A comprehensive review of large language models: issues and solutions in learning environments
Abstract A significant advancement in artificial intelligence is the development of large language models (LLMs). Despite opposition and explicit bans by some authorities, LLMs continue to play a transformative role, particularly in education, by improving language understanding and generation capab...
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Format: | Article |
Language: | English |
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Springer
2025-01-01
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Series: | Discover Sustainability |
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Online Access: | https://doi.org/10.1007/s43621-025-00815-8 |
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author | Tariq Shahzad Tehseen Mazhar Muhammad Usman Tariq Wasim Ahmad Khmaies Ouahada Habib Hamam |
author_facet | Tariq Shahzad Tehseen Mazhar Muhammad Usman Tariq Wasim Ahmad Khmaies Ouahada Habib Hamam |
author_sort | Tariq Shahzad |
collection | DOAJ |
description | Abstract A significant advancement in artificial intelligence is the development of large language models (LLMs). Despite opposition and explicit bans by some authorities, LLMs continue to play a transformative role, particularly in education, by improving language understanding and generation capabilities. This study explores LLMs’ types, history, and training processes, alongside their application in education, including digital and higher education settings. A novel theoretical framework is proposed to guide the integration of LLMs into education, addressing key challenges such as personalization, ethical concerns, and adaptability. Furthermore, the study presents practical case studies and solutions to barriers, such as data privacy and bias, offering insights into their role in enhancing the teaching–learning process. By providing a systematic analysis and proposing a structured framework, this study advances current knowledge and highlights the significant potential of LLMs in revolutionizing education. |
format | Article |
id | doaj-art-1484064eb0304aa88fb17ccb35661587 |
institution | Kabale University |
issn | 2662-9984 |
language | English |
publishDate | 2025-01-01 |
publisher | Springer |
record_format | Article |
series | Discover Sustainability |
spelling | doaj-art-1484064eb0304aa88fb17ccb356615872025-01-19T12:05:11ZengSpringerDiscover Sustainability2662-99842025-01-016113410.1007/s43621-025-00815-8A comprehensive review of large language models: issues and solutions in learning environmentsTariq Shahzad0Tehseen Mazhar1Muhammad Usman Tariq2Wasim Ahmad3Khmaies Ouahada4Habib Hamam5Department of Electrical and Electronic Engineering Science, University of JohannesburgSchool of Computer Science, National College of Business Administration and EconomicsAbu Dhabi UniversityDepartment of Computing, School of Arts and Creative Technology, University of Greater ManchesterDepartment of Electrical and Electronic Engineering Science, University of JohannesburgDepartment of Electrical and Electronic Engineering Science, University of JohannesburgAbstract A significant advancement in artificial intelligence is the development of large language models (LLMs). Despite opposition and explicit bans by some authorities, LLMs continue to play a transformative role, particularly in education, by improving language understanding and generation capabilities. This study explores LLMs’ types, history, and training processes, alongside their application in education, including digital and higher education settings. A novel theoretical framework is proposed to guide the integration of LLMs into education, addressing key challenges such as personalization, ethical concerns, and adaptability. Furthermore, the study presents practical case studies and solutions to barriers, such as data privacy and bias, offering insights into their role in enhancing the teaching–learning process. By providing a systematic analysis and proposing a structured framework, this study advances current knowledge and highlights the significant potential of LLMs in revolutionizing education.https://doi.org/10.1007/s43621-025-00815-8Natural language processing systemsLarge language modelsNeural networksArtificial intelligenceEducationLearning systems |
spellingShingle | Tariq Shahzad Tehseen Mazhar Muhammad Usman Tariq Wasim Ahmad Khmaies Ouahada Habib Hamam A comprehensive review of large language models: issues and solutions in learning environments Discover Sustainability Natural language processing systems Large language models Neural networks Artificial intelligence Education Learning systems |
title | A comprehensive review of large language models: issues and solutions in learning environments |
title_full | A comprehensive review of large language models: issues and solutions in learning environments |
title_fullStr | A comprehensive review of large language models: issues and solutions in learning environments |
title_full_unstemmed | A comprehensive review of large language models: issues and solutions in learning environments |
title_short | A comprehensive review of large language models: issues and solutions in learning environments |
title_sort | comprehensive review of large language models issues and solutions in learning environments |
topic | Natural language processing systems Large language models Neural networks Artificial intelligence Education Learning systems |
url | https://doi.org/10.1007/s43621-025-00815-8 |
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