Abstract: Conversational technologies are revolutionizing how organizations communicate with people, thereby raising quick responses and constant availability expectations. Students often have queries about the institutional and academic policies and procedures, academic progression, activities, and more in an academic environment. In reality, the student services team and the academic advisors are overwhelmed with several queries that they cannot provide instant responses to, resulting in dissatisfaction with services. Our study leverages Artificial Intelligence and Natural Language processing technologies to build a bilingual chatbot that interacts with students in the English and Arabic languages. The conversational agent is built in Python and designed for students to support advising-related queries. We use a purpose-built domain-specific corpus consisting of the common questions advisors receive from students and their responses as the chatbots knowledge base. The chatbot engine determines the user intent by processing the input and retrieves the most appropriate response that matches the intent with an accuracy of 80% in English and 75% in Arabic. We also evaluated the chatbot interface by conducting field experiments with students to test the accuracy of the chatbot with real-time input and test the application interface.

Ghazala Bilquise, Samar Ibrahim and Khaled Shaalan, “Bilingual AI-Driven Chatbot for Academic Advising” International Journal of Advanced Computer Science and Applications(IJACSA), 13(8), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130808

@article{Bilquise2022,
title = {Bilingual AI-Driven Chatbot for Academic Advising},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130808},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130808},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {8},
author = {Ghazala Bilquise and Samar Ibrahim and Khaled Shaalan}
}