Abstract
In a taught master’s programme designed for sustainability professionals, students often encounter challenges in connecting academic theories to real-world applications. While frameworks like the Porter Hypothesis—which suggests that environmental regulations can drive innovation and competitiveness—are foundational, students sometimes find it difficult to see their practical relevance. Traditional teaching methods, such as instructor-provided case studies, often fail to engage students in critical analysis. To address this, I integrated generative AI (Gen AI) as a pedagogical tool to foster deeper understanding of the theory, critical thinking, and AI literacy.
After introducing the Porter Hypothesis, I designed an in-class exercise where students used Gen AI (e.g., ChatGPT) to identify case studies that purportedly supported the theory. Students shared their findings in small groups and selected one case to present to the class. The exercise then shifted to critical analysis: students evaluated whether the case truly supported the Porter Hypothesis, discussing both its alignment and limitations. For instance, while a case might highlight regulatory-driven innovation, students explored whether it also revealed trade-offs, such as increased short-term costs or uneven sectoral impacts. This process required students to interrogate AI-generated content, identify oversimplifications, and contextualize findings within the theory’s assumptions.
The exercise yielded three key outcomes. First, students developed higher-order analytical skills by critically evaluating AI-generated case studies. Second, students gained practical AI literacy, recognizing its limitations and the risks of incorporating its outputs directly. Third, the activity bridged theory and practice, enabling students to engage deeply with the Porter Hypothesis’s complexities and real-world applicability.
Post-exercise reflections revealed that students not only felt more confident in applying theoretical frameworks but also began generating their own questions about the theory. This self-directed inquiry extended beyond the original scope of the lesson, demonstrating the exercise’s effectiveness in fostering curiosity and critical engagement.
This initiative illustrates how Gen AI can be strategically integrated into sustainability education to enhance critical thinking, theory application, and AI literacy. By positioning students as active consumers and critics of AI-generated content, educators can cultivate both discipline-specific understanding and meta-cognitive skills. The approach underscores the value of Gen AI as a learning tool while emphasizing the importance of critical engagement and contextual analysis.
Presenter(s) / Author(s)
