Abstract
As generative AI transforms creative and professional workflows, higher education must adapt to equip students with the skills to harness these tools critically and ethically. This project investigates the integration of generative AI into university curricula to enhance visual literacy, with a focus on environmental disciplines. Through a mixed-methods approach, we (1) analyze perspectives from environmental professionals on AI’s role in recruiting graduates, (2) evaluate discipline-specific student engagement with AI for visual tasks (e.g., climate-themed infographic creation), and (3) develop a framework for cross-disciplinary AI integration in teaching and learning. We will present findings from interviews with environmental professionals, revealing current industry practices and expectations regarding AI proficiency. These insights will be complemented by student-generated data on AI usage patterns and challenges in visual projects. Based on preliminary industry feedback and emerging trends in AI education, we hypothesize that: (1) while AI demonstrates strong theoretical efficiency, its practical application in professional environments may fall short of expectations; (2) student engagement with AI tools will vary significantly across disciplines, though no clear patterns may yet emerge based on academic background; and (3) despite differing familiarity with AI, students will express strong interest in developing AI-enhanced visual problem-solving skills. This work contributes to the scholarship of teaching and learning by addressing a critical gap: preparing students to leverage AI for visual problem-solving in sustainability contexts. We will share actionable recommendations, student-generated examples (pending data collection), and tips for educators to replicate this approach in their fields.
Presenter(s) / Author(s)
