Background of the Study
Personalized education is increasingly seen as a critical component in enhancing student learning outcomes and success. Traditional one-size-fits-all approaches in university education often fail to address the individual needs, preferences, and learning styles of students (Akinyele & Oyebade, 2024). With the growing availability of student data, universities are increasingly adopting AI-based learning analytics to provide personalized learning experiences that adapt to the unique needs of each student (Oladapo & Adedeji, 2025). AI-based learning analytics tools use machine learning algorithms to analyze large datasets, such as academic performance, learning behavior, and engagement, to provide actionable insights that can guide personalized educational interventions (Fola & Aremu, 2024).
Benue State University, Makurdi, located in Makurdi LGA, Benue State, represents an ideal case for exploring the potential of AI-based learning analytics in personalized education. The university, like many in Nigeria, faces challenges in addressing the diverse academic needs of its student population. The integration of AI-based learning analytics could help to improve student engagement, academic performance, and overall educational outcomes by providing tailored recommendations and interventions (Akinola et al., 2023). This study aims to develop an AI-based learning analytics system that can analyze students' academic data and provide personalized recommendations for improving their learning experiences.
Statement of the Problem
Benue State University, Makurdi, struggles with providing personalized learning experiences to its diverse student body due to limited resources and traditional teaching methods. Students often face challenges in finding the right academic resources, staying engaged with the material, and managing their learning effectively. The lack of a data-driven approach to understanding student learning patterns and needs hampers the university's ability to offer personalized educational support. This study seeks to develop an AI-based learning analytics system that can enhance personalized education at the university.
Objectives of the Study
To design an AI-based learning analytics system that provides personalized recommendations for students at Benue State University.
To evaluate the effectiveness of the AI-based learning analytics system in improving student engagement and academic performance.
To assess students' perceptions of the usefulness and effectiveness of personalized learning analytics in enhancing their educational experience.
Research Questions
How effective is the AI-based learning analytics system in providing personalized learning recommendations for students at Benue State University?
What impact does the AI-based learning analytics system have on students' academic performance and engagement?
How do students perceive the use of AI-based learning analytics in improving their academic experiences?
Research Hypotheses
AI-based learning analytics will significantly improve student engagement and academic performance at Benue State University.
Students will have a positive perception of AI-based learning analytics and its impact on their academic experiences.
Personalized learning interventions based on AI analytics will lead to higher retention and success rates among students at Benue State University.
Significance of the Study
This study will provide valuable insights into the role of AI-based learning analytics in enhancing personalized education. The findings will contribute to the growing body of knowledge on the use of AI in education and offer practical recommendations for universities seeking to improve student outcomes through data-driven, personalized interventions.
Scope and Limitations of the Study
The study will focus on the development and evaluation of an AI-based learning analytics system at Benue State University, Makurdi, located in Makurdi LGA, Benue State. The study will be limited to undergraduate students, and data will be collected from academic performance records and student surveys.
Definitions of Terms
AI-Based Learning Analytics: The use of artificial intelligence to analyze student data and provide personalized recommendations for improving learning outcomes.
Personalized Education: Tailored educational experiences that adapt to the individual needs, preferences, and learning styles of students.
Learning Analytics: The process of collecting and analyzing data about student learning behaviors to enhance educational outcomes and experiences.
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