- The paper demonstrates that integrating participatory design enables students and teachers to critically assess and shape generative AI usage through co-designed curricula.
- It employs a five-week case study using dyadic teacher-student partnerships, revealing mutual learning and culturally grounded curriculum development.
- The findings underscore that active student participation transforms learners from passive recipients into empowered agents of critical AI literacy.
Critical AI Literacy through Participatory Design: Integrating Generative AI in Secondary Education
Context and Motivation
The paper "Emergent Technology, Emergent Critique: Students and Teachers Developing Critical AI Literacy through Participatory Design around Generative AI" (2604.21995) addresses the problem of how generative AI tools are adopted and interrogated in K-12 educational settings. The authors focus specifically on critical AI literacy, conceptualized as encompassing not only technical competencies but also sociopolitical critique, ethical engagement, and participatory agency. With generative AI's rapid introduction into classrooms, the question of who decides how these technologies are integrated— and under what frameworks— becomes salient. The study positions participatory design (PD) as a methodological lever for democratizing this process, enabling both youth and educators to co-design curricula that foreground critical perspectives.
Theoretical Foundations
Critical AI literacy, as synthesized by Veldhuis et al. [veldhuis2025critical], is delineated across four interrelated dimensions: disrupting the commonplace (questioning taken-for-granted assumptions), considering multiple viewpoints (including those of marginalized communities), focusing on the sociopolitical (analyzing AI's entanglements with power and inequality), and taking action (enacting ethical and design-oriented interventions). The paper builds on situated learning theory [lave1991situated], positing that critical AI literacy emerges via social participation and collective sense-making. Recent empirical work has underscored the role of community, cultural context, and participatory empowerment in fostering critical orientations toward AI among youth [aleman2024data, ojedaramirez2024ailiteracy].
Methodology
A five-week after-school PD program was implemented with three 11th-grade Latinx students and three teachers at a southern California public high school. Each teacher-student dyad co-designed a curricular unit integrating generative AI into their respective subject areas (computer science, design, social studies). The sessions featured critical-ethical icebreakers, conceptual discussions, hands-on curriculum design, and reflective activities. Data were drawn from multi-modal sources: video/audio recordings, design artifacts, interviews, and researcher memos. A descriptive case study methodology [yin2018case] was employed to capture the process and outcomes of PD, organized using the critical AI literacy dimensions as an analytic lens.
Key Findings
Practices of Critical AI Literacy
Analysis of the focal PD sessions revealed three practices:
- Collectively Unsettling Assumptions about AI: The integration of ethical dilemmas in session openers facilitated active interrogation of AI’s real-world impacts. Students leveraged these experiences in curriculum proposals (e.g., fishbowl-style discussions) to unsettle peers' assumptions and anchor learning in sociotechnical consequences.
- Mutual Learning through Complementary Expertise: The dyadic PD structure enabled bidirectional transfer of expertise; student community knowledge was structurally necessary for designing meaningful AI learning experiences. This dynamic reframed students from informants to authoritative designers, with their lived experiences directly shaping curriculum content and focus.
- Grounding AI Critique in Cultural Knowledge and Creative Practice: Design tasks required explicit engagement with community conditions (e.g., food insecurity, resource distribution), leading to curricular units that embedded AI critique within culturally situated scenarios. Teachers and students jointly materialized critical perspectives through creative redesign, speculative futures, and applied systems thinking.
Implications
The study demonstrates that PD, when structured to make student knowledge necessary, enables genuine agency and shapes both the adoption and interrogation of generative AI tools in formal education contexts. The findings make two interrelated claims:
- Strategies for PD can be tailored to foster critical AI literacy, emphasizing collective unsettlement, reciprocal learning, and culturally grounded critique.
- Positioning youth as design protagonists is only actionable when structures— such as dyadic partnerships, community-situated tasks, and ethical framing— make their perspectives constitutive of curricular outcomes.
Numerical and Bold Claims
While the sample size is limited (n=6), the qualitative evidence supports strong assertions regarding the efficacy of dyadic PD in sustaining mutual learning and critical literacy. The paper asserts that students' knowledge is not merely supplementary but decisive in determining how AI tools are adopted and what aspects are interrogated.
Practical and Theoretical Implications
Practically, the study provides replicable strategies for integrating critical AI literacy in secondary classrooms via participatory curriculum co-design, with implications for districts introducing generative AI technologies. Theoretically, the work advances models of computational empowerment and transformative agency [iivari2024transformative, smith2024agenda], demonstrating how empowerment and critique are co-constituted in PD. The research reframes PD as not only a site for technology adoption but for critical literacy practice itself, contributing to the ongoing discourse on youth agency and protagonist positioning [iversen2017child, mahboob2022brave].
Future Directions
The results suggest scalability and adaptation across different sociocultural contexts. Further research is warranted to evaluate sustainability, broader applicability, and potential tensions in hierarchical school environments. Systematic investigation of PD structures that maximize mutual learning and critique may inform best practices for AI integration in K-12 education.
Conclusion
The paper provides a situated case demonstrating how participatory design with youth and educators produces critical AI literacy practices in the context of generative AI’s emergence in classrooms. The study evidences that when students are positioned as designers with genuine authority, they shape not only the adoption but the interrogation and contextualization of AI tools in their learning environments. These practices are emergent— forged through collective unsettlement, mutual learning, and culturally grounded critique— and substantiate the role of PD as a mechanism for operationalizing critical AI literacy in formal education.
