Abstract
Generative AI is rapidly reshaping how students learn, communicate, and prepare for professional life, yet its integration into higher education remains uneven and under-examined—particularly in relation to visual literacy. This collaborative project investigates how generative AI can be embedded within university teaching to develop students’ ability to create, interpret, and critically evaluate visual communication about climate change, a competency increasingly valued across environmental disciplines.
The study adopts a mixed-methods design centred on two undergraduate courses with contrasting disciplinary orientations: an environmental science course for science students and a language-of-sustainability course for art students. Both cohorts received shared instructional content covering the science of climate change and the linguistics of climate communication, establishing a common knowledge base from which to explore how disciplinary background shapes engagement with AI-assisted visual tasks.
The pedagogical sequence was intentionally iterative. Students in both courses completed three linked stages: first, a pre-survey capturing their baseline understanding of climate change and prior AI usage; second, a draft infographic accompanied by a survey documenting how AI was used during the drafting process; and third, a revised final infographic with a corresponding survey on AI use during revision. The infographic prompt asked students to communicate the single most important thing they would want everyone to understand about Earth’s climate, human impact on it, or how we talk about it. This design enables us to trace how students’ AI strategies, climate understanding, and visual reasoning evolve across drafts and differ across disciplines.
To contextualise the curricular goals within workforce expectations, we also conducted interviews with environmental professionals. Findings indicate that AI use in industry is common but uneven, centred on practical tasks such as research, report drafting, and visual content creation. Professionals anticipate that AI competency will become increasingly important in graduate recruitment, reinforcing the need for universities to prepare students accordingly.
We received 46 students (31 science, 15 art) response to the pre-survey. Ongoing analysis will examine how disciplinary background relates to students’ perceived understanding of climate change, their attitudes toward AI, and the quality and communication effectiveness of their infographic products. By linking student background, AI usage patterns, and visual outputs across two iterative stages, this project offers practical insights into designing cross-disciplinary learning activities that harness generative AI to build visual literacy for the future environmental workforce.