結合生成式人工智慧與自然語言處理技術之科學探究定題自動回饋鷹架開發與初步評估;Development and Preliminary Evaluation of an Automatic Feedback Scaffolding for Generating Questions During Scientific Inquiry:Using Generative Artificial Intelligence and Natural Language Processing Technologies

NCUIR > College of Electrical Engineering & Computer Science > Graduate Institute of Network Learning Technology > Electronic Thesis & Dissertation > Item 987654321/95624

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/95624

Title:	結合生成式人工智慧與自然語言處理技術之科學探究定題自動回饋鷹架開發與初步評估;Development and Preliminary Evaluation of an Automatic Feedback Scaffolding for Generating Questions During Scientific Inquiry:Using Generative Artificial Intelligence and Natural Language Processing Technologies
Authors:	蔡狄澄;Tsai, Ti-Cheng
Contributors:	網路學習科技研究所
Keywords:	科學探究;自然語言處理;自我導向學習;生成式人工智慧;scientific inquiry;natural language processing;self-directed learning;generative artificial intelligence
Date:	2024-07-23
Issue Date:	2024-10-09 17:06:32 (UTC+8)
Publisher:	國立中央大學
Abstract:	隨著台灣教育部自 2014 年實施的「十二年國民基本教育課程綱要總綱」強調全人教育及自主學習的重要性，高中已將自主學習納入課程，並規劃多種類型的活動，如探究與實作、專題研究及服務學習等，幫助學生解決問題、制定策略、創新思維及生成成果，培養靈活理解和終身學習技能。課綱前言指出，教育應致力於培養具有國際視野、自主學習能力、創新思維和社會責任感的全人。全球化和科技發展使自主學習成為21世紀生存的關鍵能力，並達成終生學習目標。在科學探究範疇，科學家進行探究專題時經歷定義問題、規劃步驟、執行計劃、自我監督及結果檢視等自主學習過程。類似學習模式能提高學生參與度、技能發展及真實環境應用能力。本研究利用自然語言處理技術開發教育聊天機器人，作為學生學習夥伴，提供個性化學習體驗和即時回饋，並透過問卷調查法針對43位高中生進行資料蒐集，評估學習者對系統的科技接受度及其功能與輔助工具的知覺有用性，並蒐集建議與回饋，以及透過問卷調查法針對3位高中自然科現場教師進行資料蒐集，評估「科學探究定題自動回饋鷹架」研究問題之適用性。研究結果顯示，學生以及高中自然科現場教師皆對「科學探究定題自動回饋鷹架」給予正向回饋，期望本研究能為未來研究或系統開發與研究提供參考。;Following the ′General Guidelines of the 12-Year Basic Education Curriculum′ implemented by Taiwan′s Ministry of Education in 2014, which stresses holistic education and autonomous learning, high schools have integrated self-directed learning into their curriculum. This integration involves activities such as inquiry-based projects, specialized research, and service learning, aimed at enhancing problem-solving, innovative thinking, and lifelong learning skills. The curriculum emphasizes developing individuals who are globally aware, capable of self-directed learning, innovative, and socially responsible. This study leverages natural language processing technology to develop an educational chatbot, serving as a learning companion to provide personalized experiences and immediate feedback for students. Data was collected via surveys from 43 high school students to evaluate their acceptance of the technology, the perceived usefulness of the system’s functions and tools, and to gather improvement suggestions. Additionally, feedback from three high school science teachers was collected to assess the effectiveness of the ′Automatic Feedback Scaffolding for Scientific Inquiry Questioning.′ Results indicate that both students and teachers provided positive feedback on the scaffolding tool, highlighting its potential to influence future research and development in educational systems.
Appears in Collections:	[Graduate Institute of Network Learning Technology] Electronic Thesis & Dissertation

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