Investigation into AI-Based Personalized Academic Advising Systems in Gombe State University, Gombe State
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- NGN 5000
Background of the Study
Academic advising plays a vital role in supporting students throughout their academic journey by providing guidance on course selection, career advice, and personal development. However, the traditional methods of academic advising, which often rely on one-on-one meetings with advisors, can be resource-intensive and time-consuming, leading to inconsistent levels of support for students (Ogunyemi & Akinbode, 2023). With the growing student population in many universities, there is a need for more efficient and scalable solutions to provide personalized academic guidance. Artificial intelligence (AI) has the potential to revolutionize academic advising by offering data-driven, personalized recommendations tailored to each student's academic performance, career goals, and personal preferences (Jones et al., 2024).
In the context of Gombe State University, an AI-based personalized academic advising system could serve as an intelligent virtual advisor, providing real-time advice to students and assisting faculty members in offering timely support (Khan et al., 2023). Such a system would analyze data on academic performance, past course selections, and even student interests to offer tailored suggestions for course planning and career development. This study aims to investigate the feasibility and effectiveness of an AI-based personalized academic advising system at Gombe State University.
Statement of the Problem
Gombe State University faces challenges in offering consistent and personalized academic advising to its large student population. Traditional academic advising methods are not sufficient to cater to the growing number of students and often lack the data-driven insights necessary for tailored advice. This leads to inefficiencies in academic planning, delays in decision-making, and unmet student needs. The study aims to assess whether AI-powered systems can address these issues and improve the quality and accessibility of academic advising.
Objectives of the Study
- To design and implement an AI-based personalized academic advising system for students at Gombe State University.
- To evaluate the effectiveness of the AI system in providing personalized academic advice.
- To assess the impact of the AI-based advising system on student satisfaction and academic performance.
Research Questions
- How effectively does the AI-based personalized advising system provide relevant academic advice to students?
- What are the key factors that influence the accuracy and relevance of the AI-generated advice?
- How does the implementation of AI-based advising impact student satisfaction and academic success?
Research Hypotheses
- The AI-based personalized advising system will offer more accurate academic guidance compared to traditional advising methods.
- Students who use the AI-based advising system will report higher levels of satisfaction with their academic advising.
- The implementation of the AI-based system will lead to improved academic performance among students.
Significance of the Study
This study will provide valuable insights into how AI can enhance academic advising at Gombe State University by offering personalized, real-time recommendations. It will help optimize resource allocation in academic advising, improve student decision-making, and contribute to better academic outcomes.
Scope and Limitations of the Study
The study will focus on the design and evaluation of an AI-based academic advising system for undergraduate students at Gombe State University. The research will be limited to students in selected academic programs and will not include postgraduate students or those from other universities.
Definitions of Terms
AI-Based Personalized Advising System: A data-driven system powered by AI that provides tailored academic guidance to students based on their academic records, interests, and career goals.
Academic Advising: The process of helping students make informed decisions about their academic and career paths.
Student Satisfaction: The level of contentment students feel regarding their academic advising experience.
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