Investigation into the Use of AI in Predicting University Student Career Paths: A Case Study of Ibrahim Badamasi Babangida University, Lapai (Lapai LGA, Niger State)
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- NGN 5000
Background of the Study
As universities increasingly focus on preparing students for successful careers, predicting potential career paths for students based on their academic performance, interests, and skills has become a valuable tool for career counseling and planning. Traditional career services often rely on interviews and surveys to guide students, but these methods may not always provide comprehensive insights into students’ future career trajectories (Baker & Clark, 2024). Artificial intelligence (AI), particularly machine learning models, offers a novel approach to predicting students’ career paths by analyzing large datasets, including academic records, extracurricular activities, and behavioral patterns (Miller & Roberts, 2025).
Ibrahim Badamasi Babangida University in Lapai, Niger State, presents a fitting case study for exploring the use of AI in predicting career paths for university students. By utilizing AI models to analyze student data and forecast potential career outcomes, the university can provide tailored career guidance, helping students make informed decisions about their future careers. Previous studies have shown that AI can significantly improve career path predictions by considering a variety of factors beyond academic performance, such as personal interests and market trends (Yang et al., 2023). This study aims to investigate how AI can be used to predict career paths for students at Ibrahim Badamasi Babangida University.
Statement of the Problem
Career counseling at Ibrahim Badamasi Babangida University often relies on traditional methods that do not fully take into account the complex factors influencing career choices. As a result, students may receive generic or inaccurate advice that does not align with their true potential or market demands (Adams & King, 2024). This study addresses the gap by investigating the use of AI in predicting career paths, providing more accurate and personalized career advice to students.
Objectives of the Study
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To explore the use of AI in predicting the career paths of university students at Ibrahim Badamasi Babangida University.
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To assess the accuracy of AI-based career prediction models compared to traditional career counseling methods.
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To evaluate the impact of AI-driven career path predictions on student career decision-making and outcomes.
Research Questions
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How can AI models be utilized to predict the career paths of university students at Ibrahim Badamasi Babangida University?
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How accurate are AI-based predictions of career paths compared to traditional career counseling methods?
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How does AI-based career path prediction affect the career decision-making process for students?
Research Hypotheses
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AI-based models will provide more accurate career path predictions for students at Ibrahim Badamasi Babangida University than traditional methods.
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Students receiving AI-based career predictions will show improved career decision-making and satisfaction with their chosen career paths.
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AI-driven career counseling will lead to better alignment between students’ career choices and job market opportunities.
Significance of the Study
This study will provide valuable insights into the role of AI in enhancing career counseling services at universities. The findings can help Ibrahim Badamasi Babangida University refine its career services and guide other institutions in implementing AI-driven career prediction models to improve student outcomes.
Scope and Limitations of the Study
The study will focus on Ibrahim Badamasi Babangida University in Lapai LGA, Niger State, and will explore the use of AI in predicting student career paths. Limitations include the availability and quality of student data, as well as the potential for model biases and challenges in integrating AI technology into existing university systems.
Definitions of Terms
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AI-Based Career Path Prediction: The use of artificial intelligence algorithms to analyze student data and predict suitable career paths based on academic performance and other factors.
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Career Counseling: A service provided by universities to guide students in making informed decisions about their future careers.
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Machine Learning: A subset of AI that enables systems to learn from data and make predictions or decisions without explicit programming.
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