Learning from AI's pen: Using corpus data as a lens to promote attention and learning from patterns of language in AI-generated text

While AI technologies have transformed the processes adopted by language learners to produce and revise academic writing, more approaches are needed to promote understanding of text patterns and linguistic features of GenAI texts so learners can engage with language skill development and maintain control as novice authors of academic texts. The current study presents a fusion of corpus methods (embedded in a free Windows/macOS tool), facilitating researchers, teachers and students in hands-on, interactive, comparative analysis of essays created by students and essays on the same topics created through GenAI tools. To demonstrate the feasibility of the approach, we analysed 2003 university level argumentative essays on 26 topics, alongside 546 AI-generated essays (21 essays per topic), focussing on four essays from one randomly selected topic for exemplification. The methods highlight notable strengths of AI-generated texts, including broad vocabulary profiles, balance between maintaining lexical focus and avoiding repetition, and rich collocational relations. By visually representing the roles of vocabulary items in text-level contexts, the tool provides a new approach for English for Academic Purposes teachers and students to engage with data patterns in the texts they have produced with and without GenAI, with potential to aid detection, identification, reflection and ultimately production.