遊戲化的學習可以引起學習者的動機，激勵及吸引學習者提高學習表現。然而，卻較少的研究著重在高等教育學生使用遊戲化學習方式的行為意圖。本研究利用問卷調查法蒐集問卷探討遊戲化運用於高等教育並且討論影響遊戲化運用於高等教育的主要影響因素。根據PLS-SEM的結果得知:在設計遊戲化課程時，建議對於學生先導入遊戲化的內容來增加學生的熟悉度與正面自主性的融入經驗，學生會對遊戲化的績效與付出預期提升，進而提升學生對於遊戲化課程的接受程度。績效預期為影響學生接受遊戲化之最重要因素，其餘因素如付出預期、社會影響、促成條件、參與度、技巧、控制感也占了重要的地位，因此，課程設計師也需針對社群的互動性加以琢磨，進而提升學生的學習績效。期望透過本研究結果，對於課程設計師在規劃課程內容時有實質性的幫助，並提升效率及有效性。

Gamification provides a practical approach to improving learning processes, especially learner’s motivation. However, little research conducted on student’s intention to use gamification in higher education. Therefore, this study explored the gamification in higher educational courses by collecting surveys and discusses the major factors influencing the acceptance of gamification in higher education. Based on the PLS-SEM results, students should take initial game-based learning content to be more familiar with gamification; furthermore, they could have a positive experience so that they would increase their intention. Performance expectancy is the most important factor influencing a student to accept gamification. Other factors, such as effort expectancy, social influence, facilitating conditions, involvement, skills, and control, are also important factors; thereby, instruction designers should increase the interactive activities in the curriculum. With the results of this study, the instructor designer could have substantial help in planning the course content and enhance its efficiency and effectiveness.

目次
表次  v
圖次  vi
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  4
第三節 名詞釋義  5
第四節 研究範圍與限制  7
第二章 文獻探討  9
第一節 遊戲化  9
第二節 整合性科技接受模式  21
第三節 沉浸經驗  33
第四節 偏最小平方法結構方程式模組  45
第三章 研究設計  49
第一節 研究架構  49
第二節 研究流程  51
第三節 研究對象與抽樣方法  53
第四節 研究工具  54
第五節 資料處理  56
第四章 資料分析  61
第一節 樣本描述性統計  61
第二節 信度、效度分析  63
第三節 PLS-SEM分析  71
第四節 綜合討論  79
第五章 研究結論與建議  81
第一節 研究結論  81
第二節 研究建議  85
參考文獻  87
中文部分  87
英文部分  88
附件一  97

表次
表2-1遊戲設計元素分級表  10
表2-2九大類遊戲設計元素  11
表2-3遊戲化之相關研究  16
表2-4整合性科技接受模式發展歷程  21
表2-5構面概念來源  27
表2-6整合性科技接受模式之相關研究  29
表2-7沉浸三階段  33
表2-8沉浸經驗之相關研究  41
表3-1高等教育遊戲化學習接受模式問卷概念題項對照表  54
表3-2 Cronbach’s α係數代表意義  57
表3-3驗證性因素分析配適指標標準表  58
表3-4 PLS-SEM檢驗標準  59
表4-1樣本交叉分析統計結果  62
表4-2 KMO與Bartlett檢定  64
表4-3轉軸後因子矩陣表  65
表4-4驗證性因素分析適配指標標準及分析結果比較表  66
表4-5驗證性因素分析結果  67
表4-6 Bootstrap分析結果  69
表4-7各構面之α、CR值與AVE值整理表  71
表4-8 Fornell-Larker Criterion結果  72
表4-9 PLS-SEM各題項之loading值分析結果  74
表4-10本研究各項假設結果  78

圖次
圖2-1遊戲化學習理論  13
圖2-2 TRA理論架構  23
圖2-3 TAM理論架構  23
圖2-4 TAM2理論架構  24
圖2-5 UTAUT理論架構圖  25
圖2-6三頻道沉浸模型  35
圖2-7四頻道沉浸模型  36
圖2-8八頻道沉浸模型  37
圖2-9路徑模式  46
圖2-10 PLS-SEM系統分析步驟  47
圖3-1研究架構圖  50
圖3-2研究流程圖  52
圖3-3資料分析流程圖  56
圖4-1因素萃取陡坡圖  64
圖4-2驗證性因素分析結果  68
圖4-3全部樣本PLS路徑分析結果  75
圖4-4 PLS-SEM重要績效分析法  76
圖4-5 IPMA項目分析  77

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