Expert System for Identification of Digital Transformation Maturity Level in Secondary Schools Using Forward Chaining
Keywords:
Expert System, Digital Transformation Maturity, Secondary Schools, Forward Chaining, Decision Support SystemAbstract
The rapid growth of digital transformation in education has significantly influenced secondary schools through the adoption of e-learning platforms, digital administration systems, and smart classroom technologies, making digital maturity an essential aspect of modern educational development. However, many schools still lack a structured and standardized approach to measure their level of digital transformation maturity, resulting in assessments that are often subjective and inconsistent. This study aims to develop an expert system for identifying the digital transformation maturity level of secondary schools. The system is built using a rule-based approach supported by a knowledge base derived from expert interviews and relevant literature, including established digital maturity frameworks. Data collection is conducted through structured questionnaires that capture key indicators such as ICT infrastructure, teacher digital literacy, digital learning adoption, and institutional policy support. The inference mechanism employed in the system is Forward Chaining, which processes input facts and applies IF–THEN rules to generate logical conclusions. The system is capable of classifying schools into predefined maturity levels, ranging from initial to advanced stages of digital transformation. The results indicate that the expert system can effectively evaluate and categorize digital maturity levels in a systematic and consistent manner. In conclusion, the proposed system provides a reliable decision-support tool that assists school administrators and policymakers in assessing and improving digital transformation readiness in secondary education institutions.
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