Abstract:

This paper explores the integration of Artificial Intelligence (AI) and big data analytics within sustainability education to enhance graduate employability in the evolving Global Skills Taxonomy era. Drawing on pedagogical practice at the University of Westminster, the study examines how students engaged with AI-driven analysis and visualisation of social media datasets related to the United Nations Sustainable Development Goals (SDGs) between 2020 and 2022.

Students across two modules were supported to collect and analyse large datasets of social media content collected using the Twitter/X API, focusing on public sentiment surrounding selected sustainability topics and SDGs. Timed and quantitative limitations were used to develop a subset of tweets extracted from a larger corpus generated through SDG related keywords. The initial emphasis was not on social media proficiency, but on using computational tools to explore sustainability as a dynamic, real-time global issue. Using platforms such as Tableau and Excel, students developed data visualisations and produced critical analyses of their findings. The final analysis included structured metadata, including embedded media, engagement metrics for example retweets on set hashtags, geographical classifications, and temporal markers. The students were required to produce and submit a critical analysis of results with wide implications for enhancing employability in Education for Sustainability today.

The study highlights how this approach fosters key transferable skills, including data literacy, analytical thinking, and digital communication; competencies increasingly aligned with labour market demands. According to the World Economic Forum, roles in AI, big data, and sustainability analysis are among the fastest growing globally, reinforcing the relevance of such pedagogical innovation.

Findings demonstrate that embedding AI-enabled, data-driven sustainability analysis into the curriculum enhances student engagement while supporting the development of future-ready skills. Furthermore, the approach aligns with institutional commitments to sustainability, including participation in initiatives such as the EAUC SDG Accord.

The paper contributes to ongoing discourse on innovative pedagogy by proposing a model for integrating AI and big data into sustainability education. It also highlights the potential of sentiment analysis as a tool for stakeholder inclusion and real-time sustainability monitoring. Finally, it identifies opportunities for future research in curriculum design, graduate employability, and the role of emerging technologies in shaping education for the future of work

Keywords:

Artificial Intelligence (AI), Bigdata, Publics’ sentiment analysis, sustainability, SDGs, stakeholder inclusivity, new media monitoring, digital skills, Global Skills Taxonomy, employability.