1. NCCU Academic Hub
  2. Publications
  3. College of Informatics
  4. Theses
  5. Item

Publications-Theses

Article View/Open

Publication Export

Google ScholarTM

NCCU Library

Citation Infomation

Related Publications in TAIR

題名 探究使用者之合作傾向對其與ChatGPT完成協作任務的影響
Exploring the Impact of Users’ Cooperative Tendencies on the Completion of Collaboration Tasks with ChatGPT
作者 楊千萱
Yang, Chien-Hsuan
貢獻者 江玥慧
Chiang, Yueh-Hui
楊千萱
Yang, Chien-Hsuan
關鍵詞 ChatGPT
協作問題解決
合作傾向
概念地圖
ChatGPT
Collaborative Problem Solving(CPS)
Cooperative Tendency
Concept Map
日期 2024
上傳時間 4-Sep-2024 15:02:45 (UTC+8)
摘要 ChatGPT的出現讓許多人通過自然語言，就能產生各種形式的內容，以達成目標。但是它並非總能提供符合需求的資訊，為了瞭解使用者的合作能力與其在短時間內讓ChatGPT產生正確結果的能力之間有無關聯，本研究設計與ChatGPT協作任務的實驗，來探討使用者外在的協作能力、內在的合作傾向與最終成果的關聯性。 本研究於實驗中要求使用者不斷與ChatGPT討論，最後讓它繪製出一張程式碼概念圖。除此之外，藉由團隊合作量表來評估使用者的合作傾向，並採用CRESST 團隊開發的協作解決問題模型，使用內容分析從使用者與ChatGPT對話中，分析出最常使用的協作能力。最後將合作傾向、協作能力以及程式碼概念圖等資料，使用相關性分析來觀察彼此間的關聯性。 研究結果顯示，使用者更偏向使用「協調能力」，不經篩選直接採納ChatGPT的資訊，這也影響到最終的成品缺乏創意性與豐富性。同時也觀察到在合作中較傾向使用「協商」態度的使用者與ChatGPT會互為領導者，當使用者被領導時，會以較開放的方式去接收資訊，換使用者領導時則比較常指派任務或選擇最佳解決方案。另外，使用者分別採用不同的合作態度來處理ChatGPT給予的回饋，無論哪種合作傾向都與繪圖的部分成果呈正相關，這與本研究最初的假設「擅於合作的人，擅於使用ChatGPT」一致。
The emergence of ChatGPT has enabled many people to generate various forms of content to achieve their goals using natural language. However, it doesn't always provide information that meets the requirements. To understand if there's a correlation between users' collaborative abilities and their capacity to produce accurate results with ChatGPT in a short time, this study designed experiments involving collaborative tasks with ChatGPT to explore the relationship between users' external collaborative abilities, internal cooperative tendencies, and final outcomes. In the experiment, users were required to continuously discuss with ChatGPT, ultimately having it draw a program code concept map. Additionally, a teamwork scale was used to assess users' cooperative tendencies, and the CRESST team's collaborative problem-solving model was adopted to analyze the most frequently used collaborative skills in the dialogue between users and ChatGPT through content analysis. Finally, correlation analysis was used to observe the relationships among cooperative tendencies, collaborative abilities, and the program code concept map data. The research results show that users tend to use "coordination skills" more, directly adopting information from ChatGPT without filtering, which affects the final product's lack of creativity and richness. It was also observed that users who tend to use a "negotiation" attitude in collaboration take turns being leaders with ChatGPT. When users are led, they tend to receive information more openly, and when users lead, they more often assign tasks or choose the best solutions. Moreover, users adopt different cooperative attitudes to handle feedback from ChatGPT, and regardless of the type of cooperative tendency, it shows a positive correlation with some aspects of the drawing results. This is consistent with the study's initial hypothesis that "people who are good at cooperation are good at using ChatGPT."
參考文獻 [1] A. Azaria, “ChatGPT Usage and Limitations.,” hal-03913837, Israel, 2022. [2] C. V. Boxtel, J. V. D. Linden, E. Roelofs, & G. Erkens, “Collaborative Concept Mapping: Provoking and Supporting Meaningful Discourse,” Theory Into Practice 41(1),, p. 40–46, 2002. [3] D. Djukanovic &. C. Radoje, “Validation of Propensity to Cooperation Questionnaire,” Communication Strategies & Consulting d.o.o, 2022. [4] D. P. Ausubel, Educational psychology: a cognitive view, NewYork: Holt,Rinehart & Winston of Canada Ltd, 1968. [5] F. Hesse, E.Care, J.Buder, K. Sassenberg, & P. Griffin, “ A framework for teachable collaborative problem solving skills,” Assessment and teaching of 21st century skills, pp. 37-56, 2015. [6] H. E. Herl, G. K. W. K. Chung, & H. F. O’Neil, “The use of computer-based collaborative knowledge mapping to measure team processes and team outcomes,” Computers in Human Behavior, pp. 463-493, 1999. [7] H. F. O'Neil, S. H. Chuang, & G. K. W. K. Chung, “Issues in the Computer-Based Assessment of Collaborative Problem Solving,” National Center for Research on Evaluation, Standards, and Student Testing (CRESST), Los Angeles, 2004. [8] J. Roschelle &. S. D. Teasley, “The Construction of Shared Knowledge in Collaborative Problem Solving,” Computer Supported Collaborative Learning, Springer, Berlin, Heidelberg, 1995. [9] J. D. Novak &. D. B. Gowin, Learning how to learn, Cambridge University Press, 1984. [10] K. Cavdar & T. Temizel,“Analyzing the effects of the personality traits on the success of online collaborative groups,” Social and Behavioral Sciences 228, p. 383 – 389, 2016. [11] L. Wang, C. MacCann, X. Zhuang, O. L. Liu, & R. D. Roberts, “Assessing Teamwork and Collaboration in High School Students: A Multimethod Approach,” Canadian Journal of School Psychology, pp. 108-124, 2009. [12] OECD, “PISA 2015 Draft Collaborative Problem Solving Framework.,” OECD, 2013. [13] P. Dillenbourg, M. Baker, A. Blaye, & C. O'Malley, “The evolution of research on collaborative learning.,” Learning in Humans and Machine: Towards an interdisciplinary learning science, pp. 189-211, 1996. [14] P. P. Ray, “ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope,” Internet of Things and Cyber-Physical Systems, pp. 121-154, 2023. [15] P. K. Anita, A. Pasztor, & G.Molnar, “Measuring collaborative problem solving: research agenda and assessment instrument,” Interactive Learning Environments, pp. 1-21, 2021. [16] T. Panitz, “Collaborative versus Cooperative Learning: A Comparison of the Two Concepts Which Will Help Us Understand the Underlying Nature of Interactive Learning,” 1999. [17] T. Walle. &. J. E. Hannay, “Personality and the nature of collaboration in pair programming,” 3rd International Symposium on Empirical Software Engineering and Measurement, pp. 203-213, 2009. [18] 方朝郁, “概念構圖在國小自然與生活科技領域教學上的應用,” 教育研究, pp. 127-138, 2005. [19] 郭佳甄, “初探高一生在弱結構問題之協作問題解決能力和其協作互動歷程,” 臺灣師範大學, 2016.
描述 碩士
國立政治大學
資訊科學系
111753227
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0111753227
資料類型 thesis
dc.contributor.advisor 江玥慧zh_TW
dc.contributor.advisor Chiang, Yueh-Huien_US
dc.contributor.author (Authors) 楊千萱zh_TW
dc.contributor.author (Authors) Yang, Chien-Hsuanen_US
dc.creator (作者) 楊千萱zh_TW
dc.creator (作者) Yang, Chien-Hsuanen_US
dc.date (日期) 2024en_US
dc.date.accessioned 4-Sep-2024 15:02:45 (UTC+8)-
dc.date.available 4-Sep-2024 15:02:45 (UTC+8)-
dc.date.issued (上傳時間) 4-Sep-2024 15:02:45 (UTC+8)-
dc.identifier (Other Identifiers) G0111753227en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/153394-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學系zh_TW
dc.description (描述) 111753227zh_TW
dc.description.abstract (摘要) ChatGPT的出現讓許多人通過自然語言，就能產生各種形式的內容，以達成目標。但是它並非總能提供符合需求的資訊，為了瞭解使用者的合作能力與其在短時間內讓ChatGPT產生正確結果的能力之間有無關聯，本研究設計與ChatGPT協作任務的實驗，來探討使用者外在的協作能力、內在的合作傾向與最終成果的關聯性。 本研究於實驗中要求使用者不斷與ChatGPT討論，最後讓它繪製出一張程式碼概念圖。除此之外，藉由團隊合作量表來評估使用者的合作傾向，並採用CRESST 團隊開發的協作解決問題模型，使用內容分析從使用者與ChatGPT對話中，分析出最常使用的協作能力。最後將合作傾向、協作能力以及程式碼概念圖等資料，使用相關性分析來觀察彼此間的關聯性。 研究結果顯示，使用者更偏向使用「協調能力」，不經篩選直接採納ChatGPT的資訊，這也影響到最終的成品缺乏創意性與豐富性。同時也觀察到在合作中較傾向使用「協商」態度的使用者與ChatGPT會互為領導者，當使用者被領導時，會以較開放的方式去接收資訊，換使用者領導時則比較常指派任務或選擇最佳解決方案。另外，使用者分別採用不同的合作態度來處理ChatGPT給予的回饋，無論哪種合作傾向都與繪圖的部分成果呈正相關，這與本研究最初的假設「擅於合作的人，擅於使用ChatGPT」一致。zh_TW
dc.description.abstract (摘要) The emergence of ChatGPT has enabled many people to generate various forms of content to achieve their goals using natural language. However, it doesn't always provide information that meets the requirements. To understand if there's a correlation between users' collaborative abilities and their capacity to produce accurate results with ChatGPT in a short time, this study designed experiments involving collaborative tasks with ChatGPT to explore the relationship between users' external collaborative abilities, internal cooperative tendencies, and final outcomes. In the experiment, users were required to continuously discuss with ChatGPT, ultimately having it draw a program code concept map. Additionally, a teamwork scale was used to assess users' cooperative tendencies, and the CRESST team's collaborative problem-solving model was adopted to analyze the most frequently used collaborative skills in the dialogue between users and ChatGPT through content analysis. Finally, correlation analysis was used to observe the relationships among cooperative tendencies, collaborative abilities, and the program code concept map data. The research results show that users tend to use "coordination skills" more, directly adopting information from ChatGPT without filtering, which affects the final product's lack of creativity and richness. It was also observed that users who tend to use a "negotiation" attitude in collaboration take turns being leaders with ChatGPT. When users are led, they tend to receive information more openly, and when users lead, they more often assign tasks or choose the best solutions. Moreover, users adopt different cooperative attitudes to handle feedback from ChatGPT, and regardless of the type of cooperative tendency, it shows a positive correlation with some aspects of the drawing results. This is consistent with the study's initial hypothesis that "people who are good at cooperation are good at using ChatGPT."en_US
dc.description.tableofcontents 第一章 緒論 第一節 研究動機1 第二節 研究目的2 第三節 研究問題3 第二章 文獻回顧 第一節 協作學習與合作學習的差異4 第二節 協作問題解決5 第三節 合作傾向7 第四節 概念地圖9 第三章 研究方法與步驟 第一節 研究方法11 第二節 研究架構11 第三節 研究對象12 第四節 研究工具14 第五節 研究流程15 第六節 資料分析18 第四章 實驗結果 第一節 協作能力編碼21 第二節 合作傾向與協作能力的關係25 4-2-1 參與者自我認同合作傾向的回答情況25 4-2-2 合作傾向與協作能力的相關性分析27 第三節 概念圖的影響31 4-3-1 概念圖評分判斷31 4-3-2 概念圖與協作能力之相關性33 4-3-3 概念圖與合作傾向之相關性35 第四節 研究小結與討論36 4-4-1 研究小結36 4-4-2 討論36 第五章 結論與未來展望 第一節 結論40 第二節 研究限制與未來發展40 參考文獻 42 附錄A 44 附錄B 47 附錄C 48zh_TW
dc.format.extent 2787770 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0111753227en_US
dc.subject (關鍵詞) ChatGPTzh_TW
dc.subject (關鍵詞) 協作問題解決zh_TW
dc.subject (關鍵詞) 合作傾向zh_TW
dc.subject (關鍵詞) 概念地圖zh_TW
dc.subject (關鍵詞) ChatGPTen_US
dc.subject (關鍵詞) Collaborative Problem Solving(CPS)en_US
dc.subject (關鍵詞) Cooperative Tendencyen_US
dc.subject (關鍵詞) Concept Mapen_US
dc.title (題名) 探究使用者之合作傾向對其與ChatGPT完成協作任務的影響zh_TW
dc.title (題名) Exploring the Impact of Users’ Cooperative Tendencies on the Completion of Collaboration Tasks with ChatGPTen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) [1] A. Azaria, “ChatGPT Usage and Limitations.,” hal-03913837, Israel, 2022. [2] C. V. Boxtel, J. V. D. Linden, E. Roelofs, & G. Erkens, “Collaborative Concept Mapping: Provoking and Supporting Meaningful Discourse,” Theory Into Practice 41(1),, p. 40–46, 2002. [3] D. Djukanovic &. C. Radoje, “Validation of Propensity to Cooperation Questionnaire,” Communication Strategies & Consulting d.o.o, 2022. [4] D. P. Ausubel, Educational psychology: a cognitive view, NewYork: Holt,Rinehart & Winston of Canada Ltd, 1968. [5] F. Hesse, E.Care, J.Buder, K. Sassenberg, & P. Griffin, “ A framework for teachable collaborative problem solving skills,” Assessment and teaching of 21st century skills, pp. 37-56, 2015. [6] H. E. Herl, G. K. W. K. Chung, & H. F. O’Neil, “The use of computer-based collaborative knowledge mapping to measure team processes and team outcomes,” Computers in Human Behavior, pp. 463-493, 1999. [7] H. F. O'Neil, S. H. Chuang, & G. K. W. K. Chung, “Issues in the Computer-Based Assessment of Collaborative Problem Solving,” National Center for Research on Evaluation, Standards, and Student Testing (CRESST), Los Angeles, 2004. [8] J. Roschelle &. S. D. Teasley, “The Construction of Shared Knowledge in Collaborative Problem Solving,” Computer Supported Collaborative Learning, Springer, Berlin, Heidelberg, 1995. [9] J. D. Novak &. D. B. Gowin, Learning how to learn, Cambridge University Press, 1984. [10] K. Cavdar & T. Temizel,“Analyzing the effects of the personality traits on the success of online collaborative groups,” Social and Behavioral Sciences 228, p. 383 – 389, 2016. [11] L. Wang, C. MacCann, X. Zhuang, O. L. Liu, & R. D. Roberts, “Assessing Teamwork and Collaboration in High School Students: A Multimethod Approach,” Canadian Journal of School Psychology, pp. 108-124, 2009. [12] OECD, “PISA 2015 Draft Collaborative Problem Solving Framework.,” OECD, 2013. [13] P. Dillenbourg, M. Baker, A. Blaye, & C. O'Malley, “The evolution of research on collaborative learning.,” Learning in Humans and Machine: Towards an interdisciplinary learning science, pp. 189-211, 1996. [14] P. P. Ray, “ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope,” Internet of Things and Cyber-Physical Systems, pp. 121-154, 2023. [15] P. K. Anita, A. Pasztor, & G.Molnar, “Measuring collaborative problem solving: research agenda and assessment instrument,” Interactive Learning Environments, pp. 1-21, 2021. [16] T. Panitz, “Collaborative versus Cooperative Learning: A Comparison of the Two Concepts Which Will Help Us Understand the Underlying Nature of Interactive Learning,” 1999. [17] T. Walle. &. J. E. Hannay, “Personality and the nature of collaboration in pair programming,” 3rd International Symposium on Empirical Software Engineering and Measurement, pp. 203-213, 2009. [18] 方朝郁, “概念構圖在國小自然與生活科技領域教學上的應用,” 教育研究, pp. 127-138, 2005. [19] 郭佳甄, “初探高一生在弱結構問題之協作問題解決能力和其協作互動歷程,” 臺灣師範大學, 2016.zh_TW