| _version_ | 1866901343120130048 |
|---|---|
| author | Abduxamidova Muyassar |
| author_facet | Abduxamidova Muyassar |
| contents | <p>This paper investigates the integration of artificial intelligence (AI) into educational management, with a particular<br>focus on predictive mechanisms for Uzbekistan’s school system. Using a mixed-methods approach, the study<br>analyzes quantitative EMIS data alongside qualitative insights obtained from school leaders to identify current practices,<br>challenges, and institutional readiness for AI-based forecasting. The findings indicate that only 18 % of schools currently<br>use AI tools in managerial decision-making; however, more than 90 % of school principals acknowledge the necessity of<br>AI for planning student enrollment, staffing, and academic performance. The paper concludes that the development of<br>AI-supported forecasting within the national EMIS platform has the potential to transform decision-making processes from<br>reactive to proactive management. Policy recommendations are proposed to strengthen digital infrastructure, leadership<br>competencies, and data-driven governance.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18077577 |
| institution | Zenodo |
| language | |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Artificial Intelligence in Educational Management: Opportunities and Predictive Mechanisms in the Context of Uzbekistan Abduxamidova Muyassar <p>This paper investigates the integration of artificial intelligence (AI) into educational management, with a particular<br>focus on predictive mechanisms for Uzbekistan’s school system. Using a mixed-methods approach, the study<br>analyzes quantitative EMIS data alongside qualitative insights obtained from school leaders to identify current practices,<br>challenges, and institutional readiness for AI-based forecasting. The findings indicate that only 18 % of schools currently<br>use AI tools in managerial decision-making; however, more than 90 % of school principals acknowledge the necessity of<br>AI for planning student enrollment, staffing, and academic performance. The paper concludes that the development of<br>AI-supported forecasting within the national EMIS platform has the potential to transform decision-making processes from<br>reactive to proactive management. Policy recommendations are proposed to strengthen digital infrastructure, leadership<br>competencies, and data-driven governance.</p> |
| title | Artificial Intelligence in Educational Management: Opportunities and Predictive Mechanisms in the Context of Uzbekistan |
| url | https://doi.org/10.5281/zenodo.18077577 |