Evaluation of AI-Based Adaptive Learning Platforms for Personalized University Education: A Case Study of Benue State University, Makurdi (Makurdi LGA, Benue State)
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Background of the Study
Personalized learning, which tailors the educational experience to the needs, preferences, and abilities of individual students, has gained considerable attention in higher education (Johnson & Brown, 2023). Traditional university education often follows a one-size-fits-all approach, which can lead to varying levels of student engagement and academic success (Lee & Zhang, 2024). Adaptive learning platforms powered by artificial intelligence (AI) offer a promising solution to address these challenges by providing personalized educational experiences based on real-time data and continuous assessment of student progress (Tian & Liu, 2025).
Benue State University in Makurdi, Benue State, offers a suitable case study to explore the effectiveness of AI-based adaptive learning platforms in higher education. These platforms can track students' progress, analyze learning behaviors, and adjust content delivery in real-time to optimize the learning experience (Wang et al., 2023). By integrating AI technologies, Benue State University can enhance student learning outcomes, improve engagement, and support individualized academic pathways for its diverse student population.
Statement of the Problem
Benue State University faces challenges in delivering personalized learning experiences that meet the diverse needs of its student body. Traditional teaching methods often fail to accommodate the varying learning paces and styles of students, leading to disengagement and suboptimal academic performance (Roberts & Thompson, 2023). This study seeks to evaluate the effectiveness of AI-based adaptive learning platforms in personalizing the educational experience for students at Benue State University.
Objectives of the Study
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To assess the effectiveness of AI-based adaptive learning platforms in personalizing university education at Benue State University.
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To evaluate the impact of adaptive learning on student engagement, academic performance, and retention.
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To explore the potential benefits and challenges of implementing AI-based adaptive learning platforms at Benue State University.
Research Questions
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How effective are AI-based adaptive learning platforms in personalizing university education at Benue State University?
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What is the impact of adaptive learning platforms on student engagement and academic performance at Benue State University?
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What are the challenges and benefits of implementing AI-based adaptive learning platforms at Benue State University?
Research Hypotheses
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AI-based adaptive learning platforms will improve student engagement and academic performance at Benue State University.
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The use of adaptive learning platforms will lead to higher retention rates and more personalized learning experiences for students.
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Students using AI-based adaptive learning platforms will outperform those using traditional teaching methods in terms of academic achievement.
Significance of the Study
This study will provide valuable insights into the application of AI-based adaptive learning platforms in higher education, offering potential solutions for improving student engagement, performance, and retention. The findings will inform Benue State University’s approach to adopting and integrating AI-driven technologies into its educational framework.
Scope and Limitations of the Study
The study will focus on Benue State University, located in Makurdi LGA, Benue State, and will assess the implementation and effectiveness of AI-based adaptive learning platforms for personalized education. Limitations include the availability of data on student performance and engagement, as well as the initial investment and technical challenges in adopting AI technologies.
Definitions of Terms
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Adaptive Learning: A personalized learning approach that uses AI to adjust content delivery based on individual students’ progress, learning styles, and needs.
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AI-Based Learning Platforms: Software systems that leverage artificial intelligence to provide personalized educational content and assessments.
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Student Engagement: The level of active participation, motivation, and commitment that students exhibit toward their learning activities.
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