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研究生: 劉婉馨
Lau Woan Shin
論文名稱: 臺灣大學生持續使用生成式 AI 意願的決定因素
Determinants of Continuance Intention to Use ChatGPT in Higher Education: A Study in Taiwan
指導教授: 周子銓
Tzu-Chuan Chou
口試委員: 周子銓
Tzu-Chuan Chou
黃政嘉
Jheng-Jia Huang
黃振皓
Chen-Hao Huang
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2023
畢業學年度: 112
語文別: 英文
論文頁數: 66
中文關鍵詞: 生成式人工智慧(GenAI)ChatGPT教育科技用後感知有用性信任意願結構方程模式
外文關鍵詞: Generative Artificial Intelligence (GenAI), ChatGPT, educational technology, post-usage usefulness, trusting intention, structural equation modeling
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本研究探討了生成式人工智慧(GenAI)對教育領域的影響,重點在於臺灣大學生對 ChatGPT 的看法和持續使用意願。 本研究採用定量方法,利用結構方程模式進行分析,探討績效預期和用後感知有用性對大學生對生成式 AI 的態度的影響,以及由此產生針對生成式 AI 的信任意願和持續使用意願。 結果表明,這些因素對學生的態度和持續使用生成式 AI 的意願有明顯的正面影響,並強調了教育機構有效整合 GenAI 的必要性。 本研究為教育領域人工智慧的廣泛討論做出了貢獻,為教育工作者、政策制定者和技術創新者在人工智慧驅動的教育進步背景下提供了有價值的見解。


This research examines the effects of Generative Artificial Intelligence (GenAI), with a special emphasis on ChatGPT, on the educational sector, highlighting the perceptions and ongoing usage intentions of university students in Taiwan. Adopting a quantitative approach, the study employs structural equation modeling to analyze survey data, exploring the influence of performance expectancy and post-usage usefulness on students' attitudes towards GenAI and their consequent trusting intention and continuance intention towards these technologies. The results reveal a significant positive impact of these factors on students' attitudes and their intention to persist with GenAI usage, emphasizing the necessity for educational institutions to integrate GenAI effectively. This study contributes to the broader conversation about AI in education, providing valuable insights for educators, policymakers, and technology innovators in the context of AI-driven educational advancements.

摘要 II Abstract III Acknowledgement IV Table of Contents V List of Symbols and Abbreviations VII List of Figures IX List of Tables X Chapter 1 1 INTRODUCTION 1 1.1. Background 1 1.2. Research Question 3 1.3. Research Scope 4 1.4. Research Purpose 5 Chapter 2 6 LITERATURE REVIEW 6 2.1. Importance of GenAI in Higher Education 6 2.2. Students’ Views on GenAI in Learning 7 2.3. Students’ Attitudes and Experiences with AI 7 2.4. Acceptance of AI 8 2.5. Key Theories in AI Acceptance 8 2.6. Theoretical Foundations 9 2.6.1. Post-usage Usefulness 9 2.6.2. Positive Attitude 10 2.6.3. Trusting Intention 10 2.7. Challenges and Limitations of GenAI 10 Chapter 3 12 RESEARCH MODEL AND METHODS 12 3.1. Hypothesis Development and Research Model 12 3.1.1. Performance Expectancy 12 3.1.2. Post-usage Usefulness 14 3.1.3. Positive Attitude 15 3.1.4. Affective Attitude 15 3.1.5. Cognitive Attitude 16 3.1.6. Trusting Intention 17 3.2. Research Method 17 3.2.1. Measurement Instrument 17 3.2.2. Subject and Data Collection 20 3.2.3. Analytical Methods and Software 21 Chapter 4 22 DATA ANALYSIS AND FINDINGS 22 4.1. Demographic Characteristics 22 4.2. Measurement Model Assessment 23 4.2.1. Indicator Reliability 25 4.2.2. Construct Reliability 28 4.2.3. Construct Validity 28 4.2.4. Cross Loadings 30 4.3. Structural Model Assessment 31 4.3.1. Indicator Multicollinearity 32 4.3.2. Explanatory Power 32 4.3.3. Structural Effect Size 33 4.3.4. Predictive Power 34 4.4. Hypothesis Results (Direct Relationships) 35 Chapter 5 37 DISCUSSION AND CONCLUSION 37 5.1. Findings 37 5.2. Alternative Model and Interpretations 38 5.3. Research Contributions 40 5.3.1. Theoretical Implications 41 5.3.2. Managerial Implications 41 5.3.3. Implications and Challenges of GenAI 42 5.4. Limitations and Future Research 42 5.5. Conclusion 43 References 45 Appendix A. Measurement Items (English) 63 Appendix B. Measurement Items (Chinese) 65

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