Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций
Конференция: The 8th Computational Methods in Systems and Software 2024 (CoMeSySo2024); Cham; Cham
Год издания: 2025
Идентификатор DOI: 10.1007/978-3-031-96759-7_30
Ключевые слова: categorization, e-Learning, education science, Functional clustering, learning psychology, learning theory
Аннотация: E-learning has largely expanded the methodological and technical capabilities of the teacher. Electronic educational environments allow not only to design the teaching material, but also to organize the testing of mastering the discipline, including, in an automated way. Another advantage of such environments is the storage of dataПоказать полностьюon grades and other parameters of student learning. This allows to conduct diverse data analysis. In this paper, we analyze the data on student academic performance in an e-learning course in order to identify different learning styles. We applied k-means clustering method to identify students with similar learning strategies. Knowing the student's preferences allows to individualize the learning process and develop learning strategies for each individual student based on their specific characteristics. #COMESYSO1120.
Журнал: Artificial Intelligence and System Engineering
Выпуск журнала: 1490-2
Номера страниц: 406-416
Место издания: Cham