Learning Analytics and Intelligent Decision Support in Smart Educational Platforms
Keywords:
Learning analytics, smart education, intelligent decision support, educational data analysis, digital learning platformsAbstract
The rapid expansion of digital technologies in education has generated large volumes of learning data within smart educational platforms, creating new opportunities for data-driven decision making in teaching and learning processes. This study focuses on learning analytics and proposes a framework for intelligent decision support in smart educational platforms. The framework aims to identify behavioral patterns of learners, analyze learning progress, and detect key factors influencing academic performance. Data generated from students’ interactions with digital learning environments are analyzed to extract meaningful indicators that support instructors, educational managers, and curriculum designers in improving learning outcomes. The findings suggest that data-driven analytics can facilitate early identification of students at risk of academic failure, enhance the design and delivery of educational content, and improve the efficiency of teaching and learning processes. Overall, integrating learning analytics with intelligent decision support systems can significantly contribute to the development of smart education and more effective management of digital learning environments.
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