Distributed Agency in AI-Enhanced Cybersecurity Education: A Posthuman Instructional Design Framework

Abstract

This paper addresses a critical challenge facing cybersecurity educators: preparing students for AI-enhanced practice environments where effective action emerges from human-AI collaboration rather than individual expertise. Traditional instructional design frameworks assume human-centered learning processes that inadequately address distributed agency realities in contemporary cybersecurity operations. Drawing on Adams and Thompson’s posthuman inquiry methodology, this analysis develops a comprehensive pedagogical framework consisting of four principles: (1) Design for the Assemblage, Not the Individual, (2) Cultivate Relationality and Response-ability, (3) Embrace Emergence, Messiness, and Indeterminacy, and (4) Posthuman Assessment Approaches. The framework provides concrete instructional design implications, including strategies for configuring human-AI learning relations, integrating AI literacies across cognitive, civic, creative, and critical dimensions, and developing assemblage-aware cybersecurity case studies. These design implications bridge theoretical posthuman concepts with practical curriculum implementation through the lens of curriculum-as-lived rather than curriculum-as-plan. Preliminary implementation observations from an undergraduate cybersecurity ethics course demonstrate how posthuman-designed scenarios enable students to develop comfort with complexity and distributed analysis. Student reflections reveal progression from seeking singular solutions to embracing multiple valid perspectives, suggesting effective cultivation of human-AI collaborative competencies. The framework equips cybersecurity educators with both theoretical foundations and actionable design strategies for preparing students for distributed agency practice environments.