Exploring the Use of AI in Predicting Student Career Paths in Federal College of Education, Yola, Adamawa State
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Background of the Study
Career guidance is crucial for students, especially those in higher education, as it helps them make informed decisions about their future professional paths. The use of artificial intelligence (AI) in career counseling and path prediction is an emerging field that aims to enhance the accuracy and effectiveness of traditional methods. AI-driven systems can analyze a range of factors, including academic performance, interests, skills, and demographic data, to predict suitable career options for students (Olalekan & Abiola, 2024). At the Federal College of Education in Yola, Adamawa State, the lack of an automated and data-driven system for predicting students’ career paths has led to inefficiencies and uncertainty among students about their future career prospects. This study will explore the potential of AI in predicting the career paths of students, thereby offering personalized recommendations that align with their strengths and aspirations.
Statement of the Problem
The current system for career counseling at Federal College of Education, Yola, is largely manual and lacks data-driven approaches. Many students face difficulties in identifying career options that align with their skills and academic interests. This results in students pursuing career paths that may not be the best fit for them, potentially leading to dissatisfaction and lower success rates. The study seeks to explore how AI can be used to predict suitable career paths for students, thus offering a more personalized and data-driven approach to career counseling.
Objectives of the Study
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To assess the current state of career counseling practices at Federal College of Education, Yola.
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To design and implement an AI-driven system for predicting student career paths.
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To evaluate the effectiveness of the AI-based system in providing accurate career recommendations for students.
Research Questions
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What are the challenges currently faced in career counseling at Federal College of Education, Yola?
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How can AI be utilized to predict students’ career paths based on academic and personal data?
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What is the impact of AI-based career prediction systems on students' career decision-making?
Research Hypotheses
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AI-driven systems will provide more accurate career path predictions compared to traditional counseling methods.
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The implementation of an AI-based career prediction system will result in better career alignment for students at Federal College of Education, Yola.
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Students will experience greater satisfaction and clarity in their career decisions with the use of AI-driven predictions.
Significance of the Study
This study will contribute to improving career counseling at Federal College of Education, Yola, by implementing AI-based systems for personalized career path predictions. The findings will also provide valuable insights for other institutions considering the integration of AI in career services.
Scope and Limitations of the Study
The study will focus on Federal College of Education, Yola, and will involve the design and implementation of an AI system to predict career paths for students. Limitations include the availability and quality of data for training the AI model and potential resistance to adopting AI-driven systems in the counseling process.
Definitions of Terms
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AI in Career Counseling: The use of artificial intelligence to analyze data and make predictions regarding suitable career paths for students.
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Career Path Prediction: The process of using data and algorithms to recommend suitable career options for individuals based on their skills, interests, and academic background.
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Student Profiling: The collection and analysis of student data to understand their strengths, weaknesses, and preferences in academic and career-related decisions.
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