ORIGINAL RESEARCH article
Front. Educ.
Sec. Leadership in Education
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1643452
Drivers of Success in Somaliland's Preschools: A Predictive Machine Learning Model of Leadership Commitment and Institutional Capacity
Provisionally accepted
- 1Amoud University, Borama, Somalia
- 2Addis Ababa University College of Social Sciences Arts and Humanities, Addis Ababa, Ethiopia
- 3Haramaya University, Dire Dawa, Ethiopia
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This study develops a predictive machine learning model to identify the primary drivers of success in Somaliland's public preschools, conceptualized as institutional capacity. Early childhood education (ECE) is critical for development in post-conflict regions, yet there is a significant knowledge gap regarding the factors that foster institutional effectiveness in this context. Integrating Meyer and Allen's three-component model of commitment with the Resource-Based View of organizations, this research investigates how leadership commitment—specifically normative, affective, and continuance commitment—predicts the institutional capacity of preschools. A quantitative, cross-sectional survey design was employed, using a census sample of 129 educators and head teachers from all 33 public preschools across Somaliland. After comparing five regression techniques, a Robust Regression model was selected for its superior performance and resilience to outliers (RMSE = 2.16). The final model demonstrated significant predictive power (Pseudo R² = .432), revealing a distinct hierarchy of influence among the commitment dimensions. Normative commitment, or a leader's sense of duty, emerged as the most potent predictor of institutional capacity (β = 0.63, p < .001). Affective commitment, reflecting emotional attachment, was also a strong positive predictor (β = 0.27, p < .001). In contrast, continuance commitment, based on the perceived costs of leaving, had a statistically significant but practically negligible impact (β = 0.04, p = .001). These findings indicate that in Somaliland's fragile context, a leader's dedication is driven by professional obligation and purpose rather than transactional incentives. The study makes a key methodological contribution by applying predictive analytics to educational leadership research, offering a nuanced and data-driven framework. The results provide an evidence-based blueprint for policymakers to design targeted interventions—such as professionalizing leadership roles and fostering peer support networks—to build a resilient and effective ECE system in Somaliland and other fragile settings.
Keywords: Somaliland Early Childhood Education, Leadership commitment, Institutional capacity, Predictive Modeling, machine learning, Normative commitment, Robust Regression
Received: 04 Jul 2025; Accepted: 29 Sep 2025.
Copyright: © 2025 Ali, Zeleke, Adam and Negassa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Jibril Abdikadir Ali, jibrilabdikadir@amoud.edu.so
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