| 研究生: |
王偉倫 Wang, Wei-Lun |
|---|---|
| 論文名稱: |
AI 學伴?以鷹架理論引導學習者 - AI互動流程 AI Companion? Guiding Learners Through AI-Interaction Process via Scaffolding Theory |
| 指導教授: |
李怡慧
LEE, YI-HUI |
| 口試委員: |
彭志宏
PENG, CHIN-HUNG 陳蕙芬 CHEN, HUI-FEN |
| 學位類別: |
碩士
Master |
| 系所名稱: |
商學院 - 資訊管理學系 Department of Management Information System |
| 論文出版年: | 2026 |
| 畢業學年度: | 114 |
| 語文別: | 中文 |
| 論文頁數: | 59 |
| 中文關鍵詞: | 數位學習 、AI共生 、鷹架理論 、行動設計研究 |
| 外文關鍵詞: | Digital Learning, Human-AI Partnership, Scaffolding Theory, Action Design Research |
| 相關次數: | 點閱:7 下載:0 |
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隨著科技進步,數位學習工具日益多元,在數位學習轉型過程中,人工智慧技術的導入提供了即時反饋與客製化內容生成的功能,使數位學習環境從傳統的單向資訊傳遞,逐步轉向人類與AI協作的互動模式。然而,當前AI的普及卻成為一把雙面刃,學習者雖然能藉由AI提升效率,卻也陷入了學習自主性降低的危機,導致在學習中難以發揮獨立思考與創意。有鑑於此,本研究使用行動鷹架理論為基礎,並採用行動設計研究法,試圖重新思考在AI時代下,人類與學習者在學習上的平衡點,並產出適用於AI環境下的數位學習流程。本研究以閱讀學習為情境,透過理解參與者在探索、提煉與內化三個學習階段中的實際經驗,分析學習者所面臨的挫折與障礙,以及學習者與AI如何在互動過程中逐步形成兼顧效率與自主性的AI使用原則。綜整研究發現,本研究進一步提出AI輔助學習系統的設計原則,期能促進學習者與AI之間兼具互補性與自主性的共生關係。
With the advancement of technology, digital learning tools have become increasingly diverse. In the process of digital learning transformation, the integration of artificial intelligence (AI) has provided real-time feedback and customized content generation. This has gradually shifted the digital learning environment from traditional, one-way information transmission to an interactive, human-AI collaborative mode.
However, the current ubiquity of AI has become a double-edged sword. While learners can improve their efficiency through AI, they also face a crisis of reduced learning autonomy, which hinders their ability to exercise independent thinking and creativity during the learning process.
In light of this, this study utilizes Mobile Scaffolding Theory as its foundation and adopts Action Design Research (ADR) to rethink the balance between humans and learners in the AI era, aiming to generate design principles for digital learning platforms applicable to AI environments. This study identifies the obstacles learners encounter during the three stages of reading—exploration, refinement, and internalization—as well as the areas where AI can assist, the challenges learners can overcome on their own, and how the scaffolding guidance provides assistance throughout.
The design principles derived from this study aim to leverage appropriate external assistance and scaffolding guidance to lead learners in a digital environment away from improper dependence on AI toward a symbiotic relationship with AI that maintains autonomous construction. Ultimately, this research hopes to achieve a balance between deep learning and technology-assisted education.
聲明頁 II
謝辭 III
中文摘要 V
Abstract VI
目錄 VII
圖目錄 IX
表目錄 X
壹、緒論 1
第一節 研究背景 1
第二節 研究目的 2
第三節 研究貢獻 4
貳、文獻回顧 6
第一節 AI在學習上的自動化 6
第二節 AI在學習上的增能阻礙 7
第三節 鷹架理論 8
參、研究方法 12
第一節 研究設計 12
第二節 資料收集 25
第三節 分析方法 29
肆、研究分析與發現 31
第一節 探索的迷航:時間焦慮 31
第二節 提煉的迷惘:目的缺乏 35
第三節 內化的不安:答案模糊 38
第四節 平台迭代歷程 41
伍、討論 44
第一節 研究發現綜整 44
第二節 理論貢獻 46
第三節 實務貢獻 47
六、結論 49
參考文獻 50
附錄 54
附錄一 平台提示列表 54
附錄二 專家訪談原文範例 56
附錄三 半結構式訪談訪綱 59
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