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

TL;DR

This paper presents VTA-bot, a virtual teaching assistant utilizing natural language processing and deep learning to enhance student engagement and retention in online undergraduate Python courses.

Contribution

It introduces a novel chatbot system architecture and a primary dataset for supporting first-year students in online Python programming education.

Findings

Increased student participation in online Python courses

Improved engagement through the VTA-bot chatbot

System architecture demonstrated effective query handling

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 blended learning with some parts in-person and the rest of the learning taking place online. 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, the initial implementation of a virtual teaching assistant named VTA-bot, and its system architecture. Our primary implementation of the suggested system consists of a chatbot that can be queried about the content and topics of the fundamental python programming language course. Students in their first year of university will be benefited from this strategy, which aims to increase student participation and involvement in online education.