Prompts to Practice: A Pedagogical Framework for Human-Centered AI Engagement
As generative AI evolves from an assistive tool to an increasingly autonomous system, higher education faces new challenges for teaching and learning. Emerging research describes the rise of the “ghost student,” who completes coursework without active participation, and the “cognitive debt” that accrues when productive struggle is outsourced to automated systems. These developments expose the limits of reactive, compliance-focused approaches. In response, this conceptual paper argues that purposeful, human-centered AI engagement offers a better path forward. Drawing on constructionist learning theory, we introduce the Instructional Model for Human-Centered Generative AI Engagement, a pedagogical framework designed to help faculty guide students in engaging with generative AI as a thinking partner rather than a shortcut. The model consists of five recursive phases: critical and ethical awareness, prompt literacy, AI-supported learning, reflection and revision, and independent application. Central to its implementation is the Prompt Literacy Cycle, nested within Phase Two, which guides students through iterative prompting, critical interpretation of LLM-generated outputs, and reflective revision. Together, these elements support a shift towards process-oriented assessment while fostering ethical awareness, metacognition, and intentional engagement with LLM-mediated knowledge construction.