Presentation Schedule
AI-Mediated Feedback in Education: Teachers’ Baseline Perceptions, Opportunities, and Professional Barriers in a Research-Action Context (108678)
Session Chair: Danielle Pontes
Tuesday, 16 June 2026 13:55
Session: Session 2
Room: Room 108 (1F)
Presentation Type:Oral Presentation
The integration of Artificial Intelligence (AI) in education is progressively reshaping feedback processes, shifting them from episodic corrective acts to continuous, data-informed, and dialogic mechanisms embedded within learning environments. Building on the Conversational Framework and feedback literacy literature, this study investigates teachers’ baseline perceptions of AI-mediated feedback within a research-action professional development pathway. The dataset includes 363 teachers who completed a structured questionnaire grounded in the distinction between beliefs, perceived opportunities, and perceived barriers related to feedback and AI. Descriptive and inferential analyses were conducted; Results show a pre-existing culture of formative feedback. Perceived opportunities of AI for feedback are moderately high particularly in relation to learning analytics and immediate feedback, while perceived effectiveness is evaluated more cautiously. Notably, the need for professional training emerges as a dominant barrier, whereas ethical-normative concerns appear as a distinct and non-overlapping dimension.
Innovative findings indicate that teachers do not display technophobic resistance; rather, they adopt a posture of reflective professional caution. Cluster analysis identifies a majority profile of “open but cautious” teachers who recognise AI’s feedback potential but remain uncertain about its pedagogical effectiveness. The findings further reveal a distinction between perceived technological capability and educational legitimacy, suggesting that teachers evaluate as a pedagogical actor. These results indicate that the integration of AI into feedback practices is mediated more by professional agency and pedagogical judgement than by technological access alone. Feedback therefore emerges as a privileged lens through which teachers negotiate the educational legitimacy of AI.
Authors:
Simona Michelon, Università di Reggio Emilia, Italy
About the Presenter(s)
Simona Michelon is an economics teacher and a PhD Candidate in Learning Sciences and Digital Technologies and education policy practitioner working at the intersection of digital transformation and lifelong learning systems.
Connect on Linkedin
https://www.linkedin.com/in/simona-michelon-ba24a218/
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