§ 瀏覽學位論文書目資料
  
系統識別號 U0002-1806202517263300
DOI 10.6846/tku202500281
論文名稱(中文) 道德考量對大學生使用 ChatGPT 在學習應用中的接受度之探討
論文名稱(英文) Examining the Impact of Ethical Considerations on University Students' Acceptance of ChatGPT in Learning Applications
第三語言論文名稱
校院名稱 淡江大學
系所名稱(中文) 教育科技學系碩士班
系所名稱(英文) Department of Educational Technology
外國學位學校名稱
外國學位學院名稱
外國學位研究所名稱
學年度 113
學期 2
出版年 114
研究生(中文) 范茗茗
研究生(英文) Ming-Ming Fan
學號 613730067
學位類別 碩士
語言別 繁體中文
第二語言別
口試日期 2025-05-28
論文頁數 78頁
口試委員 指導教授 - 鍾志鴻(150014@o365.tku.edu.tw)
口試委員 - 卓美秀
口試委員 - 林逸農
關鍵字(中) ChatGPT
道德考量
MFQ-2
UTAUT
科技接受
關鍵字(英) ChatGPT
ethical considerations
MFQ-2
UTAUT
technology acceptance
第三語言關鍵字
學科別分類
中文摘要
研究探討德考量對大學生接受ChatGPT作為學習工具的影響。研究採用道德基礎問卷新版(MFQ-2)整合科技接受理論(UTAUT)為基礎,通過問卷調查收集數據,運用PLS-SEM進行分析。結果顯示,道德傾向顯著影響付出績效、預期績效與促成條件三項科技接受前因變數,其中促成條件與付出績效則對使用意圖具有顯著正向影響。社群影響與預期績效對使用意圖則未達顯著,顯示學生更重視實際操作與技術支援。研究結果支持將道德考量納入科技接受模型,並對教育現場在推動生成式 AI 應用時提供實務與理論參考。
英文摘要
This study investigates the impact of moral considerations on university students’ acceptance of ChatGPT as a learning tool. Drawing on the revised Moral Foundations Questionnaire (MFQ-2) and integrating the Unified Theory of Acceptance and Use of Technology (UTAUT), data were collected through a survey and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that moral considerations significantly influence three key antecedents of technology acceptance: effort expectancy, performance expectancy, and facilitating conditions. Among these, facilitating conditions and effort expectancy have a significant positive effect on behavioral intention to use ChatGPT, while performance expectancy and social influence do not show significant effects. This suggests that students place greater importance on hands-on experience and technical support than on perceived performance or peer opinions. The findings support the integration of ethical considerations into technology acceptance models and offer both theoretical and practical implications for promoting generative AI in educational settings.
第三語言摘要
論文目次
目錄
謝誌  i
中文摘要 ii
英文摘要 iii
目錄  iv
第一章 緒論 1
 第一節 研究背景與動機  1
 第二節 研究目的  4
 第三節 研究問題  5
 第四節 研究範圍與限制  6
 第五節 名詞解釋  8
第二章 文獻探討  13
 第一節 CHATGPT在學習上的應用 14
 第二節 AI幻覺 16
 第三節 資訊倫理  18
 第四節 道德考量  22
 第五節 新版道德基礎問卷(MFQ-2) 24
 第六節 整合科技接受理論(UTAUT) 26
第三章 研究方法  33
 第一節 研究架構  33
 第二節 資料處理與分析  37
 第三節 研究流程  39
 第四節 研究對象與抽樣工具  44
 第五節 研究工具 45
第四章 研究結果  47
 第一節 量測模型檢驗結果  47
 第二節 PLS - SEM分析結果 52
第五章 結論與討論 61
 第一節 研究結論 61
 第二節 研究討論 66
 第三節 研究建議 67
參考文獻 69
附錄 75

表次
表2-4-1資訊倫理研究初探……………………………………………………….19
表2-6-1 整合科技接受理論要素發展表…………………………………………27
表3-1-1 研究假設路徑對應表……………………………………………………36
表4-1-1 信度和區聚效度的檢驗結果……………………………………………49
表4-1-2 區辨效度的檢驗結果…………………………………………………….51
表4-2-1 主要假設的路徑係數(β)、T值及P值 …………………….………….55
表4-2-2 模型對內生變數的解釋力檢驗結果…………………………….……...58

圖片目錄
圖2-6-1 UTAUT理論架構圖 …………………………………………………….31
圖3-1-1 研究架構圖……..……………………………………………………...….35
圖3-3-1 研究流程圖……..…………………………………...…………………….40
圖4-2-1 本研究的全部樣本結構模型研究架構圖……..………………...……….54

參考文獻
中文文獻
朱家榮. (2010). 資訊倫理研究初探. 臺灣圖書館管理季刊, 6(1), 1-15. https://tpl.ncl.edu.tw/NclService/JournalContentDetail?SysId=A10002010
杜承潔. (2015). 探討使用者對行動通訊軟體之分享行為—以LINE為例 (碩士論文, 國立屏東大學). 國家圖書館臺灣博碩士論文知識加值系統. https://hdl.handle.net/11296/7tks3p
孫淑真. (2017). 影響中高齡者使用醫院網路掛號系統意向之研究 (碩士論文, 南華大學). 國家圖書館臺灣博碩士論文知識加值系統. https://hdl.handle.net/11296/phju64
施懿珊. (2007). 國小高年級學生資訊倫理數位教材之設計與發展(碩士論文, 淡江大學). 國家圖書館臺灣博碩士論文知識加值系統. https://hdl.handle.net/11296/hjc2e9
莊道明. (1997). 建構資訊社會的新秩序—資訊倫理. 國家政策(動態分析)雙週刊, 175, 11-12.
董正隆. (2024). AI 幻覺是什麼? iSuperman. 取自 https://www.isuperman.tw/ai%E5%B9%BB%E8%A6%BA%E6%98%AF%E4%BB%80%E9%BA%BC%EF%BC%9F/
劉世南(2025)。後抄襲時代:人工智慧與神經技術時代的跨學科倫理與誠信。中華文化總會觀點。
https://opinion.cw.com.tw/blog/profile/575/article/16846

英文文獻
Alharbi, S., & Alyahya, S. (2020). Factors affecting the acceptance of integrated electronic personal health records in Saudi Arabia: The impact of e-health literacy. Journal of Infection and Public Health, 13(12), 2047-2054. https://pubmed.ncbi.nlm.nih.gov/33249857
Borji, A. (2023). A Categorical Archive of ChatGPT Failures (arXiv:2302.03494). arXiv. 
https://doi.org/10.48550/arXiv.2302.03494
Bowman, E. (2022, December 19). A new AI chatbot might do your homework for you. But it's still not an A+ student. NPR. https://www.npr.org/2022/12/19/1143912956/chatgpt-ai-chatbot-homework-academia
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2023). Chatting and cheating: Ensuring academic integrity in the era of ChatGPT. Innovations in Education and Teaching International. https://doi.org/10.1080/14703297.2023.2190148
Dogruyol, B., Velioglu, İ., Bayrak, F. et al. (2024) Validation of the moral foundations questionnaire-2 in the Turkish context: exploring its relationship with moral behavior. Curr Psychol 43, 24438–24452.
 https://doi.org/10.1007/s12144-024-06097-z
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.). SAGE Publications. https://eli.johogo.com/Class/CCU/SEM/_A%20Primer%20on%20Partial%20Least%20Squares%20Structural%20Equation%20Modeling_Hair.pdf
Hatherley, R., & Hatherley, J. (2019). The promise and perils of AI in medicine. International Journal of Chinese & Comparative Philosophy of Medicine, 17(2), 79-109. https://doi.org/10.24112/ijccpm.171678
Graham, J., Nosek, B. A., Haidt, J., Iyer, R., Koleva, S., & Ditto, P. H. (2011).
Mapping the moral domain. Journal of Personality and Social Psychology, 
101(2), 366–385. https://doi.org/10.1037/a0021847
Kasneci, E., Sessler, K., Betschart, S., Widenka, T., & Kasneci, G.
(2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274.
https://doi.org/10.1016/j.lindif.2023.102274
Krontiris, I., et al. (2020). Autonomous Vehicles: Data Protection and Ethical Considerations. CSCS '20, December 2, 2020, Feldkirchen, Germany. https://doi.org/10.1145/3385958.3430481
Kossen, J., Farquhar, S., Kuhn, L., & Gal, Y. (2024). Detecting hallucinations in large language models using semantic entropy. Nature, 630(8017), 625-630. https://doi.org/10.1038/s41586-024-07421-0
Li, H. (2022). The acceptance of artificial intelligence in healthcare: The roles of expected utility and usability. BMC Medical Informatics and Decision Making, 22(1). https://doi.org/10.3389/fmed.2022.990604
Luan, H., Tsai, Y. S., & Chai, C. S. (2023). AI literacy in education: A systematic review of empirical research from 2011 to 2022. Computers & Education: Artificial Intelligence, 4, 100136. https://doi.org/10.1016/j.caeai.2023.100136
Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? The Journal of Academic Librarianship, 49(1), 102-120. http://dx.doi.org/10.2139/ssrn.4333415
Meindl, P., Iyer, R., & Graham, J. (2019). Distributive justice beliefs are guided by whether people think the ultimate goal of society is well-being or power. Basic and Applied Social Psychology, 41(6), 359–385.
 https://doi.org/10.1080/01973533.2019.1663524
Nguyen, Q. A., & Tran, B. X. (2021). Does knowledge matter? The role of m-Health literacy to the acceptance of m-Health applications. Journal of Science & Technology, University of Danang, 20(1), 52-57. https://doi.org/10.31130/jst-ud2021-444
Oluwajana, D., & Adebayo, A. (2021). Does the student's perspective on multimodal literacy influence their behavioural intention to use collaborative computer-based learning? Education and Information Technologies, 26(5), 5473-5490. https://www.proquest.com/docview/2565287344?pq-origsite=gscholar&fromopenview=true&sourcetype=Scholarly%20Journals
Perkins, M. (2023). Academic integrity considerations of AI large language models in the post-pandemic era: ChatGPT and beyond. Journal of University Teaching & Learning Practice, 20(2), Article 07. https://ro.uow.edu.au/jutlp/vol20/iss2/07
Sparrow, R., & Hatherley, J. (2019). The Promise and Perils of AI in Medicine, 17(2), 79-109. https://doi.org/10.24112/ijccpm.171678
Tang, X., Hanif, M. S., Haider, N., Rizwan, A., & Khurshid, A. (2024). From Friends to Feedback: Effect of Social Influence on Mobile Shopping in the Post-COVID Era. Sustainability, 16(12), 5134. https://doi.org/10.3390/su16125134. 
Vărzaru, A. A., Bocean, C. G., & Mangra, M. G. (2022). Assessing Users’ Behavior on the Adoption of Digital Technologies in Management and Accounting Information Systems. Electronics, 11(21), 3613. https://doi.org/10.3390/electronics11213613
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
Wang, Y., Huang, Y., & Chen, H. (2022). The impact of expected utility and usability on the acceptance of hybrid teaching systems. Postdigital Science and Education. https://rdcu.be/dXawb
Winkelkotte, F., Fobi, D., Möhring, M., & Wild, S. (2025). Testing psychometrics of the moral foundations questionnaire-2 (mfq-2) among pre-service teachers in ghana. Current Psychology: A Journal for Diverse Perspectives on Diverse Psychological Issues. Advance online publication. https://doi.org/10.1007/s12144-025-07630-4
Yılmaz, R. (2023). The effect of digital literacy on technology acceptance: An evaluation on administrative staff in higher education. Journal of Librarianship and Information Science. https://doi.org/10.1177/01655515231160028
Zhao, A. (2024). Embracing ChatGPT for Medical Education: Exploring Its Impact on Doctors and Medical Students. JMIR Medical Education, 10, e52483. https://doi.org/10.2196/52483

 
論文全文使用權限
國家圖書館
同意無償授權國家圖書館,書目與全文電子檔於繳交授權書後, 於網際網路立即公開
校內
校內紙本論文立即公開
同意電子論文全文授權校園內公開
校內電子論文立即公開
校外
同意授權予資料庫廠商
校外電子論文立即公開

如有問題,歡迎洽詢!
圖書館數位資訊組 (02)2621-5656 轉 2487 或 來信