| Issue |
E3S Web Conf.
Volume 513, 2024
International Conference on SDGs for Sustainable Future (ICSSF 2024)
|
|
|---|---|---|
| Article Number | 04001 | |
| Number of page(s) | 10 | |
| Section | Social Sciences, Humanities and Economics | |
| DOI | https://doi.org/10.1051/e3sconf/202451304001 | |
| Published online | 24 April 2024 | |
The comparison of Chat GPT, Perplexity AI, and Scopus database to capture Indonesian higher education quality in achieving SDGs 2030
1 Physics Education Program, Universitas Negeri Surabaya, 60231, Surabaya, Indonesia
2 Postgraduate Science Education Program, Universitas Negeri Surabaya, 60231, Surabaya, Indonesia
3 Graduate Institute of Science Education, National Dong Hwa University, 97401 Hualien, Taiwan
* Corresponding author: nadisuprapto@unesa.ac.id
Indonesia’s higher education sector significantly contributes to achieving the Sustainable Development Goals (SDGs), particularly in the context of quality education. The research aims to (1) analyse the challenges of Indonesian higher education in achieving SDGs 2030 based on data and facts, (2) analyse Indonesian higher education’s challenges in achieving SDGs 2030 by making a plan or design, (3) analyse the impact of implementing the design in Indonesian higher education achieving SDGs 2030. Literature reviews using AI tools such as Chat GPT and Perplexity AI are rarely used, especially in discovering remedies to enhance the quality of education in higher education institutions in Indonesia. There has yet to be further research comparing AI tools and the Scopus database to find literature on specific SDG topics. Research shows several challenges in Indonesian higher education in achieving SDGs 2030, with the most discussed being access and equity, quality of education, universities programs, and infrastructure.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.