.png){kind=icon}
.png){kind=icon}
Return
Digital mentor paradox: Transforming algorithmic anxiety into professional growth through AI-scaffolded pedagogical reasoning and identity
.png){kind=icon}
PRE
AI
S
H
DOI：10.1016/j.tate.2026.105526.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
The rapid integration of generative AI necessitates reconfiguring teacher preparation models. This research conceptualizes AI agents as digital mentors that instantiate Synthesized Qualitative Data strategies to foster professional growth. Integrating a cross-national experiment (N = 450), randomized controlled trial (N = 200), and field survey (N = 300), this study examines how AI support is associated with future teaching competence through pedagogical reasoning and digital identity. Results indicate that high-quality AI support predicts enhanced competence through deepened reasoning and consolidated identity. Crucially, the analysis reveals a digital mentor paradox: algorithmic anxiety amplifies, rather than attenuates, the positive association between support and developmental outcomes when structured scaffolding is present. Under adequate scaffolding, anxiety functions as a challenge stressor that is associated with enhanced engagement. These findings advance the theory of human-AI teaming, illustrating how psychological tensions may drive expertise development in the digital era.
Keywords:
Generative AI in teacher education
Pedagogical reasoning
Digital professional identity
Challenge-hindrance stressor framework
SQD strategies
Future teaching competence
Journal
IF:
3.9
Papers:
5.0K
Citations:
1.8W
Organization
Cited Papers