Call for Submissions – Special Issue on Youth Development in the Age of Generative AI

Journal of Research on Adolescence

• Youth’s trust in, attitudes toward, and knowledge about AI, as well as beliefs about what AI knows, whether AI can feel or want, what AI can and cannot do, and what role AI may play in their futures.

• AI literacy in the age of generative AI, including its definition, measurement, developmental variation, sources of knowledge, and associations with AI use, critical evaluation of AI-generated content, ethical decision-making, academic integrity, learning experiences, and developmental outcomes.

• Purposes and contexts of generative AI use among youth, including learning (school subject-specific or non-subject-specific), social connection and companionship, creative expression, entertainment, mental health support, physical health information-seeking, and other everyday uses.

• How generative AI use relates to learning, including school engagement, motivation, self-regulation, help-seeking, critical thinking, academic integrity, and school burnout.

• Generative AI and agency, including how young people decide when, why, and how to use generative AI, and how they monitor or limit its use.

• Human-AI interaction and co-agency, including how young people collaborate with generative AI; negotiate autonomy, control, and responsibility; communicate with AI through prompts and responses; interpret and evaluate AI-generated content; and perceive AI as a tool, tutor, collaborator, companion, or authority.

• Socio-relational experiences with generative AI, including anthropomorphism, parasocial or quasi-social relationships, perceived companionship, emotional support, and developmental differences in treating AI as a social agent, as well as how generative AI use relates to socio-emotional development, including loneliness, belonging, social connection, emotional adjustment, well-being, and mental health.

• Generative AI and relational development, including how AI changes friendships, romantic relationships, family relationships, relational learning, help-seeking, conflict resolution, communication, emotional reliance on AI, relational displacement, and the development of relational competencies across adolescence.

• Developmental mechanisms linking human-AI interactions to youth outcomes, including social learning, identity development, emotion regulation, autonomy, motivation, moral reasoning, executive functioning, as well as developmental differences in how adolescents perceive, interpret, and learn from interactions with generative AI.

• Family, school, peer, community, cultural, and policy contexts that shape young people’s access to, guidance around, and meaning-making about generative AI, including how these experiences may differ for young people from different socioeconomic, linguistic, cultural, and educational backgrounds.

• Measurement and methodological innovation to develop, adapt, or validate assessments, tools, or analytic approaches for studying youth development in generative AI-rich contexts, including the co-creation of designs with youth and other related stakeholders.

• Experimental and intervention studies examining how different generative AI tools, prompting strategies, instructional conditions, feedback types, or timing of AI use influence learning, motivation, engagement, agency, creativity, writing, critical thinking, well-being, or other developmental outcomes.

1. Tentative title;
2. Contact information for the corresponding author;
3. Names and affiliations of anticipated authors;
4. A brief statement on the study’s current status, including whether it will be ready for full manuscript submission by the deadline;
5. Abstract (500–1000 words of main text, up to 1 page of references, and 1–2 tables and/or figures; the main text should include sections on Background, Sample, Methods/Analyses, Results/Preliminary Findings, and Discussion/Conclusion).