The Future of Education
Prompting Disciplinary Literacy: A Case Study of Gen AI as a Scaffold for Specialized Text Production in Environmental Studies
Francesca Ripamonti, University of Milan (Italy)
Abstract
This study explores the integration of Generative Artificial Intelligence (GenAI) as a pedagogical tool to support undergraduate students in the bachelor’s degree in Human Sciences of Environment, Landscape, and Territory in understanding and producing specialized disciplinary texts in English. Since the course syllabus combines geography, anthropology, environmental studies, and spatial planning, students often encounter difficulties with the linguistic and rhetorical conventions required for academic and professional communication.
To address these challenges, a semester-long intervention based on prompt engineering and iterative co-writing with GenAI tools (e.g., ChatGPT-4 and CoPilot 365) was implemented with 42 second-year students. Through scaffolded workshops, students learned to create discipline-informed prompts, analyse model texts, identify specialized lexicon and syntactic patterns, and critically revise AI-generated outputs.
Qualitative and quantitative analyses of writing samples, student reflections and assessed final tasks demonstrated notable improvements in terminology precision, argumentative organisation, genre awareness, and confidence in using academic English within disciplinary contexts. Enhanced metalinguistic awareness was reflected in students’ ability to apply appropriate rhetorical and lexico-grammatical strategies to disciplinary communication.
The findings suggest that GenAI can function as a collaborative mediator in disciplinary writing development, providing a replicable framework for integrating AI into EMI (English as a Medium of Instruction) contexts through prompt literacy and critical revision practices.
Keywords: Generative Artificial Intelligence (GenAI); EMI (English as a Medium of Instruction); Specialized literacy; Prompt engineering
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