Proceedings of the International Conference on Current Issues in Education (ICCIE 2023)

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Research Trends of Latent Class Analysis in Education: Bibliometric Analysis Based on Scopus Data

Authors
Sa’adatul Ulwiyah1, *, Jumriani Sultan1, Heri Retnawati1
1Universitas Negeri Yogyakarta, Yogyakarta, Indonesia
*Corresponding author. Email: saadatul.2022@student.uny.ac.id
Corresponding Author
Sa’adatul Ulwiyah
Available Online 20 May 2024.
DOI
10.2991/978-2-38476-245-3_16How to use a DOI?
Keywords
Bibliometric; Latent Class Analysis; Education; Grouping Students
Abstract

Latent Class Analysis (LCA) is one of the important statistical tools used in educational research. Latent Class Analysis is used to identify unobserved groups based on patterns in the data. This study aims to capture the landscape of relevant previous research related to Latent Class Analysis in education using bibliometric analysis. Data was taken from the Scopus database which was filtered into 130 publications. The number of articles related to Latent Class Analysis in Education has increased every year, especially in recent years, such as 2019, 2021, and potentially in 2023. The citation trend related to Latent Class Analysis in the scope of educational research occurred in 2019 with a total of 159 citations. Wang Y and Garcia-Fernandes are the authors with the highest number of publications, while Boscardin CK is the author with the highest number of citations. The article that had the most significant impact was the article by Bradshaw CP, Buckley JA, and Ialongo NS entitled “School-Based Service Utilization Among Urban Children with Early Onset Educational and Mental Health Problems: The Squeaky Wheel Phenomenon”. The article was published by School Psychology Quarterly and has received 108 citations. The United States, China and Spain are the most influential countries in this field. The keywords “mental health”, “structural equation modeling”, “surveys and questionnaires”, and “adults” are some of the new research areas related to latent class analysis in education.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Current Issues in Education (ICCIE 2023)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
20 May 2024
ISBN
10.2991/978-2-38476-245-3_16
ISSN
2352-5398
DOI
10.2991/978-2-38476-245-3_16How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Sa’adatul Ulwiyah
AU  - Jumriani Sultan
AU  - Heri Retnawati
PY  - 2024
DA  - 2024/05/20
TI  - Research Trends of Latent Class Analysis in Education: Bibliometric Analysis Based on Scopus Data
BT  - Proceedings of the International Conference on Current Issues in Education (ICCIE 2023)
PB  - Atlantis Press
SP  - 137
EP  - 148
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-38476-245-3_16
DO  - 10.2991/978-2-38476-245-3_16
ID  - Ulwiyah2024
ER  -