Toward Effective Educational Supervision in Yemen: A Hybrid Fuzzy Delphi and Clustering Analysis of Technical Barriers

<ns3:p>Objectives Comprehensive educational supervision is essential for ensuring quality teaching, fostering professional development, and supporting institutional capacity building. However, its implementation encounters numerous structural, technical, and human resource challenges. This study aimed to identify, validate, rank, and cluster the technical barriers affecting comprehensive educational supervision in Amanat Al Asimah, Yemen. This aligns with national reform goals by offering strategic insights to improve supervisory systems, thereby enhancing teaching quality, institutional performance, and educational resilience in fragile contexts Methods This study employed a three-phase mixed-methods approach. Initially, a literature review identified 11 key barriers to effective supervision. These were validated using the Fuzzy Delphi Method (FDM), involving 16 experienced educational supervisors to assess the consensus and suitability of the items. Subsequently, a quantitative survey targeting 370 teachers was conducted to evaluate their perceived severity. Fuzzy set theory was used to aggregate and defuzzify the responses, generating crisp scores for prioritization. Finally, K-means clustering was applied to segment the barriers based on their impacts. Results FDM analysis confirmed the validity of all 11 identified barriers, with a domain-level threshold of 0.093 and an average expert consensus of 90%, indicating strong agreement. The fuzzy set-based evaluation highlighted three top-priority challenges: weak supervisory competencies, limited ability to develop effective supervisory plans, and poor supervisor-teacher relationships. K-means clustering grouped the barriers into three segments: one high-priority barrier, seven moderate-priority concerns, and three low-priority issues. Notably, weak supervisory competencies emerged as the most critical barrier, isolated in a high-priority cluster. Conclusion These findings provide evidence-based guidance for policy and strategic interventions aimed at enhancing the effectiveness of supervision systems in fragile educational settings. The study concludes with recommendations for strengthening supervisory competencies, improving resource allocation, and fostering trust-based supervisor-teacher relationships, thereby contributing to the quality of education and institutional resilience in Yemen.</ns3:p>

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Publication Details

Journal
F1000Research
Published
2025-09-22
DOI
https://doi.org/10.12688/f1000research.167498.1
Primary Topic
Educational and Psychological Assessments
Type
article
Field-Weighted Citation Impact
0.00

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article

Toward Effective Educational Supervision in Yemen: A Hybrid Fuzzy Delphi and Clustering Analysis of Technical Barriers

Abed Saif Alghawli, Abdel-Aziz Y. El-Sayed, Abdul Hakim Abdullah, Adel A. Nasser et al.
F1000Research
Educational and Psychological Assessments
article

Toward Effective Educational Supervision in Yemen: A Hybrid Fuzzy Delphi and Clustering Analysis of Technical Barriers

Abed Saif Alghawli, Abdel-Aziz Y. El-Sayed, Abdul Hakim Abdullah, Adel A. Nasser, Riyadh Ghaleb A. Alshameri
article en

Abstract

<ns3:p>Objectives Comprehensive educational supervision is essential for ensuring quality teaching, fostering professional development, and supporting institutional capacity building. However, its implementation encounters numerous structural, technical, and human resource challenges. This study aimed to identify, validate, rank, and cluster the technical barriers affecting comprehensive educational supervision in Amanat Al Asimah, Yemen. This aligns with national reform goals by offering strategic insights to improve supervisory systems, thereby enhancing teaching quality, institutional performance, and educational resilience in fragile contexts Methods This study employed a three-phase mixed-methods approach. Initially, a literature review identified 11 key barriers to effective supervision. These were validated using the Fuzzy Delphi Method (FDM), involving 16 experienced educational supervisors to assess the consensus and suitability of the items. Subsequently, a quantitative survey targeting 370 teachers was conducted to evaluate their perceived severity. Fuzzy set theory was used to aggregate and defuzzify the responses, generating crisp scores for prioritization. Finally, K-means clustering was applied to segment the barriers based on their impacts. Results FDM analysis confirmed the validity of all 11 identified barriers, with a domain-level threshold of 0.093 and an average expert consensus of 90%, indicating strong agreement. The fuzzy set-based evaluation highlighted three top-priority challenges: weak supervisory competencies, limited ability to develop effective supervisory plans, and poor supervisor-teacher relationships. K-means clustering grouped the barriers into three segments: one high-priority barrier, seven moderate-priority concerns, and three low-priority issues. Notably, weak supervisory competencies emerged as the most critical barrier, isolated in a high-priority cluster. Conclusion These findings provide evidence-based guidance for policy and strategic interventions aimed at enhancing the effectiveness of supervision systems in fragile educational settings. The study concludes with recommendations for strengthening supervisory competencies, improving resource allocation, and fostering trust-based supervisor-teacher relationships, thereby contributing to the quality of education and institutional resilience in Yemen.</ns3:p>

F1000ResearchVol. 14
Prince Sattam Bin Abdulaziz University (SA), Sana'a University (YE), Yahoo (Spain) (ES), University of Modern Sciences (YE), Sultan Zainal Abidin University (MY)
Prince Sattam bin Abdulaziz University, Deanship of Scientific Research, Prince Sattam bin Abdulaziz University
Openalex Percentile: Top 72%
Educational and Psychological Assessments
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