Integrated Artificial Intelligence and Information Systems Framework for Enhancing Pedagogical Efficiency in Inclusive Digital Learning Environments toward Sustainable Education Development

This study proposes an integrated framework that combines artificial intelligence (AI) and information systems to enhance pedagogical efficiency in inclusive digital learning environments while supporting sustainable education development. The framework integrates adaptive learning technologies, intelligent tutoring systems, web-based information systems, real-time learning analytics, and data-driven decision-making within a system engineering perspective. A mixed-method research design was employed through experimental implementation, system-based analysis, classroom observations, structured questionnaires, and performance assessments involving higher education learning environments. The findings demonstrate that the integrated framework improves instructional effectiveness, learner engagement, accessibility, personalized learning, and administrative efficiency. These improvements are achieved through adaptive instructional pathways, automated feedback, continuous learning analytics, and intelligent monitoring that support diverse learner characteristics and optimize teaching and learning processes. The proposed framework contributes to educational technology by bridging information systems, AI, and pedagogical strategies into a unified model for inclusive digital education. Furthermore, the framework supports Sustainable Development Goal 4 (Quality Education) by promoting accessible, adaptive, learner-centered, and technology-driven educational environments that enhance both learning outcomes and long-term educational sustainability.

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