Optimization of AI-Based Course Recommender Systems for University Students in Taraba State University, Jalingo, Taraba State
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- NGN 5000
Background of the study
As universities continue to offer a wide range of courses, students often struggle to choose the most appropriate ones that align with their academic interests, strengths, and career goals. Course selection is a critical component of academic success, and poor choices can lead to academic dissatisfaction, underperformance, or even delayed graduation. AI-based course recommender systems have been developed to address this issue by providing personalized recommendations to students based on their preferences, previous academic performance, and career aspirations. These systems use machine learning algorithms to analyze data and suggest courses that are most likely to meet students' needs. In Taraba State University, Jalingo, Taraba State, the implementation of such a system could help guide students through the course selection process, optimize their learning experiences, and improve academic outcomes. This study seeks to explore the effectiveness of AI-based course recommender systems in helping university students at Taraba State University make informed decisions about their academic pathways.
Statement of the problem
At Taraba State University, students often face difficulties in selecting courses that align with their academic strengths and future career goals, leading to suboptimal academic performance and unnecessary delays in graduation. While academic advisors provide some guidance, there is a lack of personalized, data-driven systems that can assist students in choosing the best courses based on their unique academic profile and preferences. AI-based course recommender systems have the potential to optimize the course selection process, but their effectiveness and practicality in the context of Taraba State University remain uncertain.
Objectives of the study
1. To design and implement an AI-based course recommender system for students at Taraba State University, Jalingo.
2. To evaluate the effectiveness of the AI-based recommender system in improving students' course selection and academic outcomes.
3. To assess the perceptions of students and faculty on the use of AI-based course recommender systems.
Research questions
1. How effective is the AI-based course recommender system in helping students at Taraba State University select the most appropriate courses?
2. What impact does the AI-based system have on students' academic outcomes, such as course grades and graduation rates?
3. How do students and faculty perceive the use of AI-based course recommender systems in academic decision-making?
Research hypotheses
1. The AI-based course recommender system will significantly improve students' course selection and academic outcomes.
2. The use of the AI-based system will lead to better alignment between students' course choices and their academic strengths and career goals.
3. Students and faculty will have positive perceptions of the AI-based course recommender system and its impact on academic success.
Significance of the study
This study will provide valuable insights into the potential of AI-based course recommender systems to enhance the academic decision-making process in higher education. The findings will contribute to the growing body of research on AI in education and may guide the development of similar systems at other universities.
Scope and limitations of the study
The study will focus on the implementation and evaluation of an AI-based course recommender system specifically at Taraba State University, Jalingo. Limitations include challenges related to system integration, the availability of relevant data, and user adoption.
Definitions of terms
• Course Recommender System: An AI-based system that uses data to suggest courses to students based on their academic profiles and preferences.
• AI (Artificial Intelligence): A branch of computer science that deals with creating systems capable of performing tasks that typically require human intelligence, such as decision-making and problem-solving.
• Academic Outcomes: The results of a student’s academic efforts, typically measured by grades, course completion, and graduation rates.
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