The effect of AI on personalized learning in Kwara State Polytechnic Library, Ilorin, Kwara State
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Background of the study
Artificial intelligence (AI) is revolutionizing the educational landscape by enabling personalized learning experiences that adapt to individual student needs. In Kwara State Polytechnic Library, Ilorin, AI tools such as adaptive learning systems, intelligent tutoring systems, and recommendation engines are being integrated into the library’s digital resources. These technologies analyze user behavior, learning patterns, and content engagement to offer customized resource suggestions and tailored study plans (Adeyemi, 2023). The integration of AI in personalized learning helps in identifying knowledge gaps and dynamically adjusting learning materials, thereby enhancing academic outcomes. In addition, AI-driven analytics provide insights into student performance, facilitating targeted interventions and enabling proactive support from librarians and educators. However, challenges such as data privacy concerns, algorithmic biases, and the need for continuous system updates persist, potentially limiting the full potential of personalized learning initiatives (Oluwatobi, 2024). This study investigates the impact of AI on personalized learning by examining how these systems influence resource accessibility, student engagement, and overall academic performance in the Kwara State Polytechnic Library. By evaluating user satisfaction and academic improvement, the research aims to provide comprehensive insights into the benefits and limitations of deploying AI in a library setting. Furthermore, it will explore strategies to overcome challenges related to technological integration and user adaptation, ensuring that AI-driven personalized learning becomes a sustainable tool for academic support (Ibrahim, 2024).
Statement of the problem
Despite the promising benefits of AI in personalized learning, Kwara State Polytechnic Library faces significant challenges that affect its effective implementation. Many students experience inconsistent performance due to occasional algorithmic bias and technical glitches that result in inappropriate resource recommendations. Data privacy issues and limited digital literacy among some users further impede the full utilization of AI tools. These challenges create a gap between the expected and actual outcomes of personalized learning, affecting overall academic performance. Therefore, this study seeks to identify these critical barriers and propose strategies to enhance the reliability and efficiency of AI systems in promoting individualized learning (Adeniyi, 2024).
Objectives of the study
To evaluate the impact of AI on personalized learning outcomes.
To identify the challenges associated with AI integration in library services.
To propose strategies for optimizing AI-driven personalized learning.
Research questions
How does AI influence personalized learning among students at the library?
What are the primary challenges in implementing AI for personalized learning?
What measures can improve the effectiveness of AI in enhancing individualized learning experiences?
Significance of the study
This study is significant as it provides valuable insights into how AI can transform personalized learning in a library setting. The findings will guide policymakers and library administrators in refining AI systems to better cater to individual learning needs, ultimately improving academic performance and resource utilization. The recommendations will serve as a framework for overcoming implementation challenges, ensuring sustainable integration of AI in educational environments (Olu, 2024).
Scope and limitations of the study
Limited to the topic only.
Definitions of terms
Personalized Learning: An educational approach that tailors learning experiences to individual needs.
AI-driven Systems: Technologies that use artificial intelligence to analyze data and adapt services.
Adaptive Learning: Systems that adjust learning content based on user performance.
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