Exploring the impact of AI-driven real-time feedback systems on learner engagement and adaptive content delivery in education

Salameh, Waleed Abdullatif Khader (2025) Exploring the impact of AI-driven real-time feedback systems on learner engagement and adaptive content delivery in education. International Journal of Science and Research Archive, 14 (2). 098-104. ISSN 25828185

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Abstract

This study explores the impact of AI-driven real-time feedback systems and adaptive content delivery on learner engagement and educational outcomes. The integration of AI into educational settings offers personalized learning experiences by providing immediate, actionable feedback and dynamically adjusting content to suit individual learner needs. Through a synthesis of existing literature, the study examines the effectiveness of AI tools in enhancing learner motivation, improving retention, and supporting diverse learning paces. It also addresses key challenges, such as data privacy, algorithmic bias, and unequal access, which can limit the widespread adoption of AI technologies in education. The findings highlight the potential of AI to transform educational practices, but caution that ethical considerations and equitable access must be prioritized to fully realize its benefits. This research offers valuable insights for educators, policymakers, and developers seeking to optimize AI applications in education.

Item Type: Article
Uncontrolled Keywords: AI in education; Real-time feedback; Adaptive learning; Learner engagement; Personalized learning; Educational outcomes; Data privacy; Algorithmic bias; Technology adoption; Educational equity
Subjects: Q Science > Q Science (General)
Depositing User: Editor IJSRA
Date Deposited: 10 Jul 2025 16:24
Last Modified: 10 Jul 2025 16:24
URI: https://eprint.scholarsrepository.com/id/eprint/282

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