https://journals.bohrpub.com/index.php/bijscit <p><strong>ISSN: 2583-2026 (Online)</strong></p> <p><strong>BOHR International Journal of Smart Computing and Information Technology (BIJSCIT)</strong> is an open access peer-reviewed journal that publishes articles which contribute new results in all the areas of Smart Computing and Information Technology. Authors are solicited to contribute to the journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in this area.</p> BOHR Publishers en-US BOHR International Journal of Smart Computing and Information Technology 2583-2026 <p>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a> that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.</p> https://journals.bohrpub.com/index.php/bijscit/article/view/723 <p>In recent years, there has been a notable shift in how people interact with technology, marked by the growing popularity of voice assistants and chatbots. As these systems’ capabilities improve, they are increasingly becoming the preferred method of contact between customers and technology. Chatbots are popular owing to their simplicity and efficiency. Chatbots may manage several users’ inquiries simultaneously, removing the need for individual staff members to address them. Therefore, businesses that integrate chatbots into their operational systems save money. This study empirically investigated the efficacy of natural language processing (NLP) in creating a chatbot specifically tailored to handle college information inquiries. This paper introduces Lucy, a chatbot that utilizes a deep neural network in conjunction with complex language models including BERT, RoBERTa, and DistilBERT architectures. College students were surveyed to assess Lucy’s performance in a user research study. The research showed that Lucy is effective as a teaching tool for imparting knowledge to students, with an accuracy rate above 85%. From the evidence, Lucy is capable of subsequently reducing in-person enquiries by acting as a centralized forum for student questions, which highlights the chatbots in the education sector and also demonstrates the capabilities to improve the quality of information shared to the students.</p> Rupesh Gelal Suraj Karki Saman Shrestha Krishna Bikram Shah Copyright (c) 2024 Krishna Bikram Shah, Rupesh Gelal, Suraj Karki, Saman Shrestha https://creativecommons.org/licenses/by/4.0 2024-09-04 2024-09-04 5 1 1 11 10.54646/bijscit.2023.39