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作者姓名(中文):吳思賢
作者姓名(英文):Szu-Shien Wu
論文名稱(中文):從專利分析觀察人工智慧技術在教育的應用趨勢
論文名稱(外文):Looking at the Application Trend of Artificial Intelligence Technology in Education from Patent Analysis
指導教授姓名(中文):管中徽
盧希鵬
指導教授姓名(英文):Chung-Huei Kuan
Hsi-Peng Lu
口試委員姓名(中文):王俊傑
口試委員姓名(英文):CHUN-CHIEH WANG
學位類別:碩士
校院名稱:國立臺灣科技大學
系所名稱:管理學院MBA
學號:M10521212
出版年(民國):109
畢業學年度:108
學期:2
語文別:中文
論文頁數:76
中文關鍵詞:國際專利分類(IPC)專利分析人工智慧教育
外文關鍵詞:International Patent Classification (IPC)Patent AnalysisArtificial IntelligenceEducation
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本研究採用專利視角,觀察人工智慧技術在教育應用趨勢。從GPSS專利資料庫檢索259件美國專利,美國籍申請案佔八成,領先申請人是IBM,有59件申請案,其中71%是近十年申請案。主流的人工智慧技術是專家系統,但隨著人工智慧技術發展,國際分類號IPC還會有更細緻分類。本研究發現,AIED領域佈局有綜合模式與垂直模式,佔專利家族數75%。人工智慧在教育應用的技術趨勢,專家系統還是主流,早期專家系統是靜態,近五年專家系統是動態,知識庫可以隨著其他人工智慧分析資料進行動態調整。人工智慧技術在教育的應用場景趨勢有四項,學習程度預測、作業流程輔助、醫療推薦與醫療診斷預測與人工智慧訓練人工智慧。本研究發現AIED學術研究除了關注單一技術或多個演算法優化,也可以擴展兩個研究方向,多個人工智慧技術串接應用研究與人工智慧訓練人工智慧應用。
This study uses a patent perspective to observe the trend of artificial intelligence technology in education. Retrieving 259 U.S. patents from the GPSS patent database, American applications accounted for 80%. The leading applicant was IBM, with 59 applications, 71% of which were applications in the past ten years. The mainstream artificial intelligence technology is an expert system, but with the development of artificial intelligence technology, the international classification code IPC will have more detailed classification. This study found that the AIED field has an integrated model and a vertical model, accounting for 75% of patent families. The technical trend of artificial intelligence in education is that the expert system is still the mainstream. The early expert system is static, and the expert system is dynamic in the past five years. The knowledge base can be dynamically adjusted with other artificial intelligence analysis data. There are four trends in the application scenarios of artificial intelligence technology in education: learning level prediction, work process assistance, medical recommendation and medical diagnosis prediction, and artificial intelligence training artificial intelligence. This research finds that AIED academic research not only focuses on the optimization of a single technology or multiple algorithms, but can also expand two research directions, where multiple artificial intelligence technologies are connected in series with application research and artificial intelligence training artificial intelligence applications.
目錄
摘要...................................................................................................................................................I
Abstract..........................................................................................................................................II
致謝...............................................................................................................................................III
目錄................................................................................................................................................IV
圖表目錄......................................................................................................................................VI
第一章緒論....................................................................................................................................1
1.1研究背景與動機..................................................................................................................1
1.2論文架構...............................................................................................................................2
1.3論文預期貢獻......................................................................................................................3
第二章文獻探討...........................................................................................................................4
2.1人工智慧在教育應用研究...............................................................................................4
2.2文獻回顧小結......................................................................................................................7
第三章分析方法...........................................................................................................................8
3.1分析架構...............................................................................................................................8
3.2專利檢索程序與靜態分析.............................................................................................10
3.3趨勢分析、技術分析與個案分析................................................................................14
第四章研究樣本與數據分析..................................................................................................17
4.1研究樣本.............................................................................................................................17
4.3資料處理流程....................................................................................................................19
4.3.1靜態分析.......................................................................................................................19
4.3.2趨勢分析.......................................................................................................................19
4.3.3技術分析.......................................................................................................................20
4.3.4個案分析.......................................................................................................................20
第五章結果..................................................................................................................................21
5.1靜態分析.............................................................................................................................21
5.2趨勢分析.............................................................................................................................23
5.3技術分析.............................................................................................................................29
5.4個案分析.............................................................................................................................31
5.5數據分析小結...................................................................................................................47
第六章討論..................................................................................................................................48
第七章結論..................................................................................................................................51
7.1結果......................................................................................................................................51
7.2貢獻......................................................................................................................................51
7.3未來方向與研究限制......................................................................................................51
附錄 1986~2018年美國人工智慧技術在教育領域申請案清單................................52
參考文獻.......................................................................................................................................61

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全文檔公開日期:2025/08/26 (本校及校內區域網路)
全文檔公開日期:2025/08/26 (校外網際網路)
全文檔公開日期:2025/08/26 (國家圖書館:臺灣博碩士論文系統)
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