Logo image
Student conceptions of generative artificial intelligence in early adolescence
Journal article   Open access   Peer reviewed

Student conceptions of generative artificial intelligence in early adolescence

Renee Morrison and Kathy A Mills
Education and Information Technologies , Vol.Advanced access
03-Jul-2026
pdf
s10639-026-14065-21.17 MBDownloadView
Published Version (Advanced Access) Open Access CC BY V4.0

Abstract

generative artificial intelligence adolescence critical discourse analysis machine learning student conceptions
This research combined critical discourse analysis (CDA), concordance analysis and thematic analysis to understand early adolescent students’ conceptions of generative artificial intelligence (GenAI). The rapid rise of GenAI has raised new questions for learning in all levels of education, given the capacity of ChatGPT and other GenAI applications (Gemini, Dall-E, MS Co-Pilot) to instantly produce text and images. The study analysed how GenAI was discursively conceptualised by early adolescents (Grades 7–8, ages 11–13 years) who were familiar with ChatGPT, while participating in qualitative focus groups in a secondary school. The focus group data was iteratively coded using thematic and concordance analysis identifying four repeated themes in the students’ discourse: (i) GenAI is easy to use, downplaying the revolutionary progress, (ii) GenAI and power: machine versus human responsibility, (iii) GenAI and epistemology: what machines and humans know, and (iv) GenAI and ontology: what is actual or real. CDA was also used to interpret students’ discursive construction of GenAI. The study provides insights into adolescent perspectives of the complexities of GenAI in their own terms. The findings are significant given the paucity of research that applies discursive analyses or concordance analysis to student conceptions of GenAI, and the increasing and inevitable influence of GenAI in everyday life.

Details

Metrics

1 Record Views
Logo image