An Investigation of AI-Based Personalized Learning Systems in Katsina State Polytechnic, Katsina State
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- NGN 5000
Background of the study
Personalized learning, where education is tailored to the unique needs, strengths, and learning styles of individual students, has gained significant attention in recent years. AI technologies have the potential to revolutionize personalized learning by creating adaptive systems that can adjust educational content, delivery methods, and pacing according to students' progress. In Katsina State Polytechnic, Katsina State, there is an increasing need to improve student learning outcomes by providing personalized education that addresses the diverse learning needs of students. AI-based personalized learning systems can offer real-time feedback, recommend resources based on individual performance, and ensure that no student is left behind. This study investigates the design, implementation, and effectiveness of AI-based personalized learning systems in improving educational outcomes at Katsina State Polytechnic.
Statement of the problem
Despite the recognition of the benefits of personalized learning, many institutions, including Katsina State Polytechnic, face challenges in providing tailored learning experiences due to limited resources, large class sizes, and conventional teaching methods. The use of AI to create personalized learning pathways has not been sufficiently explored in this context. As a result, students often receive the same instructional content, regardless of their individual learning needs, leading to disengagement and underperformance. There is a need to investigate how AI can be applied to personalize learning at Katsina State Polytechnic, ensuring that students receive the most relevant and effective educational experience.
Objectives of the study
1. To design and implement an AI-based personalized learning system for Katsina State Polytechnic.
2. To evaluate the impact of the AI system on student engagement and academic performance.
3. To explore the feasibility of scaling AI-based personalized learning systems to other polytechnics in Katsina State.
Research questions
1. How does the AI-based personalized learning system improve student engagement and academic performance at Katsina State Polytechnic?
2. What features of the AI system contribute most to personalizing learning experiences for students?
3. What challenges exist in the implementation and adoption of AI-based personalized learning systems in Katsina State Polytechnic?
Research hypotheses
1. The AI-based personalized learning system will significantly increase student engagement and academic performance at Katsina State Polytechnic.
2. AI-driven personalized recommendations and content adjustments will enhance the overall learning experience for students.
3. There will be challenges in the widespread adoption and implementation of AI-based learning systems at Katsina State Polytechnic due to resource limitations and staff preparedness.
Significance of the study
This study will contribute to the growing body of research on personalized learning and AI in education, offering valuable insights into the practical application of AI technologies in enhancing student outcomes. It will serve as a reference for polytechnic institutions in Katsina State and beyond, encouraging the adoption of personalized learning models powered by AI.
Scope and limitations of the study
The study will focus on the development, implementation, and evaluation of AI-based personalized learning systems within Katsina State Polytechnic. Limitations include challenges in data collection, such as accessing student performance records, and potential resistance to adopting AI technologies among faculty and administration.
Definitions of terms
• Personalized Learning: An educational approach that tailors content, pacing, and learning activities to meet the needs of individual students.
• AI-Based System: A technology that utilizes artificial intelligence, such as machine learning or natural language processing, to adapt and personalize learning experiences.
• Student Engagement: The level of active participation, interest, and emotional involvement that students demonstrate in their learning activities.
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