Abstract:

The recent emergence of generative Artificial Intelligence (AI), especially models such as ChatGPT, is rapidly reshaping teaching–learning processes in university education. In the current context, AI offers clear advantages: immediate access to complex information, generation of examples tailored to students’ level, individualized support, and innovative tools to enhance writing skills and reading comprehension. Nevertheless, the use of AI in university education presents significant challenges, including competence gaps, issues of reliability and linguistic accuracy and poorly planned or rushed integration.

The aim of this interdisciplinary teaching proposal is to strengthen communicative soft skills in academic English and sector-specific agronomic vocabulary within a context provided by professors. The activity follows a Problem-Based Learning (PBL) approach: students select a frequent incident in greenhouse horticulture and draft an intervention protocol to address it. AI is used as a verification agent, not as a content generator; it adopts the role of a B1-level learner responsible for pointing out ambiguities or requesting advice when the steps alone are not sufficiently clear.

The expected outcomes include:
(1) strengthening writing skills and reading comprehension;
(2) consolidating technical vocabulary;
(3) improving simplicity and precision in language; and
(4) facilitating the transfer of academic English into real scenarios.

This proposal illustrates how AI could function as a teaching bridge between seemingly unrelated disciplines, promoting meaningful, contextualized learning in both fields and responding to current needs in the agri-food industry as well as in technical English teaching.

Keywords:

AI, Problem-Based Learning (PBL), Technical English, Agronomists.