AN INTELLIGENT FRAMEWORK FOR STUDENT ENGAGEMENT IN BLENDED LEARNING USING DEEP LEARNING MODELS

Blended learning, which integrates traditional face-to-face instruction with digital technologies, has emerged as a transformative model in modern education. The whole evolution, implementation, and future prospects, highlights the role as a basis of digital pedagogy. By combining online and offline teaching strategies, blended learning fosters personalized learning experiences that enhances student engagement and diverse learning styles. Drawing on empirical research, case studies, and current educational frameworks, this paper evaluates the effectiveness of blended learning across various educational levels and disciplines. Despite its advantages, blended learning presents challenges, including the digital divide, difficulty of maintaining instructional quality across platforms. Successful adoption requires strategic planning, strong institutional support, and robust technological infrastructure. By addressing both pedagogical and technological dimensions, this study demonstrates that blended learning is more than a temporary response to digital trends towards sustainable educational model. This paper introduces an intelligent blended learning framework that leverages deep learning techniques to enhance student engagement, academic performance, and overall learning effectiveness. Deep learning models are applied to examine learner behavior, interaction trends, and performance data, allowing the system to deliver personalized learning materials, adaptive evaluations, and prompt feedback. The integration of data-driven intelligence within the blended learning environment supports varied learning preferences and encourages active involvement in both online and in-person instructional settings. Deep learning, a key branch of Artificial Intelligence (AI), is revolutionizing blended learning by making it more adaptive, personalized, and engaging. By analyzing extensive student data—such as online activity, assessment performance, and learning patterns—deep learning models provide actionable insights that help optimize learning experiences and improve educational outcomes. The study underscores the effectiveness of combining deep learning with blended learning to create adaptive, intelligent, and learner-centered educational systems.