Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Advancing Sustainable Development Goal 4 – a comparative analysis of large language models

Bibliographic Data

ID14897771
AuthorsAnshul Saxena (0000-0002-5573-2802, Symbiosis Centre for Information Technology, Symbiosis International (Deemed University)), Bikramjit Rishi (0000-0002-7934-0707, Shiv Nadar University)
Year2025
Volume39
Issue7
Pages1774-1791
Publication date2025-12-02
Open AccessNo
TypeARTICLE
VenueInternational Journal of Educational Management (JOURNAL)
Journal identifiersISSN: 0951-354X • E-ISSN: 1758-6518
PublisherEmerald (PUBLISHER)
DOI10.1108/ijem-12-2024-0837
OpenAlexW4415688591
LanguageEN
References cited41

Purpose This study investigates how generative AI models (ChatGPT, Claude and Gemini) can be systematically integrated into curriculum design using Hilda Taba’s inductive model. Addressing Sustainable Development Goal 4 (SDG 4), it introduces the EduCompass framework to enhance inclusivity and instructional quality. Design/methodology/approach A structured needs assessment with MBA students identified skill gaps in analytics and AI ethics. Deep research prompts were fed into ChatGPT, Claude and Gemini to generate curriculum components. Outputs were evaluated on accuracy, relevance and clarity by academic experts and analyzed for readability (Flesch–Kincaid), semantic similarity (cosine) and statistical significance (ANOVA). Findings ChatGPT produced the most readable and pedagogically sound content, followed by Gemini and Claude. ChatGPT also received the highest expert ratings for clarity, accuracy and relevance, with significant differences confirmed via ANOVA. Cosine similarity showed the highest conceptual overlap between ChatGPT and Gemini. Originality/value This is a study to empirically compare AI-generated curricula across multiple LLMs within a classical curriculum framework. EduCompass offers a replicable model for AI-enhanced, SDG-aligned curriculum design in higher education

Analytics · CLARITY · Curriculum · Curriculum development · Readability · Sustainable development · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI · Explainable Artificial Intelligence (XAI

  • Artificial Intelligence-Enabled Intelligent Assistant for Personalized and Adaptive Learning in Higher Education

    Open Access•Ramteja Sajja, Yusuf Sermet et al.•Information•2024

  • Application of generative artificial intelligence (GenAI) in language teaching and learning

    Open Access•Locky Law•Computers and Education Open•2024

  • Policy guidelines and recommendations on AI use in teaching and learning

    Open Access•Aaron A Funa, Renz Alvin E Gabay•Social Sciences & Humanities Open•2025

  • Perceptions and Use of AI Chatbots among Students in Higher Education

    Open Access•Odin Monrad Schei, Anja Møgelvang et al.•Education Sciences•2024

  • Integration of Generative Artificial Intelligence in Higher Education

    Open Access•Jorge Cordero, Jonathan Torres-Zambrano et al.•Education Sciences•2024

  • An analysis of the generative AI use as analyst in qualitative research in science education

    Open Access•Juliana Rodrigues dos Anjos, Maira Giovana De Souza et al.•Revista Pesquisa Qualitativa•2024

  • The promise and challenges of generative AI in education

    Open Access•Michail N Giannakos, Roger Azevedo et al.•Behaviour and Information…•2025

  • AI and human collaboration in tourism

    Anshul Saxena, Bikramjit Rishi•Asia Pacific Journal of Tourism…•2025

Highly citedNo

Tools

Open DOI
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae