A Study of the Impact of Generative Artificial Intelligence on the Teaching Process and Learning Outcomes of Interior Space Design Education in Chinese Universities = 생성형 인공지능이 중국 대학 실내공간디자인 교육의 교수 과정과 학습 성과에 미치는 영향 연구

다국어 초록 (Multilingual Abstract)

With the integration of Generative Artificial Intelligence （Gen-AI） into design education, its influence has expanded from tool-based assistance to teaching processes, learning outcomes, and curriculum evaluation. Taking interior space design education in Chinese universities as the research object, this study examines the impact of Gen-AI on teaching processes, learning outcomes, and teaching adaptability. Since interior space design emphasizes spatial organization, functional zoning, circulation development, scale judgment, and user experience, its educational value cannot be measured only by image generation efficiency. This study adopts literature review, Analytic Hierarchy Process （AHP）, teaching experiment, questionnaire survey, and interview methods. Based on literature review and expert discussion, three core dimensions are identified: teaching process optimization, learning outcome improvement, and teaching adaptability. An AHP evaluation system with nine indicators is then constructed and verified through judgments from eight experts, a teaching experiment involving 20 participants, 163 valid questionnaires, and interview data. The results show that learning outcome improvement has the highest weight at the criterion level, while spatial logic judgment ability ranks first at the indicator level. Gen-AI can improve concept generation, scheme comparison, and visual expression efficiency, but it cannot replace students’professional judgment of functional relationships, circulation organization, scale proportion, and spatial experience. Based on these findings, this study proposes a phased curriculum introduction path for Gen-AI and an evaluation framework for spatial logic judgment ability, aiming to provide references for interior space design curriculum reform.

국문 초록 (Abstract)

생성형 인공지능（Generative Artificial Intelligence, Gen-AI）이 디자인 교육에 도입되면서 그 영향은 도구적 보조를 넘어 교수 과정, 학습 성과 및 교육과정 평가의 영역으로 확장되고 있다. 본 연구는 중국 대학의 실내공간디자인 교육을 연구 대상으로 하여 Gen-AI가 교수 과정, 학습 성과 및 교육 적합성에 미치는 영향을 고찰하였다. 실내공간디자인은 공간 조직, 기능 구획, 동선 전개, 스케일 판단 및 사용자 경험을 중시하므로, 그 교육적 가치는 단순히 이미지 생성 효율만으로 평가될 수 없다.
본 연구는 문헌 연구, 계층분석법（Analytic Hierarchy Process, AHP）, 교육 실험, 설문조사 및 인터뷰 방법을 활용하였다. 문헌 고찰과 전문가 논의를 바탕으로 교수 과정 최적화, 학습 성과 향상, 교육 적합성이라는 세 가지 핵심 차원을 도출하였으며, 9개 지표로 구성된 AHP 평가 체계를 구축하였다. 이후 8명의 전문가 판단, 20명의 참여자를 대상으로 한 교육 실험, 163부의 유효 설문지 및 인터뷰 자료를 통해 연구 결과를 검증하였다.
연구 결과, 준거층에서는 학습 성과 향상이 가장 높은 가중치를 보였으며, 지표층에서는 공간 논리 판단 능력이 가장 높은 순위를 차지하였다. Gen-AI는 개념 생성, 대안 비교 및 시각적 표현의 효율을 높일 수 있지만, 기능 관계, 동선 조직, 스케일 비례 및 공간 경험에 대한 학생의 전문적 판단을 대체할 수는 없다. 이에 본 연구는 Gen-AI의 단계적 교육과정 도입 경로와 공간 논리 판단 능력 평가 프레임워크를 제안함으로써 실내공간디자인 교육과정 개편에 참고 자료를 제공하고자 한다.

목차 (Table of Contents)

• I. Introduction 1
• 1. Research Background 1
• 2. Research Objectives 6
• 3. Research Questions 7
• 4. Significance of the Study 8
• 5. Research Methods 10
• II. Literature Review 12
• 1. Research Status of Gen-AI and Design Education 13
• 2. The Influence of Gen-AI on the Teaching Process of Interior Space Design 17
• 3. The Influence of Gen-AI on Learning Outcomes in Interior Space Design 21
• 4. Disciplinary Characteristics of Interior Space Design Education and Its Differences from Other Design Fields 23
• 5. Limitations of Existing Research and the Research Focus of This Study 28
• 6. Chapter Summary 32
• III. Extraction of Core Dimensions of Gen-AI’s Influence on Interior Space Design Education 34
• 1. Research Approach for Dimension Extraction 34
• 2. Theoretical Basis and Confirmation Process of Dimension Extraction 36
• 3. Core Dimension One: Teaching Process Optimization 41
• 4. Core Dimension Two: Learning Outcome Improvement 43
• 5. Core Dimension Three: Teaching Adaptability 46
• 6. Relationships among the Three Core Dimensions 49
• 7. Chapter Summary 51
• IV. Research on Influencing Factors of Gen-AI in Interior Space Design Education 52
• 1. Research Approach and Analytical Framework 52
• 2. Construction of the Influencing Factor Indicator System 55
• 3. Expert Group Composition and Judgment Matrix Construction 58
• 4. AHP Weight Calculation and Consistency Test 66
• 5. Analysis of Influencing Factor Results 69
• 6. Chapter Summary 73
• V. Empirical Study of Gen-AI in Interior Space Design Education 76
• 1. Research Design and Empirical Approach 76
• 2. Teaching Experiment Design and Implementation Process 78
• 3. Evaluation Process of the Teaching Experiment 82
• 4. Analysis of Teaching Experiment Results 88
• 5. Questionnaire Survey Results and Likert Scale Analysis 97
• 6. Offline Interviews and Semi-Structured Expert Interview Analysis 104
• 7. Chapter Summary 113
• VI. Discussion 116
• 1. Discussion on the Mechanism of Gen-AI’s Influence on Interior Space Design Education 116
• 2. Advantages and Boundaries of Gen-AI in Interior Space Design Education 119
• 3. Professional Specificity of Gen-AI Intervention in Interior Space Design Education 123
• 4. Implications for Curriculum Reform in Interior Space Design 127
• 5. Research Limitations and Future Prospects 134
• VII. Conclusion 139
• References 145
• Appendix 148
• 국문초록 154