Background of the Study
Academic advising plays a critical role in guiding students through their educational journey. At Federal University Dutse, Jigawa State, traditional academic advising systems, which rely on face-to-face interactions and manual scheduling, are often inefficient and unable to address the diverse and evolving needs of students in real time. With advancements in artificial intelligence, chatbots have emerged as effective tools for automating academic advising. AI-based chatbots can provide instant responses to student inquiries, offer personalized advice based on academic records and preferences, and operate 24/7 to assist students beyond regular office hours (Chinwe, 2023). These systems utilize natural language processing and machine learning algorithms to understand and respond to complex questions, making academic support more accessible and scalable. By integrating data from institutional databases, the chatbot can offer tailored guidance on course selection, career planning, and academic resources, thus reducing the burden on human advisors and enhancing student engagement. Moreover, the use of chatbots promotes consistency and objectivity in the advising process, ensuring that all students receive reliable and accurate information. Real-time data analytics can further enable continuous improvements in the system, as feedback from interactions is used to refine its responses (Ibrahim, 2024). However, challenges such as ensuring data privacy, handling nuanced queries, and achieving high levels of user satisfaction remain. This study aims to design and implement an AI-based chatbot for academic advising at Federal University Dutse, evaluating its effectiveness in improving the accessibility and quality of academic support services while reducing administrative workload (Olufemi, 2025).
Statement of the Problem
At Federal University Dutse, the current academic advising process is constrained by limited human resources and inconsistent service delivery. Students often experience delays in receiving guidance, which can adversely affect course selection and academic planning. The traditional system, reliant on scheduled appointments and manual record-keeping, is unable to provide timely and personalized assistance, particularly during peak enrollment periods (Adebola, 2023). Additionally, the lack of continuous, round-the-clock support results in missed opportunities for intervention, leaving students without necessary guidance when urgent decisions arise. Despite the potential of AI-based chatbots to address these challenges, their implementation is still in its nascent stages, with concerns regarding accuracy, data privacy, and the handling of complex, context-specific queries. The absence of a robust, automated academic advising tool leads to inefficiencies and increased workload for academic staff, while students remain underserved in terms of immediate, reliable support. This study seeks to address these issues by developing an AI-based chatbot designed specifically for academic advising. The research will evaluate the chatbot’s performance in terms of response accuracy, user satisfaction, and its overall impact on reducing the advisory burden. By automating routine advising tasks and providing instant, personalized feedback, the system is expected to streamline the academic support process, enhance student engagement, and improve academic outcomes.
Objectives of the Study:
To design and implement an AI-based chatbot for academic advising.
To evaluate the chatbot’s effectiveness in providing accurate and timely academic support.
To propose improvements and integration strategies for enhanced advising services.
Research Questions:
How effectively does the chatbot address student inquiries compared to traditional advising?
What impact does the chatbot have on reducing advisory workload and response times?
What are the key challenges in deploying an AI-based advising system, and how can they be mitigated?
Significance of the Study
This study is significant as it introduces an AI-based chatbot to revolutionize academic advising at Federal University Dutse. The system aims to enhance the accessibility and quality of academic support, providing personalized guidance and reducing the administrative burden on advisors. The findings will offer practical recommendations for integrating AI into academic advising, promoting efficiency and improved student outcomes. This research supports the broader adoption of digital tools in higher education to meet the evolving needs of students (Chinwe, 2023).
Scope and Limitations of the Study:
The study is limited to the implementation of an AI-based chatbot for academic advising at Federal University Dutse, Jigawa State, and does not extend to other support services or institutions.
Definitions of Terms:
AI-Based Chatbot: A software agent that uses artificial intelligence to simulate conversation with users.
Academic Advising: The process of providing guidance on academic course selection and career planning.
Natural Language Processing (NLP): Technology that enables computers to interpret and generate human language.
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