Peer Reviewed

Determinants in modelling early school dropout

Type of paper: Research Article

Authors

Bianca-Raluca Cibu

Corresponding Author

Affiliation: Bucharest University of Economic Studies, Bucharest, Romania

Email: cibubianca18@stud.ase.ro

https://orcid.org/0009-0003-8597-7514

Camelia Delcea

Affiliation: Bucharest University of Economic Studies, Bucharest, Romania

Email: camelia.delcea@csie.ase.ro

https://orcid.org/0000-0003-3589-1969

Adrian Domenteanu

Affiliation: Bucharest University of Economic Studies, Bucharest, Romania

Email: domenteanuadrian18@stud.ase.ro

https://orcid.org/0009-0001-9615-1174

Published:December 15, 2024

How to Cite

Cibu, B.-R., Delcea, C., & Domenteanu, A. (2024). Determinants in modelling early school dropout. CACTUS Tourism Journal, 30 (1). doi.org/10.24818/CTS/6/2024/2.02

Based on the official APA guide. Review the full set of examples.

© 2024 The Author(s);

Licensed under CC BY-NC 4.0

Abstract

Recognizing the importance of continuity in education, it was deemed necessary to carry out a study whose main objective is to identify the factors that lead to the intention to drop out in order to formulate effective strategies to combat this phenomenon. Early school dropout has negative consequences both for individual development and for social and economic progress. Therefore, this paper aims to contribute to the understanding and prevention of this phenomenon through a rigorous analysis of its determinants. In this context, eight relevant dependent variables have been identified in the literature that are believed to play a significant role in the intention to drop out of school. These variables include factors such as school absenteeism, alcohol or substance abuse, attitude, awareness, family, family supervision, school environment and school rules. The analysis used in the study examines these significant variables through structural equation modeling (SEM). Smart PLS software was used to conduct this analysis, which allows the use of Partial Least Squares SEM (PLS-SEM) and Bootstrapping modeling techniques. The data used for this research was collected using a well-structured questionnaire consisting of 28 questions aimed at capturing students' perceptions and experiences of school and the factors that might contribute to their intention to drop out of school. A total of 669 respondents completed the questionnaire, providing a solid database for analysis.

Keywords

PLS-SEM, Bootstrapping, Romania, education, EU periphery

JEL Classification

H75, I21, I25, P36

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