DESIGN AND IMPLEMENTATION OF AN ONLINE CHATBOT FOR ADMISSION ENQUIRY
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CHAPTER ONE
INTRODUCTION
1.1 Background to the study
Chatbots have been increasingly popular in a variety of corporate sectors in recent years, including higher education institutions such as universities. In the higher education context, applicants send their queries through the university’s email or the inquiry section on the website, which are typically slow to respond to or left unanswered, whereas chatbots can provide accurate and timely responses to common admission enquiries, reducing the workload of the admissions team and improving the overall applicant experience. However, implementing this chatbot, which can be complex, necessitates knowledge of natural language processing (NLP) and machine learning (ML) technologies, as well as a thorough understanding of the user’s journey and the various touchpoints that prospective students have with the university during the inquiry process. Using conversational AI, the bot-human interaction can also be made more human. A chatbot system simulates a conversation (or chat) with a user in natural language utilizing conversational artificial intelligence (AI) technology via messaging apps, websites, mobile apps, or the phone (Selig, 2022). A chatbot is a piece of software that is created artificially and communicates with humans using natural language. Chatbots can serve as a personal assistant on mobile devices, providing users with individualized information, facilitating real-time social contact through media, and even being utilized in health consultations (M. Yamada, 2016). According to (Court Bishop, 2022), customer service teams that handle up to 20,000 support requests per month might save more than 240 hours by simply utilizing chatbots. Chatbots are increasingly employed in instant messaging and are being integrated into people’s daily life, retail experiences, and educational courses (Ferrell, 2020). In general, bots are robots that are sophisticated enough to interpret human requests and then frame them in a way that other software systems can understand in order to request the data they require (Sumit, 2019). The purpose of this study is to solve the gap in rapid response between universities and prospective students while also analyzing its success in improving the overall experience for applicants and expediting the admissions enquiry process.
1.2 Statement of problem
For each new academic session, the university receives a large number of applications, which are then processed into enrolment. Applicants may need to ask questions about courses, the university’s atmosphere, fees, lodging, and learning systems. With so many student inquiries putting a strain on the admissions department, the majority of questions may go unanswered. There is a need for a system that can respond to inquiries accurately and quickly, as well as guide applicants on what to do, by managing several inquiries at the same time.
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