Intelligent Chatbot for Admission in Higher Education

Abstract

Universities assist prospective students by giving counselling services and information, which is usually done directly at the educational institution, over the phone, or through social media accounts that is available on the college website. However, increasing visitors cause longer wait times due to officers’ restricted availability, resulting in lower satisfaction among prospective new students. Furthermore, this service is only available during university or college business hours. One possible solution to solve this problem is to use a chatbot to answer frequent questions raised by prospective new students. Intelligent chatbot for university admission is discussed in this study. Botsify platform was used to develop the chatbot for admission. 42 postgraduate students clicked on the chatbot link, most of them from Princess Nourah University. These students interacted with the chatbot by asking numerous questions and receiving responses from the chatbot. The chatbot performance was measured by using both the chatbot usability questionnaire and Confusion Matrix. According to the study’s findings, the chatbot system that was created could correctly and adequately answer questions provided by prospective students while the questions were stored in the chatbot knowledge. The measurement of chatbot performance was done by using Chatbot Usability Questionnaire (CUQ) which consisted of sixteen balanced questions about various elements of chatbot usability. The participants’ number of the Chatbot Usability questionnaire were 22. The result of the CUQ average was 76.6. At the same time, the Confusion Matrix was used to evaluate the chatbot performance and the accuracy of the chatbot was 91%.

Tayseer: A Novel AI-Powered Arabic Chatbot Framework for Technical and Vocational Student Helpdesk Services and Enhancing Student Interactions

“…A survey by Al-Hagbani and Khan [50] emphasized the difficulties associated with creating Arabic chatbots, mainly due to the intricacy of the language. Notwithstanding these difficulties, RASA has been effectively implemented in several fields, including university [51,52] and college inquiry chatbots [53]. The combination of RASA NLU and neural network techniques has also been investigated to create an advanced chatbot system [25,54].…”

“…The creation of an Arabic RASA chatbot necessitates profound comprehension of the distinctive linguistic attributes of the Arabic language and the employment of specialized tools and technology specifically designed for processing the Arabic language. Utilizing open-source frameworks such as RASA and including morphological and syntactic disambiguation greatly enhances the creation of a proficient Arabic RASA chatbot [26,53].…”

Developing Effective Educational Chatbots with GPT: Insights from a Pilot Study in a University Subject

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