THE CLUSTER ANALYSIS OF BEHAVIORAL FACTORS IN THE FORMATION OF STUDENTS' DIGITAL IDENTITY
Keywords:
digital identity;, survey data, hierarchical clustering, digital activity, academic activity, research activity, social activityIssue
Section
Abstract
The digital identity of students is becoming increasingly relevant in the modern world of education. With the development of technology and the transition to online learning, ensuring the security of student data and their authentication in a digital environment are becoming important tasks for educational institutions. This article is devoted to identifying the features of the digital identity of students of regional universities in East Kazakhstan. The purpose of the study is to use cluster analysis to analyze survey data in order to identify the features of students' digital identity. The general methodology of the study is presented, according to which preliminary data processing was carried out in order to prepare them for subsequent analysis. The paper uses hierarchical clustering using Ward's algorithm to analyze behavioral factors affecting the formation of students' digital identity. Before conducting cluster analysis using the Elbow method, the optimal number of clusters was determined, which made it possible to effectively divide and classify the studied data. The study used survey data collected among 324 students from three regional universities of the Republic of Kazakhstan. The survey was conducted in an online format using a Google Form. The content of the questions includes digital activity and interaction of students in the online space, as well as questions about their academic, research and social activities. The Cronbach's α coefficient was used to assess the reliability and reliability of the data. As a result of the study, groups of students with different levels of digital identity ("Intensive digital activity", "Hybrid form of digital activity", "Limited digital activity"). Based on the conducted research, it is proposed to develop a digital profile of the student, taking into account his level of digital identity, as well as planning personalized learning trajectories in order to optimize their academic and social development.
Published
How to Cite
Most read articles by the same author(s)
- Saule Smailova , Maria Voronenko , Volodymyr Lytvynenko , Сауле Кумаргажанова, Elena Blinaeva , Aizhan Tlebaldinova , APPLICATION OF BAYESIAN NETWORKS TO DETERMINE THE IMPACT OF HIGHER EDUCATION ON ECONOMIC DEVELOPMENT , Вестник ВКТУ: No. 3 (2024): "Вестник ВКТУ им.Д.Серикбаева"
- Жанат Сейтахметова, Saule Kumargazhanova, Yuri Weiss , Leonid Bobrov, DESIGNING A TRANSITION SYSTEM TO PERSONALIZED LEARINING: ANALYSIS OF THE RESULTS OF THE STAKEHOLDER SURVEY , Вестник ВКТУ: No. 1 (2023): "Vestnik D. Serikbayev of EKTU"
- Yevgeniy Fedkin , Saule Smailova , Сауле Кумаргажанова, Zhadyra Konurbayeva , Faizullinovna, The DIGITAL PLATFORM ARCHITECTURE FOR ENGINEERING EDUCATION MODEL , Вестник ВКТУ: No. 4 (2023): "Vestnik D. Serikbayev of EKTU"
- Mamykova Zh. D., Kumargazhanova S.K., Aitenova M.R., Kopnova O.L, Karyukin V.I., Barlybay K.M., Bolatkhan M., Bolatkhan O., Development of a scenario analysis of the application of the Information and Analysis System , Вестник ВКТУ: No. 4 (2022): "Vestnik D. Serikbayev of EKTU"
- yelena-01 blinayeva-01, Saule Smailova, Askar Aulbekov, Yana Yaanus, APPLICATION OF NEURAL NETWORKS FOR ATMOSPHERIC POLLUTION FORECASTING , Вестник ВКТУ: Vol. 1 No. 3 (2023): «НАУКА, ОБРАЗОВАНИЕ И ПРАКТИКИ РЕАЛИЗАЦИИ BIM И ГИС ТЕХНОЛОГИИ»
- Laura Suleimenova, Сауле Кумаргажанова, Aizhan Tlebaldinova , Saule Smailova , Alia Urkumbaeva , The APPLICATION OF ONTOLOGICAL MODELING IN THE PROBLEMS OF KNOWLEDGE MANAGEMENT IN A MODERN UNIVERSITY , Вестник ВКТУ: Vol. 1 No. 4 (2023): CITech
- Akbota Kumarkanova, Akerke Tankibayeva, Aizhan Tlebaldinova , Markhaba Karmenova, Сауле Кумаргажанова, COMPREHENSIVE APPROACH TO MRI IMAGE PREPROCESSING BASED ON FILTERING AND QUALITY ASSESSMENT , Вестник ВКТУ: No. 2 (2025): "Вестник ВКТУ им.Д.Серикбаева"