Analysis of AI-Based Online Course Recommendation Models in Federal University, Dutsin-Ma, Katsina State
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- NGN 5000
Background of the Study
With the expansion of online learning platforms and digital resources, students now have access to a vast array of online courses that can complement their formal education. However, with such an overwhelming number of courses available, students may find it difficult to identify which ones align best with their academic goals, interests, and future career paths. AI-based online course recommendation models leverage data such as students' academic performance, learning behaviors, and preferences to suggest courses that best meet their needs. These recommendation systems can personalize learning experiences, ensuring that students engage with content that enhances their skills and knowledge.
Federal University, Dutsin-Ma, located in Katsina State, has seen an increase in the demand for online courses, especially with the rise of digital learning platforms. However, students struggle to navigate through the vast catalog of available online courses to find those that suit their learning objectives. An AI-based recommendation system could help students make informed decisions by offering personalized course suggestions. This study aims to analyze the effectiveness of AI-based online course recommendation models in improving students' learning experiences and academic outcomes at Federal University, Dutsin-Ma.
Statement of the Problem
At Federal University, Dutsin-Ma, students face difficulties in identifying online courses that align with their academic needs and personal interests. The sheer number of available online courses and resources overwhelms students, and traditional methods of course selection based on broad categories fail to provide personalized recommendations. As a result, students often enroll in courses that are either too advanced, irrelevant, or do not contribute to their academic goals. AI-based course recommendation models have the potential to address this issue by providing personalized course suggestions based on students’ learning profiles. However, there is limited research on the application of these models in Nigerian universities. This study will explore the feasibility and impact of such models at Federal University, Dutsin-Ma.
Objectives of the Study
- To develop and implement an AI-based online course recommendation model for students at Federal University, Dutsin-Ma.
- To evaluate the effectiveness of the AI-based system in suggesting relevant courses to students based on their academic performance and interests.
- To assess the potential challenges and benefits of implementing AI-based course recommendation systems in Nigerian universities.
Research Questions
- How effective is the AI-based online course recommendation model in providing relevant course suggestions to students at Federal University, Dutsin-Ma?
- What impact does the AI-based course recommendation system have on students' academic performance and satisfaction?
- What challenges and opportunities exist in implementing AI-based course recommendation models in Nigerian universities?
Research Hypotheses
- The AI-based online course recommendation model significantly improves students’ ability to select relevant courses based on their academic needs and interests.
- Students who use AI-based course recommendations will experience better academic performance and higher satisfaction levels compared to those who rely on traditional methods of course selection.
- The implementation of AI-based course recommendation models faces challenges related to data privacy, technical infrastructure, and students' acceptance of the technology.
Significance of the Study
This study will offer valuable insights into the potential benefits of AI-based course recommendation systems in improving students' learning experiences and academic outcomes at Federal University, Dutsin-Ma. The findings could guide other universities in adopting similar systems to personalize and enhance the academic journey for their students.
Scope and Limitations of the Study
The study will focus on the development and evaluation of an AI-based online course recommendation system for students at Federal University, Dutsin-Ma, Katsina State. It will be limited to undergraduate students and may not fully apply to other categories of students or universities in Nigeria. The study will also be confined to AI technologies that can be implemented using the university’s current infrastructure.
Definitions of Terms
AI-Based Course Recommendation System: A system that uses artificial intelligence algorithms to suggest relevant courses to students based on their academic profile, learning behavior, and preferences.
Online Course: A course that is offered over the internet, typically through digital platforms, and can be accessed by students remotely.
Personalized Learning: Tailoring educational experiences and resources to individual students based on their needs, preferences, and academic performance.
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