Issue |
E3S Web of Conf.
Volume 508, 2024
International Conference on Green Energy: Intelligent Transport Systems - Clean Energy Transitions (GreenEnergy 2023)
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Article Number | 03013 | |
Number of page(s) | 12 | |
Section | IoT, AI and Data Analytics | |
DOI | https://doi.org/10.1051/e3sconf/202450803013 | |
Published online | 05 April 2024 |
Modelling algorithms for learner interaction with training courses
Fergana branch of Tashkent University of Information Technologies, 150118 Fergana, Uzbekistan
* Corresponding author: sanya_89_29@mail.ru
This paper considers learning as a process of mastering a knowledge domain, investigating the interaction of learners with courses of study and the influence of learner actions on the state of mastery of the knowledge space in order to define a learning control function and to model algorithms for constructing the knowledge space. Key aspects of the interaction process, variables that can be changed to customise the learning model, are given. A threshold to mastery of a course element is formulated and a scale of mastery level for a particular knowledge element is described. As a result, algorithms for forming, expanding and segmenting the knowledge space were created. The research presented the concept of learning as a guided wave process of knowledge mastery, where the learner's actions correspond to the structure of the knowledge space and are determined by its properties.
Key words: Modelling / training / interaction / algorithm / learning / mastering / knowledge / course / wave process / knowledge space
© The Authors, published by EDP Sciences, 2024
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