臺灣博碩士論文加值系統

隨著人工智慧和數位媒體應用的迅速增長，教育工作者紛紛採用各種新技術進行教學。許多學者致力於研究這些技術，並將其應用於教學領域。許多研究顯示，將人工智慧融入教學或學習中，有助於提升學習成效、學習動機、學習參與度和創造力等。然而，在數位藝術教學中，生成式人工智慧的應用仍相對罕見，尤其是在學生創作自己的藝術作品方面。因此，本研究將探討大學生使用生成式人工智慧可能引發的學習焦慮，並研究運用學習鷹架解決這一問題的可行性。本研究將採用具有潛力的生成式人工智慧工具SinGAN，結合數位藝術課程，增強學生在數位藝術創作和人工智慧應用方面的技能和知識。。
本研究將運用學習鷹架於數位藝術課程，透過數位藝術課程與SinGAN深度學習的結合，將課程內容化分成三種SinGAN深度學習的功能應用，透過教學者運用學習鷹架於數位藝術課程，研究學生是否能有效降低學習焦慮，在製作藝術作品過程中是否能習得成功經驗，以提高學生的學習成效及學習參與度並能有一致性的學習情緒。並採用準實驗設計，對象為南部某大學學生共43人，實驗組以SinGAN深度學習與同儕鷹架來進行學習任務，控制組以SinGAN深度學習進行學習任務，比較兩組學生在「學習成效」、「學習焦慮」、「學習參與度」與「學習情緒」之前、後測成績的差異。運用統計量化分析方法：描述性統計、獨立樣本t檢定及ANCOVA進行分析，統計結果顯示，實驗組在學習成效、學習焦慮以及學習參與度中達到顯著差異，兩組學習情緒無顯著差異。

With the rapid growth of artificial intelligence and digital media applications, educators are increasingly adopting various new technologies for teaching. Many scholars are dedicated to researching these technologies and applying them in educational settings. Numerous studies have shown that integrating artificial intelligence into teaching or learning can enhance learning effectiveness, motivation, engagement, and creativity. However, the application of generative AI in digital art education remains relatively rare, especially in the context of students creating their own art projects. Therefore, this study aims to explore the learning anxiety that university students may experience when using generative AI and investigate the feasibility of using learning scaffolding to address this issue.

This study will apply learning scaffolding in digital art courses by integrating SinGAN deep learning. The course content will be divided into three functional applications of SinGAN deep learning. By using learning scaffolding in digital art courses, the study aims to investigate whether students can effectively reduce learning anxiety, gain successful experiences in the process of creating art, and thereby improve their learning outcomes and engagement while maintaining consistent learning emotions.

摘 要 i
誌 謝 iii
目 次 v
表目次 vii
圖目次 viii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的與問題 3
第三節 研究限制 4
第四節 論文架構 4
第二章 文獻探討 6
第一節 數位藝術教學 6
一、數位藝術教育與實踐 6
二、數位藝術教學與技術 7
第二節 生成式人工智慧 8
一、生成式對抗網路(GAN) 8
二、SinGAN 9
第三節 學習鷹架 10
一、同儕鷹架 10
第四節 學習焦慮 11
第三章 研究方法 12
第一節 研究流程架構 12
第二節 研究設計 13
第三節 實驗設計 19
第四節 研究工具 21
一、學習成效測驗 21
二、學習焦慮量表 21
三、學習參與度量表 22
四、學習情緒量表 22
第四章 實驗結果與分析 25
第一節 學習成效評估結果 25
第二節 學習焦慮評估結果 26
第三節 學習參與度評估結果 28
第四節 學習情緒評估結果 29
第五章 結論與未來展望 30
第一節 結論 30
第二節 研究貢獻與討論 32
第三節 未來展望與建議 34
參考文獻 35
附錄 41

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