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    請使用永久網址來引用或連結此文件: https://ir.lib.ncu.edu.tw/handle/987654321/99437


    題名: 生成式人工智慧支援文創課程之雙語對話練習;Generative AI-Supported Bilingual Dialogue Practice in Cultural and Creative Courses
    作者: 洪霈羽;Pei-Yu, Hung
    貢獻者: 學習與教學研究所
    關鍵詞: 生成式AI;EMI課程;TELL;ESP;Generative AI;EMI courses;TELL;ESP
    日期: 2026-01-27
    上傳時間: 2026-03-06 18:59:44 (UTC+8)
    出版者: 國立中央大學
    摘要: 本研究旨在探討生成式人工智慧支援之英語學習平台(Pocketor)介入文創相關課程之雙語對話練習後,對學生學習動機與科技接受度之影響,並進一步瞭解學生在英語同儕對話偏好與英語對話滿意度之表現。研究採單組前後測設計,以某大學文創相關科系修課學生為對象,蒐集前測與後測有效樣本共26份。研究工具包含ARCS動機量表(注意力、關聯性、自信、滿意度)、科技接受度模型(TAM)量表(知覺有用性、知覺易用性),以及英語同儕對話偏好調查與英語對話滿意度評量。資料分析以描述性統計呈現各構面分布,並以配對樣本t檢定比較介入前後之差異,另採逐題分析以更細緻呈現學生在各題項之變化。
    研究結果顯示,介入後學生在學習動機(ARCS)與科技接受度(TAM)之部分題項達顯著差異,顯示生成式AI支援之雙語對話練習可能在特定面向上提升學生之學習投入與對系統使用的正向感受;同時,學生之英語同儕對話偏好與英語對話滿意度亦呈現整體偏正向之趨勢。綜合而言,Pocketor作為生成式AI 輔助工具,具備促進文創課程雙語對話練習之潛力,建議教學現場可透過任務設計、回饋機制與同儕互動安排,強化學生在「注意力維持」、「學習信心建立」與「對話體驗品質」等面向。惟本研究受限於樣本數與單組設計,未來可擴大樣本並加入對照組或混合方法,以更全面驗證生成式AI支援雙語對話練習之教學成效與學習歷程。
    ;This study investigates the effects of integrating a generative-AI–supported English learning platform (Pocketor) into bilingual dialogue practice in a cultural and creative (CC) course. Specifically, it examines changes in students’ learning motivation and technology acceptance, as well as their preferences for English peer dialogue and their satisfaction with English dialogue activities. A one-group pretest–posttest design was adopted. Participants were students enrolled in a CC-related course at a university, with 26 valid paired responses collected for both the pretest and posttest.
    Research instruments included the ARCS Motivation Scale (Attention, Relevance, Confidence, and Satisfaction), the Technology Acceptance Model (TAM) Scale (Perceived Usefulness and Perceived Ease of Use), an English Peer Dialogue Preference Survey, and an English Dialogue Satisfaction Questionnaire. Descriptive statistics were used to summarize overall trends across constructs. Paired-samples t-tests were conducted to compare pretest and posttest scores, and item-level analysis was performed to provide a more fine-grained understanding of changes across individual items.
    Results indicated statistically significant differences in selected items within the ARCS and TAM measures after the intervention, suggesting that generative AI–supported bilingual dialogue practice may enhance specific aspects of students’ engagement and their perceptions of system use. In addition, students demonstrated generally positive tendencies in both peer dialogue preferences and dialogue satisfaction. Overall, Pocketor shows potential as an instructional support tool for bilingual dialogue practice in CC courses. Pedagogical implications include designing structured tasks, providing timely feedback, and arranging peer interaction to strengthen sustained attention, confidence building, and the quality of dialogue experiences. Given limitations such as the sample size and the one-group design, future research should incorporate larger samples, comparison groups, and mixed-method approaches to further validate learning outcomes and explore learning processes in depth.
    顯示於類別:[學習與教學研究所 ] 博碩士論文

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