Customising chatbots for writing development: Anticipating semiotic mediation with the theoretical architecture of systemic functional linguistics

This conceptual paper provides a social semiotic perspective on GenAI technologies in English for Academic Purposes contexts. It focuses on the process of customising AI chatbots to steer how an LLM responds. Through discussing two customised chatbots for Master's of Nursing Science students who are writing research proposals, the paper argues that the theoretical framework of Systemic Functional Linguistics is ideal for chatbot design. Examples use Cogniti software to show how EAP teachers can custom design a chatbot with minimal coding. These examples illustrate how SFL informs decisions about the scope of customised chatbots and the metalanguage within system messages. The discussion of system messages focuses on the challenge of creating consistency with how customised chatbots identify and describe the function of language features when generating feedback messages. The paper argues that this metalanguage should correspond to the metalanguage which students experience in face-to-face teaching and learning as well as online materials. Such continuity involves principled choices about where AI is integrated in teaching and learning sequences. It also involves clarity about the knowledge that students are expected to apply during ‘conversations’ with AI. In this regard, the paper draws attention to a social semiotic reading of Vygotsky's semiotic mediation. It argues that anticipating what is mediated is crucial for the process of customising a chatbot and making new knowledge visible to our students. • Relates semiotic mediation to the design of AI tools. • Applies a linguistic framework to design the scope of customised chatbots. • Applies a teaching and learning sequence for integrating AI tools. • Shows customed designed chatbots for writing research proposals. • Discusses continuity with metalanguage about research writing.