Systematic Literature Review and Bibliometric Analysis on Ethical Policies for Generative Artificial Intelligence (GAI) in Higher Education Institutions (HEIs)

Generative Artificial Intelligence (GAI) has revolutionized higher education with features like instant feedback, resource and material creation, adaptive learning, interactivity, and more. However, GAI also brings with it a number of serious challenges that raise ethical and moral concerns regarding academic integrity. To carry out this transition process, it will be necessary to develop clear guidelines that adhere to integrity standards and ethical codes of higher education institutions. In addition to offering responses to a number of research questions, the purpose of this study is to further the current discourse surrounding the moral guidelines for GAI in higher education. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique and Bibliometric Analysis using VOSviewer, 37 related research studies were reviewed and evaluated. The results demonstrate that the number of articles published has been increasing over time, with the largest number of scientific publications occurring in 2024. This can be explained by the fact that, despite the fact that GAI offers benefits and drawbacks for the educational sector, particularly for higher education, it also makes clear how important it is for professionals and organizations to use GAI tools in order to handle ethical issues by continuously developing policies. By creating norms and policies, future ethical problems with GAI in education may be more accurately predicted. The engagement and dedication of academic experts and other relevant stakeholders are essential to achieving this goal of increasing public awareness and effectively utilizing GAI technology.

Authors

Institutions

Publication Details

Published
2024-11-20
DOI
https://doi.org/10.1109/icimcis63449.2024.10956736
Citations
7
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.84
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Systematic Literature Review and Bibliometric Analysis on Ethical Policies for Generative Artificial Intelligence (GAI) in Higher Education Institutions (HEIs)

Liyana Shuib, Maizatul Akmar Ismail, Artika Arista
7 citations
Artificial Intelligence in Healthcare and Education
0.84
article

Systematic Literature Review and Bibliometric Analysis on Ethical Policies for Generative Artificial Intelligence (GAI) in Higher Education Institutions (HEIs)

Liyana Shuib, Maizatul Akmar Ismail, Artika Arista
article en
7 citations

Abstract

Generative Artificial Intelligence (GAI) has revolutionized higher education with features like instant feedback, resource and material creation, adaptive learning, interactivity, and more. However, GAI also brings with it a number of serious challenges that raise ethical and moral concerns regarding academic integrity. To carry out this transition process, it will be necessary to develop clear guidelines that adhere to integrity standards and ethical codes of higher education institutions. In addition to offering responses to a number of research questions, the purpose of this study is to further the current discourse surrounding the moral guidelines for GAI in higher education. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) technique and Bibliometric Analysis using VOSviewer, 37 related research studies were reviewed and evaluated. The results demonstrate that the number of articles published has been increasing over time, with the largest number of scientific publications occurring in 2024. This can be explained by the fact that, despite the fact that GAI offers benefits and drawbacks for the educational sector, particularly for higher education, it also makes clear how important it is for professionals and organizations to use GAI tools in order to handle ethical issues by continuously developing policies. By creating norms and policies, future ethical problems with GAI in education may be more accurately predicted. The engagement and dedication of academic experts and other relevant stakeholders are essential to achieving this goal of increasing public awareness and effectively utilizing GAI technology.

University of Malaya (MY), Universitas Pembangunan Nasional Veteran Jakarta (ID)
Quality Education
Openalex Percentile: Top 23%
Artificial Intelligence in Healthcare and Education
0.84
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.