Drivers of success in Somaliland's preschools: a predictive machine learning model of leadership commitment and institutional capacity

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 R 2 = 0.432), 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 < 0.001). Affective commitment, reflecting emotional attachment, was also a strong positive predictor (β = 0.27, p < 0.001). In contrast, continuance commitment, based on the perceived costs of leaving, had a statistically significant but practically negligible impact (β = 0.04, p = 0.001). 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.

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Publication Details

Journal
Frontiers in Education
Published
2025-10-28
DOI
https://doi.org/10.3389/feduc.2025.1643452
Citations
1
Primary Topic
Early Childhood Education and Development
Type
article
Field-Weighted Citation Impact
8.93
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article

Drivers of success in Somaliland's preschools: a predictive machine learning model of leadership commitment and institutional capacity

Dawit Negassa Golga, Befekadu Zeleke, Bahir Adem Abdulahi, Jibril Abdikadir Ali
1 citations
Frontiers in Education
Early Childhood Education and Development
8.93
article

Drivers of success in Somaliland's preschools: a predictive machine learning model of leadership commitment and institutional capacity

Dawit Negassa Golga, Befekadu Zeleke, Bahir Adem Abdulahi, Jibril Abdikadir Ali
article en
1 citations

Abstract

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 R 2 = 0.432), 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 < 0.001). Affective commitment, reflecting emotional attachment, was also a strong positive predictor (β = 0.27, p < 0.001). In contrast, continuance commitment, based on the perceived costs of leaving, had a statistically significant but practically negligible impact (β = 0.04, p = 0.001). 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.

Frontiers in EducationVol. 10
Haramaya University (ET), Amoud University (SO), Addis Ababa Science and Technology University (ET), Addis Ababa University (ET)
Openalex Percentile: Top 2%
Early Childhood Education and Development
8.93
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