ITDS | SPMS

UENR POWERED AI CHATBOT AND LITERACY MOBILE APP

Project Description
Supervisor

As a result of the rapid technological development and the development of the chatbot concept and the time and effort it can save. Many specialized frameworks have emerged to undertake chatbot creation and development. By relying on artificial intelligence, the chatbot has integrated machine learning within it, and it has become more comprehensive and wider for various technological fields. The use of chatbots evolved rapidly in numerous fields in recent years, including Marketing, Supporting Systems, Education, Health Care, Cultural Heritage, and Entertainment. In this paper, we first present a historical overview of the evolution of the international community’s interest in chatbots. The project is focused on creating and implementing an Artificial Intelligence (AI) chatbot tailored for university of natural resource operations. The chatbot employs Natural Language Processing (NLP) and Machine Learning (ML) to simulate human conversations and provide real-time, intelligent answers to students' questions. The aim is to reduce the workload for human representatives, increase the efficiency of services, and improve user satisfaction. Natural language processing, which evolved from computational linguistics, uses methods from various disciplines, such as computer science, artificial intelligence, linguistics, and data science, to enable computers to understand human language in both written and verbal forms. The chatbot will be 24/7 available, with real-time help and immediate response rates. Python (Django, FastAPI), WebSockets, and a React.js frontend will be utilized to develop the system for an interactive as well as scalable user interface. This paper outlines the scope, aims, methodology, expected outcomes, as well as project organization. AI chatbots can provide immediate support in answering queries, explaining, and providing additional resources. For teachers, the primary benefits are the time-saving support and enhanced pedagogy. But our study also highlights important challenges and key considerations that teachers must manage carefully. These involve issues of AI applications like trustworthiness, correctness, and moral considerations.

Machine Learning: Machine Learning (ML) research in Computer Science and Information Technology focuses on the development of algorithms and models that enable computers to learn from data and improve their performance over time without being explicitly programmed. It is a subset of Artificial Intelligence that uses statistical techniques to give machines the ability to learn patterns, make decisions, and predict outcomes based on data. Supervised learning, a key area of ML research, involves training models on labeled data, where the input-output relationships are predefined. This method is widely used for tasks such as classification (e.g., spam detection) and regression (e.g., predicting house prices). Unsupervised learning, on the other hand, involves finding hidden patterns in data without predefined labels, with clustering and association being typical applications in areas such as customer segmentation and anomaly detection. Reinforcement learning is another area of ML that focuses on teaching agents to make decisions by interacting with their environment and receiving feedback in the form of rewards or penalties. It is often applied in robotics, game playing, and autonomous systems, where continuous learning and adaptation are required.

This AI chatbot mobile app for NLP and ML aims to address the pressing need for available, correct, and counseling by developing a mobile app that provides students with information, resources, and counseling needed to achieve academic wellness and make proper academic decisions

2024/2025

Feb 3, 2026

AFARI YAW ESHUN – UEB3201021, BOAMAH OWUSU CHARLES–UEB3263623, BONSU AMA KONAMAH – UEB3207821, ACKON PRINCE EDINOR– UEB3279423, BAAH MARFO WILLIAMS – UEB3218621

BSc Information Technology