turanВестник университета «Туран»Bulletin of "Turan" University1562-29592959-1236Университет «Туран»10.46914/1562-2959-2023-1-3-384-398turan-3568Research ArticleОБРАЗОВАНИЕ И ОБУЧЕНИЕ: МЕТОДОЛОГИЯ, ТЕОРИЯ, ТЕХНОЛОГИЯEDUCATION AND TRAINING: METHODOLOGY, THEORY, TECHNOLOGYРаскрытие восприятия студентов в онлайн-образовании через анализ классификатора деревьевUnveiling perceptions of students in online education through Tree Classifier analysishttps://orcid.org/0000-0002-2193-9418ДжумасейтоваА. К.JumasseitovaA. K.

PhD, профессор.

Алматы

PhD, professor.

Almaty

a.dzhumaseitova@kbtu.kzhttps://orcid.org/0009-0000-8638-476XКайдароваН. А.KaidarovaN. A.

Докторант.

Алматы

PhD student.

Almaty

n.kaidarova@kbtu.kzКазахстанско-Британский технический университетКазахстанKazakh British Technical UniversityKazakhstan20230510202303384398Copyright © Джумасейтова А.К., Кайдарова Н.А., 20232023Джумасейтова А.К., Кайдарова Н.А.Jumasseitova A.K., Kaidarova N.A.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik.turan-edu.kz/jour/article/view/3568

В данной статье представлен анализ восприятия студентами онлайн-образования с использованием алгоритма Tree Classifier. Исследование включает опрос 460 студентов, которые принимали участие в онлайн-обучении во время пандемии Covid-19. С помощью 49 вопросов опрос направлен на понимание опыта студентов, столкновений, полученной поддержки и предпочтений в отношении онлайн-образования. Основная цель – выявить группу студентов, предпочитающих онлайн-обучение лицом к лицу. В рамках данного исследования с использованием алгоритма Tree Classifier на Python извлекаются ценные идеи восприятия студентами онлайн-образования. Сфокусировавшись на студентах г. Алматы (Казахстан), авторы имели возможность провести сравнение с подобными международными исследованиями, чтобы создать основу для дальнейших исследований и рекомендаций по улучшению онлайн-, очного или смешанного форматов обучения. Полученные результаты проливают свет на факторы, влияющие на удовлетворенность студентов, их вовлеченность и предпочтения в онлайн-обучении. Основываясь на полученных выводах, авторы предлагают практические рекомендации для улучшения опыта онлайн-обучения и решения выявленных проблем. Предлагается всестороннее понимание восприятия и предпочтений студентов в онлайн-образовании на основе опыта студентов г. Алматы. Полученные результаты, а также сравнительный анализ опыта других стран, послужат, на наш взгляд, ценной информацией для будущих исследований, будут способствовать улучшению качества онлайн-обучения, а также будут ценным ресурсом для педагогов, политиков и исследователей.

This article presents an analysis of students’ perceptions in online education using Tree Classifier analysis. The study involves a survey of 460 students who participated in online learning during the Covid-19 pandemic. With 49 questions, the survey aims to understand students’ experiences, challenges, support received, and preferences regarding online education. The main objective is to identify a cohort of students who prefer online study over face-to-face learning. Implementing the Random Forest algorithm in Python, this study extracts valuable insights into students’ perceptions of online education. Focusing on students in Almaty city, Kazakhstan, the research allows for potential comparisons with similar international studies to inform future research and policy recommendations for improving online, face-to-face, or blended learning formats. The findings shed light on factors influencing student satisfaction, engagement, and preference for online learning. Drawing on these insights, the study provides practical recommendations to enhance the online learning experience and address the identified challenges. This research contributes to the existing knowledge on online education, serving as a valuable resource for educators, policymakers, and researchers. It offers a comprehensive understanding of students’ perceptions and preferences in online education, based on the experiences of students in Almaty city. The results, coupled with comparative analyses from other countries, inform future research and facilitate improvements in online education delivery.

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The authors declare that there are no conflicts of interest present.