Building a Machine Learning Powered Chatbot for KSU Blackboard Users

Abstract

Chatbots have attracted the interest of many entities within the public and private sectors locally within Saudi Arabia and also globally. Chatbots have many implementations in the education field and can range from enhancing the elearning experience to answer students' inquiries about course schedules and grades, tracking prerequisites information and elective courses. This work aim is to develop a chatbot engine that helps with frequently asked questions about the Blackboard system, which could be embedded into the Blackboard website. It contains a machine-learning model trained on Arabic datasets. The engine accepts both Arabic textual content as well as English textual content if needed; for commonly used English terminologies. Rasa framework was chosen as the main tool for developing the Blackboard chatbot. The dataset to serve the current need (i.e. Blackboard system) was requested from Blackboard support staff to build the initial dataset and get a sense of the frequently asked questions by KSU Blackboard student users. The dataset is designed to account for as many as possible of KSU Blackboard related inquires to provide the appropriate answers and reduce the workload of Blackboard system support staff. Testing and evaluating the model was a continuous process before and after the model deployment. The model post-tuning metrics were 93.4%, 92.5%, 92.49% for test accuracy, f1-score and precision, respectively. The average reported accuracy in similar studies were near 90% on average as opposed to results reported here.

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].…”