AI feedback-seeking and learning engagement in art education: psychological antecedents and reflective mechanisms

Generative artificial intelligence provides students with a feedback source that differs from traditional teacher and peer interaction, yet limited research has explained why students actively seek feedback from AI or how such feedback-seeking is associated with subsequent learning engagement. Drawing on transactional stress and coping theory and social cognitive theory, this study examined the psychological antecedents and reflective mechanisms of AI feedback-seeking in art education.

Two complementary studies were conducted. Study 1 utilized survey data from 315 higher education students with recent experience in art learning and generative AI use to investigate whether a fear of negative evaluation was associated with AI feedback-seeking through interpersonal help-seeking avoidance. Study 2 involved 172 students who completed a standardized AI-supported art-creation task. It examined whether AI feedback-seeking was associated with task behavioral engagement through reflective learning and whether openness strengthened this indirect relationship. The proposed relationships were tested using partial least squares structural equation modeling.

In Study 1, fear of negative evaluation was positively associated with interpersonal help-seeking avoidance, which in turn was associated with greater AI feedback-seeking. The indirect association between fear of negative evaluation and AI feedback-seeking through interpersonal help-seeking avoidance was significant, whereas the direct association was not. In Study 2, AI feedback-seeking was positively associated with reflective learning, which was further associated with task behavioral engagement. Reflective learning significantly mediated the association between AI feedback-seeking and task behavioral engagement. Openness strengthened both the association between AI feedback-seeking and reflective learning and the corresponding indirect association with task behavioral engagement.

The findings indicate that avoiding interpersonal help does not necessarily reflect withdrawal from feedback. Under evaluation concerns, students may instead select AI as a feedback source involving less interpersonal exposure. However, seeking AI feedback is not uniformly associated with stronger learning engagement; its relevance depends on whether students reflect on the information obtained and remain receptive to alternative perspectives. The study positions AI feedback-seeking as both a coping-oriented form of feedback-source selection and a learner-initiated resource for reflective engagement in art education.