Work

Examining Student Teachers’ Agency in an AI-Supported Learning Environment: Q Methodology Research

Year: 2025

Type: article

Abstract: Drawing on a socio-cognitive framework, we explored student teachers’ agency along intrapersonal, behavioral and environmental dimensions within the context of a classroom management course. The study investigated the enactment of student agency in an AI-supported learning environment using an innovative AI conversational chatbot whose outputs are based solely on curated course material. Using Q methodology, the analysis of 22 Q sorts revealed three distinct factors: (1) “I got this…just leave me alone” – self-reliant users confident in their abilities but exhibiting limited ethical awareness and reflective practices, (2) “Cipherbot is helpful , but…” – balanced users demonstrating intentional and ethical engagement, and (3) “A blind date with Cipherbot” – uncritical users heavily reliant on Cipherbot with diminished agency and criticality. The results are discussed in light of ongoing deliberations on the complexities of preparing student teachers for ethical and agentive GenAI use.

Source: International Journal of Artificial Intelligence in Education

DOI: 10.1007/s40593-025-00529-y

Authors: Youmen Chaaban, Song-Gyo Jung, Johanne Medina, Jinan Y. Azem, Joni Salminen, Bernard J. Jansen

Institutions: Qatar University, Hamad bin Khalifa University, University of Vaasa

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: hybrid

Estimated APC paid: $3,190