Competence, Confidence, and Conditions: A Qualitative Study of AI-Enhanced Teaching in Higher Education

• In Event: AERA Research in Progress Roundtable Session Four
  In Invited Roundtable: Research-in-Progress RT019 (Saturday)

Abstract

This study investigates how higher-education academics translate digital competence into digital confidence when enacting AI-enhanced formative assessment. Framed by DigCompEdu and TPACK (Redecker, 2017; Mishra & Koehler, 2006), self-efficacy (Bandura, 1997), and activity theory (Engeström, 2001), it addresses tensions flagged in recent syntheses on AI in HE—promise vs integrity, policy, and staff readiness (Batista, Mesquita & Carnaz, 2024; Lyanda, Owidi & Simiyu, 2024; Bancroft, Challen & Pearce, 2024). An interpretivist, two-site design (UK–UAE) combines interviews (≈25–30), think-aloud planning with optional AI use, and observation/stimulated recall. Reflexive thematic and framework analyses map efficacy sources to design choices and formative moves. Anticipated contributions include mechanism-level propositions and confidence-building CPD/policy principles; system findings are read through activity-system contradictions (Tlili et al., 2025).

Author

• Noshaba Anbreen, University of Birmingham - Dubai