Exploring the Use of AI for Personalized Learning in Online Education: A Case Study of Federal University, Wukari (Wukari LGA, Taraba State)
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- NGN 5000
Background of the Study
Personalized learning is an educational approach where content, resources, and learning activities are tailored to the needs, interests, and learning preferences of individual students. With the increasing prevalence of online education, there is a growing need to integrate artificial intelligence (AI) to create personalized learning experiences that adapt to students' progress and performance. Federal University, Wukari, located in Wukari LGA, Taraba State, offers a range of online courses that could benefit from AI-driven personalized learning systems.
This study will explore the role of AI in enhancing personalized learning in online education, focusing on how AI can track student progress, recommend customized learning paths, and optimize teaching strategies based on individual performance and preferences.
Statement of the Problem
The traditional one-size-fits-all approach to online education does not cater to the diverse learning needs of students. Many students at Federal University, Wukari, may not be receiving the tailored support they need to excel in their studies. AI has the potential to address this issue by providing personalized learning experiences that can enhance student engagement, improve learning outcomes, and reduce dropout rates.
Objectives of the Study
1. To investigate how AI can be used to create personalized learning paths for online students at Federal University, Wukari.
2. To assess the effectiveness of AI-based personalized learning systems in improving student engagement and learning outcomes.
3. To evaluate the challenges and opportunities in implementing AI-powered personalized learning in online education.
Research Questions
1. How can AI be utilized to personalize the learning experience for students in online education at Federal University, Wukari?
2. What impact does AI-driven personalized learning have on student engagement, performance, and retention rates?
3. What are the main challenges in implementing AI-powered personalized learning systems in the context of online education?
Research Hypotheses
1. AI-powered personalized learning systems will significantly improve student engagement and academic performance in online education at Federal University, Wukari.
2. Students will show a higher level of satisfaction and retention when using AI-driven personalized learning systems compared to traditional online education methods.
3. The implementation of AI-powered personalized learning will face challenges such as data privacy concerns, the need for infrastructure, and faculty readiness.
Significance of the Study
This study will provide insights into how AI can be used to enhance personalized learning in online education, offering practical recommendations for Federal University, Wukari, and other institutions looking to adopt AI in their online courses. The findings could contribute to improving student success and fostering more engaging online learning environments.
Scope and Limitations of the Study
The study will focus on AI-powered personalized learning in the context of online education at Federal University, Wukari. It will not cover other forms of learning or broader AI applications in education. The study will also be limited by the availability of data and resources for implementing the AI system.
Definitions of Terms
• Personalized Learning: An educational approach that tailors content and learning activities to the individual needs, preferences, and learning styles of students.
• Artificial Intelligence (AI): The use of algorithms and machine learning models to simulate human-like cognitive functions such as learning, problem-solving, and decision-making.
• Online Education: Education that is delivered primarily over the internet, often using platforms that enable remote learning.
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