The Pedagogy of AI Mistakes: Fostering Higher-Order Thinking
For educators in higher education, this work offers a practical strategy to turn AI limitations into learning opportunities, though it is an incremental application of existing pedagogical concepts.
This paper proposes using AI errors as a pedagogical tool to foster higher-order thinking in a database design course, finding that structured interaction with AI mistakes supports metacognitive engagement and perceived AI literacy.
As generative AI becomes increasingly integrated into higher education, its frequent errors and hallucinations, often seen as limitations, offer a unique pedagogical opportunity. By framing AI as a ``learning companion'' whose imperfect outputs prompt analysis, evaluation, and reflection, we argue that instructors can engage students in the fundamental processes of higher-order thinking. This paper presents a design-oriented study in which an AI-integrated syllabus in a \textit{database design} course deliberately leverages AI's limitations to foster critical thinking and higher-order cognitive skills aligned with Bloom's taxonomy of learning. Using a mixed-methods approach, we examine how structured interaction with AI-generated errors supports metacognitive engagement, reinforces disciplinary rigor, and relates to students' perceived AI literacy and subject-matter competency.