EDUCATIONAL MANAGEMENT AND THE PREVENTION OF EARLY SCHOOL LEAVING: EVIDENCE FROM A MULTIPLE REGRESSION ANALYSIS IN ROMANIA
Authors
- Adrian NICOLAU — Athenaeum University, Bucharest, Romania
Abstract
The study investigates the role of educational management in preventing early school leaving, with a specific focus on the contribution of digitalization in secondary education. Using a unique dataset collected from more than 1,700 respondents (students, parents, and teachers), the research applies a multiple regression model to examine the relationship between school management practices, the level of digital infrastructure, and students’ intention to continue their studies. The findings indicate that managerial strategies centered on digital governance and individualized support significantly reduce the risk of dropout. Moreover, socio-economic constraints such as financial difficulties, lack of transport, and limited parental involvement are mitigated when schools provide structured remedial programs and transparent communication. The results highlight that educational leadership and investment in digital resources are decisive factors for strengthening students’ attachment to school. This study contributes to the international literature by offering empirical evidence from Romania and provides policy recommendations for improving school retention through management innovation and digital transformation.
Keywords: educational leadership, digital governance, early school leaving, student retention, multiple regression, Romania
Cite this article
APA: Adrian NICOLAU (2025). EDUCATIONAL MANAGEMENT AND THE PREVENTION OF EARLY SCHOOL LEAVING: EVIDENCE FROM A MULTIPLE REGRESSION ANALYSIS IN ROMANIA. Internal Auditing & Risk Management, Vol. 72, No. 72, pp. 75-92. https://doi.org/10.5281/zenodo.17228051
BibTeX:
@article{adriannicolau20256,
title = {EDUCATIONAL MANAGEMENT AND THE PREVENTION OF EARLY SCHOOL LEAVING: EVIDENCE FROM A MULTIPLE REGRESSION ANALYSIS IN ROMANIA},
author = {Adrian NICOLAU},
journal = {Internal Auditing & Risk Management},
year = {2025},
volume = {72},
pages = {75----92},
doi = {10.5281/zenodo.17228051}
}