Modelling algorithms for learner interaction with training courses

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 c...

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Bibliographic Details
Main Authors: Gorovik Alexander, Lazareva Marina, Khasanova Makhinur, Yuldosheva Dilfuza
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:E3S Web of Conferences
Subjects:
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/38/e3sconf_greenenergy2024_03013.pdf
Description
Summary: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.
ISSN:2267-1242