Dr. Sharif Alghazo
Based on an appraisal theory framework, this study explores the use and functions of engagement strategies in human-written and AI-generated academic essays. The study analyses 80 essays (40 human-written and 40 AI-generated) for the use of Expansion and Contraction engagement strategies. The human-written essays were collected from the Louvain Corpus of Native English Essays (LOCNESS), which includes essays written by university-level native English writers, while the AI texts were generated by ChatGPT. Analysis shows that both Expansion and Contraction strategies occur more significantly in human-written texts than in AI-generated texts. Native English writers utilise a more significant proportion of Entertain markers, with a sensitive regard for alternative standpoints, and utilise Disclaim markers in actively opposing counterarguments. AI-generated texts, in contrast, utilise a high proportion of objective citing and hedging, with little objective use of strong Proclaim markers and a virtual lack of Concur dialogistic positions. There is a striking contrast in engagement functions, with humans utilising a more significant proportion of complex rhetoric and more profound argumentation supported through statistical analysis. The findings provide implications for educators and writing instructors aiming to enhance students’ argumentative skills and for developers of AI writing tools seeking to improve rhetorical complexity and engagement in generated texts
Keywords: Engagement strategies; academic writing; human-written; AI-generated; Appraisal Theory
