結合生成式人工智慧與自然語言處理技術之合作科學探究想法收斂自動回饋鷹架開發與初步評估

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葉軒宏(Xuan-Hong Ye) 查詢紙本館藏

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網路學習科技研究所

論文名稱

結合生成式人工智慧與自然語言處理技術之合作科學探究想法收斂自動回饋鷹架開發與初步評估
(Development and Preliminary Evaluation of an Automatic Feedback Scaffolding for Idea Convergence in Collaborative Scientific Inquiry: Using Generative Artificial Intelligence and Natural Language Processing Techniques)

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至系統瀏覽論文 (2028-7-6以後開放)

摘要(中)

「合作探究學習」是強調學生共同參與問題解決、知識翻新和學習過程的模式。這種學習方式有助於培養學生的批判思維、溝通能力和合作技能，推動知識的共享和共建。教育部於 2018 年頒布了「十二年國民基本教育課程綱要」的自然科學領域課程綱要中提及到自然科學課程應引導學生經由探究、閱讀及實作等方式，習得科學探究能力、養成科學態度，以獲得對科學知識內容的理解與應用能力，可以發現「探究學習」所扮演的重要角色。同時，隨著近年人工智慧及「自然語言處理技術」的快速發展，人工智慧在各領域的應用越來越廣泛。其中，聊天機器人作為學習夥伴在教育中的應用也逐漸受到重視，在 AI 聊天機器人作為學習夥伴的背後，自然語言處理技術扮演了至關重要的角色。因此本研究結合了自然言處理技術，訓練出基於知識翻新任務的聊天機器人，幫助及引導學生進行「想法收斂」的過程，我們透過聊天機器人作為學習夥伴與學生進行互動，促進學生在合作探究學習上的知識翻新，以達成學生的反思和深入討論，進而提升探究學習的成效。本研究以台灣北部某具備知識翻新教學與科學探究教學豐富經驗之國小現場教師為對象，主要採用問卷調查法，評估本研究鷹架在合作科學探究學習想法收斂的適用性。對實驗後的問卷資料進行統計分析與討論，根據統計及分析的結果得以發現本研究鷹架在教學現場中具有實際成效。透過結果再進一步改善系統，使系統更加符合教學現場。

摘要(英)

"Collaborative inquiry-based learning" emphasizes students′ joint participation in problem-solving, knowledge innovation, and the learning process. This approach helps develop critical thinking, communication skills, and collaboration abilities, promoting knowledge sharing and co-construction. With the rapid development of artificial intelligence (AI) and natural language processing (NLP) technologies, AI applications have become increasingly widespread. The use of chatbots as learning partners in education has gained considerable attention, with NLP technology playing a crucial role. This study integrates NLP technology to develop a chatbot based on knowledge innovation tasks, aimed at assisting and guiding students through idea generation and convergence. By interacting with students, the chatbot facilitates knowledge innovation in collaborative inquiry-based learning, leading to reflection and in depth discussion, ultimately enhancing the effectiveness of inquiry-based learning. The study involved 56 fifth-grade students from an elementary school in northern Taiwan. A questionnaire survey method was used to evaluate the system′s perceived usefulness, ease of use, and willingness to use. Statistical analysis of the questionnaire data revealed positive responses from the students. Based on their suggestions and feedback, further improvements were made to the system to better suit classroom teaching needs.

關鍵字(中)

★ 生成式人工智慧
★ 自然語言處理
★ 知識翻新理論
★ 科學探究
★ 探究學習
★ 學習夥伴

關鍵字(英)

★ generative artificial intelligence (GAI)
★ natural language processing (NLP)
★ knowledge building
★ scientific inquiry
★ inquiry learning
★ learning companion

論文目次

摘要 I
ABSTRACT II
致謝 III
目錄 IV
表目錄 X
圖目錄 XI
第一章緒論 1
第一節研究背景與動機 1
第二節研究目的 3
一、開發基於「自然語言處理」技術的「想法收斂自動回饋鷹架」，並整合至「合作探究學習平台」 3
二、對已完成開發的「想法收斂自動回饋鷹架」進行初步評估 3
第三節研究問題 5
一、「合作科學探究想法收斂自動回饋鷹架」之自然語言模型成效為何？ 5
二、「合作科學探究想法收斂自動回饋鷹架」之教學現場實用性為何？ 5
第四節名詞解釋 6
一、科學探究（Scientific Inquiry） 6
二、知識翻新（Knowledge Building） 6
三、學習夥伴（Learning Companion） 6
四、自然語言處理（Natural Language Processing, NLP） 7
第五節研究範圍與限制 7
第二章文獻探討 8
第一節科學探究與探究學習 8
一、科學探究 8
二、探究的四個層次 8
三、探究學習 10
四、小結 10
第二節知識翻新理論 12
一、知識翻新理論 12
二、知識翻新的理論框架 12
三、想法收斂與 Promising Idea 15
四、Meta-Talk 在知識翻新中的應用 16
五、知識翻新教學的挑戰與前景 17
第三節學習夥伴 18
一、傳統聊天機器人 18
二、聊天機器人作為學習夥伴 18
三、聊天機器人作為學習夥伴與傳統聊天機器人的差異 18
四、學習夥伴的角色 19
五、小結 20
第三節自然語言處理 21
一、大型語言模型（Large Language Model, LLM） 21
二、預訓練語言模型 23
三、模型量化 27
四、LoRA 29
五、生成式人工智慧（GAI）與文本生成技術 33
六、文本相似度計算 36
七、向量檢索 38
八、檢索增強生成 40
九、自然語言生成在教育中的應用 43
十、小結 44
第四節相關系統介紹以及分析與比較 45
一、相關系統介紹 45
二、相關平台與工具之分析與比較 49
第五節總結 51
第三章系統設計與實作 52
第一節系統開發方式 52
一、系統開發人員架構 52
二、系統開發流程 53
第二節系統設計與規劃 55
一、系統範圍 55
二、系統功能模組 56
三、系統使用案例 59
四、系統使用流程 59
五、系統架構 60
第三節邏輯與資料處理接口實作 62
一、資料流流程規劃 62
二、後端 API 之設計與實作 63
三、資料庫設計 66
第四節自然語言處理實作 68
一、資料準備與前處理 68
二、訓練環境與軟硬體配置 72
三、向量相似度訓練實作 76
四、想法摘要訓練實作 78
五、探究方向生成訓練實作 82
第五節系統介面與功能 83
一、小組聊天室結合 AI 學伴 83
二、想法警示鷹架 84
三、想法摘要鷹架 85
四、探究方向鷹架 86
第六節系統配置 87
一、硬體設備與環境 87
二、軟體建置 87
三、使用環境建議 88
第四章研究方法 89
第一節研究對象 90
一、受測者基本資料 90
第二節研究流程 91
一、施測及評估階段 91
二、結果分析階段 91
第三節鷹架評估流程 92
一、資料蒐集與整理 92
二、評測資料生成 92
三、鷹架功能評測 93
第四節研究工具 94
一、ROUGE-SU9 自動化評估工具 94
二、學生對於「合作科學探究想法收斂自動回饋鷹架」之想法摘要摘要質量量表 94
三、教師對於「合作科學探究想法收斂自動回饋鷹架」之探究方向適用性比較五點量表 96
第五節資料收集與分析 97
一、資料收集 97
二、資料分析 97
第五章研究結果與討論 98
第一節「合作科學探究想法收斂自動回饋鷹架」之自然語言模型成效為何？ 98
一、「合作科學探究想法收斂自動回饋鷹架」之想法摘要模型成效為何？ 98
第二節「合作科學探究想法收斂自動回饋鷹架」之教學現場實用性為何？ 102
一、「合作科學探究想法收斂自動回饋鷹架」之探究方向生成適用性為何？ 102
第六章結論與建議 105
第一節研究結論 105
一、「合作科學探究想法收斂自動回饋鷹架」之自然語言模型在文本生成任務中具有一定能力 105
二、「合作科學探究想法收斂自動回饋鷹架」在教學現場中具有實際成效 105
第二節研究建議 107
一、鷹架功能改善建議 107
二、未來研究建議 107
參考文獻 109
附錄 116
附錄一「合作科學探究想法收斂自動回饋鷹架」之想法摘要模型摘要質量量表例題 116
附錄二教師對於「合作科學探究想法收斂自動回饋鷹架」之探究方向生成適用性比較五點量表例題 117

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指導教授

吳穎沺

審核日期

2024-7-23

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