The role of AI in personalizing students' library study experience in Federal College of Education, Eha-Amufu Library, Enugu State
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Background of the study
Personalization in academic libraries is pivotal for enhancing user engagement and study effectiveness. At Federal College of Education, Eha-Amufu Library, Enugu State, AI is being harnessed to tailor the library experience to individual student needs. Using machine learning algorithms and user data analysis, AI systems can offer personalized book recommendations, study resources, and tailored learning pathways (Smith, 2023). This customized approach not only improves resource accessibility but also helps students navigate the vast array of academic materials efficiently. AI-driven personalization can adapt to changing user preferences and study habits, ensuring that students receive relevant and timely support for their academic pursuits. However, challenges such as data privacy, system integration, and the initial cost of implementing AI personalization persist (Adams, 2024). This study investigates how AI technologies are being deployed to enhance the personalized study experience in the library, aiming to identify best practices and potential improvements for greater student satisfaction and academic performance (Brown, 2025).
Statement of the problem
Despite advancements in AI-driven personalization, Federal College of Education, Eha-Amufu Library faces obstacles such as inadequate data integration and concerns over data privacy. These issues limit the system’s ability to accurately tailor resources to individual student needs, resulting in a less effective personalized study experience and potential underutilization of library services (Smith, 2023).
Objectives of the study
To evaluate the role of AI in personalizing the library study experience.
To identify challenges in implementing AI-based personalization.
To propose strategies to enhance personalized library services.
Research questions
How effective is AI in tailoring library services to individual student needs?
What challenges impede the personalization process?
How can AI-driven personalization be improved in academic libraries?
Significance of the study
This study offers insights into the potential of AI to transform the study experience in academic libraries, providing recommendations that will enhance user engagement and academic performance. The findings will benefit educators, librarians, and system developers by promoting tailored learning environments (Smith, 2023; Adams, 2024).
Scope and limitations of the study
The study is limited to AI-driven personalization efforts at Federal College of Education, Eha-Amufu Library, Enugu State, focusing on enhancing the student study experience.
Definitions of terms
Personalization: The customization of services based on individual user preferences.
Machine Learning: AI techniques that enable systems to learn from data.
User Engagement: The degree to which users interact with library resources
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