A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3

In contemporary education, accurately predicting student performance and delivering prompt feedback is paramount for fostering a comprehensive grasp of academic progress. Consequently, educators must adapt their teaching methodologies to optimize learning outcomes. To tackle this challenge, researc...

Full description

Saved in:
Bibliographic Details
Main Authors: Sireesha Prathigadapa, Salwani Binti Mohd Daud
Format: Article
Language:English
Published: Commonwealth of Learning 2025-03-01
Series:Journal of Learning for Development
Subjects:
Online Access:https://jl4d.org/index.php/ejl4d/article/view/1367
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849393210493763584
author Sireesha Prathigadapa
Salwani Binti Mohd Daud
author_facet Sireesha Prathigadapa
Salwani Binti Mohd Daud
author_sort Sireesha Prathigadapa
collection DOAJ
description In contemporary education, accurately predicting student performance and delivering prompt feedback is paramount for fostering a comprehensive grasp of academic progress. Consequently, educators must adapt their teaching methodologies to optimize learning outcomes. To tackle this challenge, researchers have proposed and implemented diverse alternative and advanced strategies. This study conducts a systematic review of prior research endeavors centered on virtual tutoring and learning environments, aiming to pinpoint significant contributions in educational systems. Emphasis lies on the utilization of machine learning and deep learning models, along with the datasets utilized. Through this exploration, the study illuminates associated hurdles and proposes potential remedies for implementing virtual tutors and performance evaluation. Moreover, it proposes a solution for efficiently managing the abundant data in e-learning platforms. By synthesizing findings from multiple studies, this research enriches the existing knowledge in education systems, offering valuable insights for educators and researchers. The study's outcomes hold promise for enhancing virtual tutoring and learning environments, ultimately enriching students' educational journey and fostering academic advancement.
format Article
id doaj-art-1d35527a1656479ab81b97f6804cf764
institution Kabale University
issn 2311-1550
language English
publishDate 2025-03-01
publisher Commonwealth of Learning
record_format Article
series Journal of Learning for Development
spelling doaj-art-1d35527a1656479ab81b97f6804cf7642025-08-20T03:40:30ZengCommonwealth of LearningJournal of Learning for Development2311-15502025-03-01121A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3Sireesha Prathigadapa0Salwani Binti Mohd DaudAsia Pacific University In contemporary education, accurately predicting student performance and delivering prompt feedback is paramount for fostering a comprehensive grasp of academic progress. Consequently, educators must adapt their teaching methodologies to optimize learning outcomes. To tackle this challenge, researchers have proposed and implemented diverse alternative and advanced strategies. This study conducts a systematic review of prior research endeavors centered on virtual tutoring and learning environments, aiming to pinpoint significant contributions in educational systems. Emphasis lies on the utilization of machine learning and deep learning models, along with the datasets utilized. Through this exploration, the study illuminates associated hurdles and proposes potential remedies for implementing virtual tutors and performance evaluation. Moreover, it proposes a solution for efficiently managing the abundant data in e-learning platforms. By synthesizing findings from multiple studies, this research enriches the existing knowledge in education systems, offering valuable insights for educators and researchers. The study's outcomes hold promise for enhancing virtual tutoring and learning environments, ultimately enriching students' educational journey and fostering academic advancement. https://jl4d.org/index.php/ejl4d/article/view/1367virtual tutorChatGPTstudent performance
spellingShingle Sireesha Prathigadapa
Salwani Binti Mohd Daud
A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3
Journal of Learning for Development
virtual tutor
ChatGPT
student performance
title A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3
title_full A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3
title_fullStr A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3
title_full_unstemmed A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3
title_short A Review of Virtual Tutoring Systems and Student Performance Analysis Using GPT-3
title_sort review of virtual tutoring systems and student performance analysis using gpt 3
topic virtual tutor
ChatGPT
student performance
url https://jl4d.org/index.php/ejl4d/article/view/1367
work_keys_str_mv AT sireeshaprathigadapa areviewofvirtualtutoringsystemsandstudentperformanceanalysisusinggpt3
AT salwanibintimohddaud areviewofvirtualtutoringsystemsandstudentperformanceanalysisusinggpt3
AT sireeshaprathigadapa reviewofvirtualtutoringsystemsandstudentperformanceanalysisusinggpt3
AT salwanibintimohddaud reviewofvirtualtutoringsystemsandstudentperformanceanalysisusinggpt3