Speaker
Description
The rapid integration of GenAI presents a fundamental question: how can educators cultivate genuine critical thinking when students increasingly use AI to generate contents? This paper reframes that challenge as a pedagogical opportunity, arguing that prompt engineering and AI literacy - when embedded as classroom tasks - can serve as powerful tools for developing higher-order thinking skills. Drawing on a case study of two undergraduate public speaking classes, the author's reflective teaching practice, and a narrative literature review including critical thinking frameworks, AI literacy, and oral production pedagogy, this paper identifies three instructional strategies: prompt engineering as a metalinguistic task, in which students actively compare and evaluate AI-generated content; structured AI literacy activities that train students to acknowlege the limitations of AI output; and guided delivery instruction, in which students develop vocal variety, strategic pausing, and intonation control through targeted practice and critical comparison of their own performances with AI-narrated speech. Analysis of classroom data and teaching reflections reveals that students who engaged in critical interactions with AI output - rather than passive consumption - demonstrated stronger argumentative ability, greater willingness to challenge AI-generated claims, and increased ownership of their spoken discourse. By learning to write better prompts, students grew more conscious of language nuances and became better at evaluating content, while the AI-narration contrast activity heightened students' awareness of voice as a meaning-making resource. These findings provide practical implications for ELT curriculum design, task sequencing, and teacher professional development.
Keywords: critical thinking, prompt engineering, AI literacy, public speaking
