Optimization of an AI-Based Real-Time Student Feedback System in Federal University, Lokoja, Kogi State
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Background of the study
Student counseling is an essential part of student support services in universities. At Kebbi State University of Science and Technology (KSUSTA) in Aliero, Kebbi State, the traditional counseling system faces several challenges, including overburdened counselors, lack of personalized support, and delays in addressing students' issues. These challenges hinder the effectiveness of counseling services, potentially affecting students' academic performance and mental well-being. AI-driven student counseling systems have emerged as a promising solution to these issues by offering personalized, scalable, and responsive support. Such systems use machine learning algorithms, natural language processing, and data analytics to provide tailored advice, guidance, and real-time interventions. AI counseling systems can identify students' needs through the analysis of academic performance, behavioral data, and personal inputs. This study aims to investigate the potential of implementing AI-driven student counseling systems at KSUSTA, assessing how these systems can improve student support and address the limitations of traditional counseling methods.
Statement of the problem
At Kebbi State University of Science and Technology, the current student counseling system struggles to meet the growing demands of the student population. Counselors are often overwhelmed with large caseloads, resulting in delayed responses to students' concerns and insufficient personalized guidance. Students frequently report feeling disconnected from counseling services due to long waiting times, which impacts their academic success and emotional well-being. The lack of a proactive approach in addressing students' issues further exacerbates these challenges. AI-driven counseling systems have the potential to address these shortcomings by providing real-time, personalized interventions. However, the integration of AI into the existing infrastructure presents challenges that need to be explored. This research will investigate the feasibility of developing and implementing an AI-based counseling system at KSUSTA and evaluate its impact on student support services.
Objectives of the study
1. To design and implement an AI-driven student counseling system for Kebbi State University of Science and Technology.
2. To assess the effectiveness of the AI-driven system in providing personalized counseling support to students.
3. To evaluate the impact of AI counseling systems on student academic performance, well-being, and engagement.
Research questions
1. How can AI-driven systems be integrated into existing counseling services at Kebbi State University of Science and Technology?
2. What is the impact of AI-driven counseling systems on the quality of support and personalized guidance provided to students?
3. How do AI-driven counseling systems influence students' academic performance and mental well-being?
Research hypotheses
1. AI-driven counseling systems will significantly improve the efficiency and responsiveness of student support services at KSUSTA.
2. The implementation of AI-driven counseling systems will result in increased student satisfaction with counseling services.
3. AI-driven counseling systems will have a positive impact on students' academic performance and overall well-being.
Significance of the study
This study will contribute valuable insights into the potential benefits and challenges of implementing AI-driven counseling systems in Nigerian universities. The findings will help KSUSTA enhance its counseling services, offering a more personalized, accessible, and efficient approach to student support. Additionally, this research could serve as a model for other institutions in Kebbi State and beyond that wish to integrate AI into their student counseling frameworks.
Scope and limitations of the study
The study focuses on the design and implementation of an AI-driven counseling system at Kebbi State University of Science and Technology in Aliero, Kebbi State. The research will explore AI technologies such as machine learning, natural language processing, and chatbots, specifically for enhancing counseling services. It does not extend to other student services or institutions outside of KSUSTA. Limitations include potential challenges in system integration, staff training, and resistance to new technologies.
Definitions of terms
• Artificial Intelligence (AI): The use of machine learning, natural language processing, and other technologies to simulate human intelligence and automate processes.
• Student Counseling System: A support system in universities aimed at assisting students with personal, academic, and psychological issues.
• Natural Language Processing (NLP): A branch of AI that enables machines to understand, interpret, and respond to human language.
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