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研究生: 李頤宸
Li, Yi-Chen
論文名稱: 國小教師運用生成式人工智慧備課情形之調查研究-以臺中市為例
A Survey Study on the Use and Effectiveness of Generative Artificial Intelligence in Lesson Preparation by Elementary School Teachers: A Case of Elementary Schools in Taichung City
指導教授: 林巧敏
Lin, Chiao-Min
口試委員: 陳世娟
Chen, Shih-Chuan
柯皓仁
Ke, Hao-Ren
學位類別: 碩士
Master
系所名稱: 文學院 - 圖書資訊學數位碩士在職專班
E-Learning Master Program of Library and Information Studies
論文出版年: 2026
畢業學年度: 114
語文別: 中文
論文頁數: 107
中文關鍵詞: 生成式人工智慧備課教師效能感國小教師ChatGPT
外文關鍵詞: Generative Artificial Intelligence, Lesson Preparation, Teacher Efficacy, Elementary School Teachers, ChatGPT
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  • 隨著生成式人工智慧(Generative Artificial Intelligence, Generative AI)快速發展,教師開始將其應用於教材設計、教案撰寫、教學活動規劃及評量設計等備課工作。然而,不同教師之背景條件、人工智慧使用經驗及相關影響因素,可能影響其運用生成式人工智慧備課之情形及教師效能感。因此,本研究以臺中市國民小學教師為研究對象,採問卷調查法蒐集資料,共回收267份有效問卷,並以描述性統計、獨立樣本t檢定、單因子變異數分析、Pearson積差相關及多元迴歸分析等方法進行資料分析。
    研究結果顯示:(一)國小教師普遍已開始運用生成式人工智慧協助備課,其中以ChatGPT為最常使用之工具,主要應用於教材設計、教案撰寫及教學活動發想;(二)不同年齡及教學年資教師於生成式人工智慧使用程度具有顯著差異,而性別、學歷、職務及學校規模則未達顯著差異;(三)生成式人工智慧使用頻率及學習方式對使用程度具有顯著影響;(四)資源投入、行政支持、教師信念與態度及教師AI能力等因素皆與生成式人工智慧使用程度呈顯著正相關,其中以教師AI能力及教師信念與態度具有較佳之預測力;(五)生成式人工智慧使用程度愈高,教師知覺之備課成效愈佳,而備課成效愈佳者,其教師效能感亦愈高。
    綜合而言,生成式人工智慧已逐漸成為國小教師重要的備課輔助工具,不僅有助於提升備課效率與教學品質,亦有助於提升教師效能感。本研究結果可作為國小教師運用生成式人工智慧備課之參考,並提供未來相關研究之參考依據。


    With the rapid development of Generative Artificial Intelligence (Generative AI), elementary school teachers have increasingly adopted AI tools for lesson preparation. However, teachers' backgrounds, AI experience, and technology-related factors may influence their use of Generative AI and teaching efficacy. This study investigated the use of Generative AI in lesson preparation among elementary school teachers in Taichung City, Taiwan.
    A questionnaire survey was conducted, and 267 valid responses were analyzed using descriptive statistics, independent-samples t-tests, one-way analysis of variance (ANOVA), Pearson correlation analysis, and multiple regression analysis.
    The results showed that: (1) ChatGPT was the most frequently used tool, mainly for instructional material design, lesson planning, and teaching activity development; (2) significant differences in Generative AI use were found across age groups and teaching experience, but not gender, educational background, job position, or school size; (3) the frequency of AI use and learning approaches significantly affected teachers' level of Generative AI use; (4) resource investment, administrative support, teachers' beliefs and attitudes, and AI competence were positively associated with Generative AI use, with AI competence and teachers' beliefs and attitudes showing the strongest predictive effects; and (5) greater use of Generative AI was associated with higher lesson preparation effectiveness, which in turn enhanced teachers' teaching efficacy.
    Overall, Generative AI has become an important tool for lesson preparation. The findings provide a useful reference for elementary school teachers integrating Generative AI into lesson preparation and for future related research.

    第一章 緒論 1
    第一節 研究動機 1
    第二節 研究目的 2
    第三節 研究問題 3
    第四節 研究範圍與限制 3
    第五節名詞解釋 4
    第二章 文獻探討 7
    第一節 生成式人工智慧基本概念 7
    第二節 生成式人工智慧在教育之應用 9
    第三節 國小教師備課與教師效能感相關研究 13
    第四節 生成式人工智慧教學應用相關研究 18
    第三章 研究設計與實施 27
    第一節 研究架構 27
    第二節 研究方法 33
    第三節 研究工具 35
    第四節 研究對象 42
    第五節 研究流程 44
    第六節 資料蒐集與分析 47
    第四章 研究結果與分析 49
    第一節 國小教師運用生成式人工智慧備課情形分析 49
    第二節 不同背景與AI經驗對於生成式人工智慧使用程度差異分析 70
    第三節 不同背景變項之教師效能感差異分析 73
    第四節 生成式AI備課影響因素、備課成效與教師效能感之關係分析 79
    第五節 綜合討論 84
    第五章 結論與建議 87
    第一節 研究結論 87
    第二節 研究建議 89
    參考文獻 91
    附件一:臺中市國小教師運用生成式人工智慧備課及效能感調查問卷 97

    Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
    AWS. (n.d.). 什麼是生成式人工智慧?取自 https://aws.amazon.com/tw/what-is/generative-ai/
    AWS. (n.d.). 什麼是自然語言處理?—NLP說明。取自 https://aws.amazon.com/tw/what-is/nlp/
    Bandura, A. (1997). Self-efficacy: The exercise of control. W. H. Freeman.
    Batista, J., Mesquita, A., & Carnaz, G. (2024). Generative AI and higher education: Trends, challenges, and future directions from a systematic literature review. Information, 15(11), Article 676. https://doi.org/10.3390/info15110676
    Cai, H. (2025). Investigating the effects of ChatGPT-supported lesson plan critiques on pre-service teachers' lesson planning skills. Internet and Higher Education, 64, Article 100914.
    Cevikbas, M., Kucuk, S., & Kucuk, M. (2024). Challenges and coping strategies of novice teachers in lesson planning. Journal of Education for Teaching, 50(1), 1-18. https://doi.org/10.1080/02607476.2023.2263941
    Cheah, Y. H., Lu, J., & Kim, J. (2025). Integrating generative artificial intelligence in K–12 education: Examining teachers’ preparedness, practices, and barriers. Computers and Education: Artificial Intelligence, 8, Article 100363.
    Creswell, J. W., & Plano Clark, V. L. (2018). Designing and conducting mixed methods research (3rd ed.). SAGE Publications.
    Dahri, N. A., Vighio, M. S., Bather, J. D., & Arain, A. A. (2024). Extended TAM based acceptance of AI-powered ChatGPT for supporting metacognitive self-regulated learning: A mixed-methods study. Heliyon, 10(7), e28281. https://pubmed.ncbi.nlm.nih.gov/38628736/
    Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
    Education Endowment Foundation. (2024). Teachers using ChatGPT – alongside a guide to support them to use it effectively – can cut lesson planning time by over 30 per cent. https://educationendowmentfoundation.org.uk/news/teachers-using-chatgpt-alongside-a-guide-to-support-them-to-use-it-effectively-can-cut-lesson-planning-time-by-over-30-per-cent
    Elastic. (n.d.). 什麼是自然語言處理(NLP)?取自 https://www.elastic.co/cn/what-is/natural-language-processing
    Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11
    Fan, L. (2025). Educational impacts of generative artificial intelligence on engineering students: A cross-regional study. Scientific Reports, 15, Article 6930.
    Gibson, S., & Dembo, M. H. (1984). Teacher efficacy: A construct validation. Journal of Educational Psychology, 76(4), 569-582. https://doi.org/10.1037/0022-0663.76.4.569
    Gurl, T. J., Markinson, M. P., & Artzt, A. F. (2025). Using ChatGPT as a lesson planning assistant with preservice secondary mathematics teachers. Digital Experiences in Mathematics Education, 11, 114–139. https://doi.org/10.1007/s40751-024-00162-9
    Hoy, A. W., & Spero, R. B. (2005). Changes in teacher efficacy during the early years of teaching: A comparison of four measures. Teaching and Teacher Education, 21(4), 343-356. https://doi.org/10.1016/j.tate.2005.01.007
    Hrastinski, S. (2021). What do we mean by digital tools in teacher professional development? A systematic literature review. Journal of Digital Learning in Teacher Education, 37(3), 180-193. https://doi.org/10.1080/21532974.2021.1914495
    Karaman, M. R. (2024). Are lesson plans created by ChatGPT more effective? An experimental study. International Journal of Technology in Education, 7(2), 45-62.
    Lee, G.-G., & Zhai, X. (2024). Using ChatGPT for science learning: A study on pre-service teachers’ lesson planning. IEEE Transactions on Learning Technologies, 17, 1683–1700. https://doi.org/10.1109/TLT.2024.3401457
    Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017-1054. https://doi.org/10.1111/j.1467-9620.2006.00684.x
    National Council on Teacher Quality. (2023). Planning time may help mitigate teacher burnout—but how much planning time do teachers get? Retrieved from https://www.nctq.org/blog/Planning-time-may-help-mitigate-teacher-burnout-but-how-much-planning-time-do-teachers-get
    Ng, D. T. K., Chan, E. K. C., & Lo, C. K. (2025). Opportunities, challenges and school strategies for integrating generative AI in education. Computers and Education: Artificial Intelligence, 8, Article 100373.
    Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
    NVIDIA. (2022, June 21). 何謂Transformer 模型? https://blogs.nvidia.com/blog/what-is-a-transformer-model/
    Oluwagbenro, M. B. (2024). Generative AI: Definition, concepts, applications, and future prospects. Authorea Preprints. https://doi.org/10.22541/au.170498379.95273584/v1
    Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). SAGE Publications.
    Peterson, P. L., & Marx, R. W. (1978). Teacher planning, teacher behavior, and student achievement. American Educational Research Journal, 15(3), 417-432. https://doi.org/10.3102/00028312015003417
    Pişkin Tunç, M. (2024). Examining pre-service mathematics teachers’ purposes of using ChatGPT in lesson plan development. Sakarya University Journal of Education, 14(2), 391–406. https://doi.org/10.19126/suje.1476326
    Red Hat. (2023, August 7). 一文看懂什麼是生成式人工智慧?Generative AI入門。取自 https://www.redhat.com/zh-tw/topics/ai/what-is-generative-ai
    Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.
    Rubin, H. J., & Rubin, I. S. (2012). Qualitative interviewing: The art of hearing data (3rd ed.). SAGE Publications.
    Sabrina Belloula. (2025). Empowering educators: Leveraging AI to revolutionize lesson planning. International Journal of Research in Education and Science, 11(2), 264–280.
    Sawyer, A. M., Karchmer-Harris, M. A., & Bice, L. R. (2020). Preservice elementary teachers' use of online tools for lesson planning. Journal of Digital Learning in Teacher Education, 36(2), 104-118. https://doi.org/10.1080/21532974.2020.1719545
    Schmidt, D. A., Baran, E., Thompson, A. D., Mishra, P., Koehler, M. J., & Shin, T. S. (2009). Technological pedagogical content knowledge (TPACK): The development and validation of an assessment instrument for preservice teachers. Journal of Research on Technology in Education, 42(2), 123-149. https://doi.org/10.1080/15391523.2009.10782544
    Teo, T. (2011). Factors influencing teachers' intention to use technology: Model development and test. Computers & Education, 57(4), 2432-2440. https://doi.org/10.1016/j.compedu.2011.06.008
    Tschannen-Moran, M., & Woolfolk Hoy, A. (2001). Teacher efficacy: Capturing an elusive construct. Teaching and Teacher Education, 17(7), 783-805. https://doi.org/10.1016/S0742-051X(01)00036-1
    UNESCO. (2023). Guidance for generative AI in education and research. UNESCO. https://unesdoc.unesco.org/ark:/48223/pf0000386693
    UNESCO. (n.d.). 生成式人工智慧教育與研究應用指南。取自 https://www.unesco.org/zh/articles/guidance-generative-ai-education-and-research
    Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., Kaiser, L., & Polosukhin, I. (2017). Attention is all you need. Advances in Neural Information Processing Systems, 30, 5998-6008. https://papers.nips.cc/paper/2017/hash/3f5ee243547dee91fbd053c1c4a845aa-Abstract.html
    Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540
    Wang, N., Wang, X., & Su, Y.-S. (2024). Critical analysis of the technological affordances, challenges and future directions of generative AI in education: A systematic review. Asia Pacific Journal of Education, 44(1), 139–155. https://doi.org/10.1080/02188791.2024.2305156
    Wang, X., Zainuddin, Z., & Leng, C. H. (2025). Generative artificial intelligence in pedagogical practices: A systematic review of empirical studies (2022–2024). Cogent Education, 12(1), Article 2485499. https://doi.org/10.1080/2331186X.2025.2485499
    Xia, Q., Weng, X., Ouyang, F., Lin, T. J., & Chiu, T. K. F. (2024). A scoping review on how generative artificial intelligence transforms assessment in higher education. Education Sciences, 14(5), 468. https://doi.org/10.3390/educsci14050468
    Zahorik, J. A. (1970). The effect of planning on teaching. The Elementary School Journal, 71(3), 143-151. https://doi.org/10.1086/460583
    王金國(2021)。十二年國教課綱素養導向教學的理念與實踐。教育研究月刊,321,45-62。
    甘偵蓉(2023年5月15日)。在ChatGPT風潮下,生成式AI發展的隱憂。科學月刊,497。
    吳雅芬(2025)。生成式AI下教師角色的重塑與挑戰。教育脈動,13。https://pulse.naer.edu.tw/Article/Detail/717c0000-56bb-0050-2341-08ddbf8eb9cb
    呂巨建、謝佳燁、鄭遂博、林凱瀚、黎嘉文(2024)。國內生成式人工智慧應用於教育領域的研究現狀與趨勢——基於CiteSpace的視覺化分析。Advances in Education,14(8),1-10。https://doi.org/10.12677/ae.2024.1481409
    宋萑、林敏(2023)。ChatGPT/生成式人工智慧時代下教師的工作變革:機遇、挑戰與應對。華東師範大學學報(教育科學版),41(11),1-13。https://doi.org/10.16382/j.cnki.1000-5560.2023.11.001
    宋曜廷、潘佩妤(2010)。混合研究在教育研究的應用。教育科學研究期刊,55(4),1-30。https://doi.org/10.3966/2073753X2010125504001
    林清山(2003)。心理與教育統計學。東華書局。
    邱雅翎、王仁俊(2023)。以整合型科技接受模式探討「生生用平板」高雄市國小教師使用iPad教學之行為意圖。工業科技教育學刊,16,65-79。
    洪麗卿(2022)。從課綱至教學實踐:跨領域課程統整之實施與建議。臺灣教育評論月刊,11(4),28-33。
    苗逢春(2023)。生成式人工智慧技術原理及其教育適用性考證。現代教育技術,33(1),5-12。https://doi.org/10.3969/j.issn.1009-8097.2023.01.001
    張仁家、陳致州(2024)。高中教學現場運用AI之挑戰與應對。臺灣教育評論月刊,13(12),1-6。
    張芳全(2021)。國小教師工作壓力與職業倦怠關係之研究。教育學刊,57,89-118。https://doi.org/10.3966/102588872021120057004
    教育部(2022)。中小學數位教學指引1.0版。取自 https://www.edu.tw/News_Content.aspx?n=9E7AC85F1954DDA8&s=2A424215331E351C
    教育部(2024)。中小學數位教學指引2.0版。臺灣教育部。
    許佳綺(2017)。國民小學教師實施公開授課之研究〔未出版之碩士論文〕。國立清華大學。
    劉世雄(2021)。國小教師採合作探究理念進行觀課、議課之個案研究。教育研究與發展期刊,17(1),1-29。https://doi.org/10.3966/1816636X2021031701001
    劉志銘(2020)。偏遠國小四合一組長之工作現況、壓力與解決建議。臺灣教育評論月刊,9(4),145-149。
    劉鎮寧、洪榮昭、吳清山(2015)。臺灣與中國大陸國小教師專業發展政策與實施現況之比較研究。教育研究與發展期刊,11(2),1-28。https://doi.org/10.3966/1816636X2015061102001
    潘政緯、林巧敏(2013)。澎湖縣國小教師教學資訊需求與資訊尋求行為之研究〔未出版之碩士論文〕。政治大學。
    賴志樫、顏榮泉(2024年11月)。主編序:AI對於教育之衝擊與因應。臺灣教育評論月刊,13(11),III–IV。
    羅文杏(2021)。在臺灣國小實施雙語教學所面臨的挑戰及教師專業發展之可行建議。教育研究月刊,321,78-97。

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