Content area

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.

Details

1009240
Identifier / keyword
Title
Virtual teaching assistant for undergraduate students using natural language processing & deep learning
Publication title
arXiv.org; Ithaca
Publication year
2024
Publication date
Nov 13, 2024
Section
Computer Science
Publisher
Cornell University Library, arXiv.org
Source
arXiv.org
Place of publication
Ithaca
Country of publication
United States
University/institution
Cornell University Library arXiv.org
e-ISSN
2331-8422
Source type
Working Paper
Language of publication
English
Document type
Working Paper
Publication history
 
 
Online publication date
2024-11-15
Milestone dates
2024-11-13 (Submission v1)
Publication history
 
 
   First posting date
15 Nov 2024
ProQuest document ID
3128885044
Document URL
https://www.proquest.com/working-papers/virtual-teaching-assistant-undergraduate-students/docview/3128885044/se-2?accountid=208611
Full text outside of ProQuest
Copyright
© 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Last updated
2024-11-16
Database
2 databases
  • Coronavirus Research Database
  • ProQuest One Academic