Secondary Students as Co-Researchers on Generative AI in Learning: Empowering Youth to Shape National Education Policy
Year: 2025
Type: conference-paper
Abstract: As Generative Artificial Intelligence (GenAI) becomes an increasingly significant part of young people’s lives, educators are concerned about its impact on learning and attainment. However, understanding this impact requires more than simply studying young people’s behaviours or soliciting their opinions. It is essential to involve them actively as co-researchers, allowing their unique perspectives to shape the conversation around GenAI in schools. This project moves beyond seeing young people as research subjects, positioning them instead as co-designers, co-researchers, and potential influencers of national policy on GenAI in education. We recruited eight young people (aged 16–18) from three Scottish high schools to serve as Young People Co-Researchers (YPCR). Together, we explored their perspectives on GenAI at school, including their current usage, views on appropriate and inappropriate tasks for AI, and opinions on teachers’ use of AI and school policies. The YPCR organised and conducted semi-structured focus groups with 50 peers and collaboratively analysed the findings with adult researchers. Our results show that young people are cautiously optimistic about GenAI’s potential for learning and do not support outright bans in schools. They clearly distinguish between AI use for learning and in assessments, often expressing confusion over current policies and wishing for clearer guidance. The YPCR stated a strong desire to deepen their understanding of AI’s advantages and risks and for schools to teach responsible, effective use. Their insights are valuable for national policy development and for researchers aiming to enhance AI literacy, especially regarding data privacy and sustainability.
Authors: Colton Botta, Judy Robertson, Christina Mcmellon, Jamie Lawson, Jedidah Ajala, Sofia Lugo Gonzalez, Amina Hamidi, Nia Hicks, Kara McDonald, Ross John Paterson, Peter Scott, Jessie Tang
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4413846231