Virtual teaching assistant for undergraduate students using natural language processing & deep learning

Abstract

Online education’s popularity has been continuously increasing over the past few years. Many universities were forced to switch to online education as a result of COVID-19. In many cases, even after more than two years of online instruction, colleges were unable to resume their traditional classroom programs. A growing number of institutions are considering a hybrid approach to education, in which some face-to-face teaching is augmented with online learning. Nevertheless, many online education systems are inefficient, and this results in a poor rate of student retention. In this paper, we are offering a primary dataset, a virtual teaching assistant named VTA-bot, and its system architecture. In addition, we are showing a first implementation of the suggested system, which consists of a chatbot that can be queried about the content and topics of the ‘Programming Language I’ course, an introductory programming language course offered by the CSE department of Brac University. Students in their first year of university will benefit from this strategy, which aims to increase student participation and involvement in online education.