov, V.; Yerokhin, A.; Zolotukhin, O.; Kudryavtseva, M.

Публікація:
Personalized Adaptation of Learning Environments

dc.contributor.author	Filatov, V.
dc.contributor.author	Yerokhin, A.
dc.contributor.author	Zolotukhin, O.
dc.contributor.author	Kudryavtseva, M.
dc.date.accessioned	2023-04-17T17:26:45Z
dc.date.available	2023-04-17T17:26:45Z
dc.date.issued	2019
dc.description.abstract	This work is devoted to the development of personalized training systems. A major problem in learning environmens is applying the same approach to all students: teaching materials, time for their mastering, and a training program that is designed in the same way for everyone. Although, each student is individual has his own skills, ability to assimilate the material, his preferences and other. Recently, recommendation systems, of which the system of personalized learning is a part, have become widespread in the learning environment. On the one hand, this shift is due to mathematical approaches, such as machine learning and data mining, that are used in such systems while, on the other hand, the requirements of technological standards "validated" by the World Wide Web Consortium (W3C). According to this symbiosis of mathematical methods and advanced technologies, it is possible to implement a system that has several advantages: identifying current skill levels, building individual learning trajectories, tracking progress, and recommending relevant learning material. The conducted research demonstrates how to make learning environment more adaptive to the users according to their knowledge base, behavior, preferences, and abilities. In this research, a model of a learning ecosystem based on the knowledge and skills annotations is presented. This model is a general model of the all life learning. Second, this thesis focuses on the creation of tools for personalized assessment, recommendation, and advising.
dc.identifier.citation	Personalized Adaptation of Learning Environments / V. Filatov, A. Yerokhin, O. Zolotukhin, M. Kudryavtseva // 2019 IEEE 8th International Conference on Advanced Optoelectronics and Lasers (CAOL*2019) : сonference proceedings, Sozopol, Bulgaria, 6-8 September 2019. – P. 584–587.
dc.identifier.uri	https://openarchive.nure.ua/handle/document/22649
dc.language.iso	en
dc.subject	personalized learning
dc.subject	adaptive learning
dc.subject	learning environment
dc.subject	Semantic Web
dc.subject	recommendation system
dc.subject	academic advising
dc.title	Personalized Adaptation of Learning Environments
dc.type	Article
dspace.entity.type	Publication