Exploring the connections between integrated sustainable curricula, generative AI tools, and perceived climate change capabilities across the global south and north using multi-analytics

This study measured the relationships between integrated sustainable curricula, generative artificial intelligence tool usage, climate change sensitivity, and climate change capabilities among higher education students across the Global South and North. To achieve this, data were collected from 486 students in Ethiopia, Pakistan, Turkey, China, and Finland using a convenience sampling approach and a five-point Likert scale. We used Partial Least Squares Structural Equation Modeling (PLS-SEM), fuzzy set Qualitative Comparative Analysis (fsQCA), and Artificial Neural Network (ANN) analytics to capture both linear and configurational patterns, offering a comprehensive view of the complex relationships among the study variables. The findings reveal that integrated sustainable curricula correlate directly, significantly, and positively with climate change capabilities (β = 0.312, t = 5.27, p < 0.001). This relationship explains 70.9% of the variance (R² = 0.709). Generative AI tool usage further amplifies these relationships. Moreover, climate change sensitivity plays a mediating role by strengthening the pathway from integrated sustainable curricula to climate change capabilities. These results highlight the potential of integrated sustainable curricula and climate change sensitivity to enhance climate change capabilities. Although ANN performed comparably with multiple linear regression, fsQCA showed that the presence of any single condition (integrated sustainable curricula, climate change sensitivity, or generative AI tool usage) was sufficient to explain high levels of climate change capabilities. To the authors’ knowledge, this study is the first to measure the moderated mediation among integrated sustainable curricula, generative AI tools, and climate change sensitivity in relation to climate change capabilities within Global South and North contexts, using PLS-SEM, fsQCA, and ANN analytics. Our study also provides implications for practitioners, such as university management, curriculum policymakers and teachers, along with future research directions.