PracticeDAPR: An AI-based Education-Supported System for Art Therapy
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초록

In this paper, we propose PracticeDAPR, an AI-based education-supported system for beginners in DAPR assessment practice. As professional identity is considered a pivotal goal in art therapy education, it is important to help beginners not to experience difficulties in professional identity development. Therefore, we designed the proposed system to provide the following three factors, which are closely associated with the professional identity formation of beginners in art therapy: (i) performance improvement, (ii) anxiety reduction, and (iii) self-efficacy enhancement. To this end, we adopt online peer-to-peer learning as the foundational learning approach. In addition, by introducing AI as a mentor, we let users not only interact with their peers but also experience AI assistance. The user study targeting graduate students in art therapy was conducted with both quantitative and qualitative methods. In general, users reported positive experiences with PracticeDAPR. The results of the structural equation model analysis showed that perceived usefulness is an important contributor to the three factors, highlighting the effectiveness of online peer-to-peer learning with the AI mentor. Furthermore, by deriving the results that intention to use can be promoted by performance improvement, it is demonstrated that PracticeDAPR can consistently help the development of the professional identity, which is not easily established in a short period of time. Discussion and implications are provided in relation to using AI and online peer-to-peer learning to support current art therapy education. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

키워드

Art therapyDAPR assessmentHuman-AI interactionOnline peer-to-peer learningProfessional identityPROFESSIONAL IDENTITYPEER ASSESSMENTSTUDENTSPERCEPTIONSCOUNSELORANXIETYIMPACT
제목
PracticeDAPR: An AI-based Education-Supported System for Art Therapy
저자
Yang, MigyeongPark, ChaeheeKang, JiwonKim, JiwonKim, TaeeunSong, HayeonHan, Jinyoung
DOI
10.1145/3711112
발행일
2025-05
유형
Article
저널명
Proceedings of the ACM on Human-Computer Interaction
9
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