Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 오유란 | - |
| dc.contributor.author | Yang, Jiseon | - |
| dc.creator | Yang, Jiseon | - |
| dc.date.accessioned | 2026-02-23T16:32:08Z | - |
| dc.date.available | 2026-02-23T16:32:08Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.other | OAK-000000258594 | - |
| dc.identifier.uri | https://dcollection.ewha.ac.kr/common/orgView/000000258594 | en_US |
| dc.identifier.uri | https://dspace.ewha.ac.kr/handle/2015.oak/274294 | - |
| dc.description.abstract | Art appreciation has long been an integral part of human culture, and interest in museums has grown significantly. However, many visitors, especially non-experts, continue to struggle with engaging meaningfully with artworks. Traditional explanatory formats, such as wall texts and audio guides, provide valuable contextual information but remain one-directional and offer limited support for reflective thinking. Recent advances in AI have enabled the generation of detailed factual descriptions and interaction to some extent, yet the ways in which AI supports viewers' thinking and immersion during the art appreciation process have not been sufficiently explored. This study addresses the gap by combining Feldman’ s four-stage art critique framework(description, analysis, interpretation, and judgement) with an AI-driven interactive system designed to guide non-expert viewers through a structured critique process. By integrating a large language model with Feldman’ s art critique , the system offers reflective, stage-specific guidance to help viewers articulate observations, deepen interpretive thinking, and enhance immersive engagement. This study aims to investigate whether AI can help viewers organize their thoughts and enhance their immersion while appreciating artworks. A user study with twelve adults who had prior museum experience was conducted, and the findings empirically demonstrate that AI, when combined with Feldman$'$s structured art critique, can foster deeper cognitive engagement and increase immersion in art appreciation.;예술작품 감상은 오랫동안 인간 문화의 중요한 부분을 차지해왔으며, 미술작품 감상에 대한 관심은 꾸준히 증가하고 있다. 하지만 대다수의 일반 관람자는 미술감상에서 작품과 의미있게 교감하고, 감상하는데 어려움을 겪고 있다. 전통적인 설명 형식인 팜플렛과 오디오 가이드는 유용한 배경 정보를 제공하지만, 일방적인 설명 전달이며, 감상자의 감상 견해를 정리하고 구성하는 데 한계가 있다. 최근 인공지능 기술의 발전으로, 상세한 사실적 설명과 어느 정도 상호작용이 가능한 미술 감상 및 분석 기술이 등장하고 있으나, AI가 감상 과정에서 관람자의 생각과 몰입을 돕는 방식에 대해서는 아직 충분히 탐구되지 않았다. 이에 본 연구에서는 최근 각광받고 있는 대규모언어모델과 Feldman의 4단계 미술비평 (묘사,분석,해석,판단)을 결합한 인공지능 시스템을 제작하여, AI가 관람자가 미술 감상 시 사고를 정리하고, 몰입도를 높여 감상 경험을 유의미하게 향상하는지를 확인하고자 했다. 미술전시 감상 경험이 있는 성인 12명에 대해 유저스터디를 진행하였으며, AI가 미술 감상 시 관람자의 사고를 심화시키고, 감상 몰입도를 향상시킬 수 있음을 실험적으로 입증하였다. | - |
| dc.description.tableofcontents | I. Introduction 1 II. Related Work 3 1. Art Analysis Technologies and Frameworks 3 2. Feldman Art Critique and Its Applications 3 3. Interactive Art Appreciation 4 III.Preliminary Study 6 IV. Method 8 1. Conditions 8 2. Participants 8 3. Appratus 8 3.1 Custom Dataset 8 3.2 RAG Configuration and GPT-4o-mini Function 9 3.3 Custom Webpage 11 3.4 Artwork Selection for User Study 13 4. Procedure 15 V. Data and Analysis 16 VI. Findings 17 1. Previous User Experience on Art Appreciation and AI tools 17 1.1 Challenge of Art Appreciation 17 1.2 User Perception on Supplementary Material of Art Exhibition 17 1.3 User Experience on AItools in Art Appreciation 18 2. The Effect of AI in Art Appreciation 18 2.1 Influence of AI on the Cognitive Journey 18 2.2 Over all Satisfaction 20 2.3 Immersion of Art Appreciation 20 2.4 Impact on Future Art Appreciation 21 2.5 Perceived Usefulness of AI Tools in Art Appreciation 21 2.6 Areas for Improvement and Reuse Intention 23 VII. Post Comparison Study 24 VIII. Discussion 28 1. AI's Potential to Facilitate Engagement in Art Appreciation 28 2. The Importance of Interactivity in the Process of Immersion and Internalization 29 3. Design Implication for AI Agents in Art Appreciation 29 3.1 Scaffolded AI Guidance for Cognitive Support 29 3.2 Providing Essential Background Information 30 3.3 AI as a Cognitive Collaborator 30 IX. Limitations 31 X. Conclusion 32 Bibliography 33 | - |
| dc.format | application/pdf | - |
| dc.format.extent | 4398656 bytes | - |
| dc.language | eng | - |
| dc.publisher | 이화여자대학교 대학원 | - |
| dc.subject | Art Interpretation Support, Cognitive Scaffolding, Human-Centered AI, Art Appreciation | - |
| dc.subject.ddc | 000 | - |
| dc.title | AI-Supported Art Criticism | - |
| dc.type | Master's Thesis | - |
| dc.title.subtitle | Enhancing Experience, Completeness, and Immersion through Feldman’s Framework | - |
| dc.format.page | vi, 38 p. | - |
| dc.identifier.thesisdegree | Master | - |
| dc.identifier.major | 대학원 인공지능·소프트웨어학부 | - |
| dc.date.awarded | 2026. 2 | - |