簡易檢索 / 詳目顯示

研究生: 陳璽宇
Chen, Si-Yu
論文名稱: 人工智慧素養測驗發展及其與科技素養之相關研究
Development of AI Literacy Test and Its Correlation with Technological Literacy
指導教授: 張玉山
Chang, Yu-Shan
學位類別: 碩士
Master
系所名稱: 科技應用與人力資源發展學系
Department of Technology Application and Human Resource Development
論文出版年: 2020
畢業學年度: 108
語文別: 中文
論文頁數: 144
中文關鍵詞: AI人工智慧AI素養科技素養AI素養測驗
英文關鍵詞: AI, artificial intelligence, AI literacy, technological literacy, AI literacy test
DOI URL: http://doi.org/10.6345/NTNU202000982
論文種類: 學術論文
相關次數: 點閱:336下載:126
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報
  • 本研究以教育部《和AI做朋友》系列教材為主,發展一份「人工智慧素養測驗」,據此分析我國當代高中生的AI (artificial intelligence)素養表現情形與差異性,包含AI知識、AI技能、AI態度三個構面。本研究進一步探討不同性別、不同資訊來源之高中生是否會在AI素養的表現上有所差異或趨向,同時以洪國峰(2016)所發展之科技素養量進行測驗,並透過統計工具SPSS分析AI素養與科技素養之間的相關性。
    本研究主要結論:(1)研究者自行開發的AI素養測驗具備優良的信、效度,未來研究者可使用與推廣;(2)我國高中生在AI素養的表現屬於中低程度;(3)男、女高中生僅在AI態度表現上面有顯著差異,在AI知識、AI技能等構面上沒有顯著差異;(4)如何接收AI資訊大多不影響高中生AI素養表現,僅選擇透過「學校課程」接收AI資訊與知識的學生具有較佳的AI態度素養表現;(5)AI素養與科技素養在態度構面上存在顯著高度相關,知識、技能構面倆倆之間亦皆存在顯著低度相關。

    This research developed an AI (artificial intelligence) Literacy Test based on a series of teaching materials by the Ministry of Education. The purpose of this reserch is to analyze contemporary senior high school students’ performance on AI Literacy in Taiwan, including three dimensions: AI knowledge, AI skill, and AI attitude.
    This research also discussed if different genders or different information sources would affect the students’ performances on AI. At the same time, this research analyzed the correlation between AI literacy and technology literacy by using Hung’s technology literacy test.
    Those main results of this research were: (1) The AI literacy test had good reliability and validity which was worthy recommended and applied. (2) Senior high school students in Taiwan presented low to medium level on AI literacy performarces. (3) The students’ performances represented significant difference only on AI attitude between the gender. (4) The different information resource didn’t affect the students’ performances, but only the students’ who chose to receive AI information and knowledge by the school courses had better performances on AI attitude. (5) AI literacy and technology literacy was revealed to highly correlated on attitude dimension and lowly correlated between knowledge and skill.

    誌 謝 i 中文摘要 iii ABSTRACT v 目 錄 vii 表 次 xi 圖 次 xiii 第一章 緒 論 1 第一節 研究背景與動機 1 第二節 研究目的與待答問題 7 第三節 研究範圍 10 第四節 名詞解釋 11 第二章 文獻探討 13 第一節 人工智慧 13 第二節 科技素養 22 第三節 AI素養 29 第三章 研究方法 39 第一節 研究架構 39 第二節 研究對象 43 第三節 研究方法與流程 44 第四節 研究工具 47 第五節 資料處理與分析 57 第四章 資料分析與討論 59 第一節 正式AI素養測驗施測 59 第二節 高中生AI素養表現現況 66 第三節 不同背景變項的高中生AI素養表現之差異 74 第四節 高中生AI素養與科技素養之相關性 87 第五章 結論與建議 97 第一節 研究結果 97 第二節 建議 102 第三節 研究限制與未來研究建議 103 參考文獻 107 一、中文部分 107 二、外文部分 109 附錄 115 附錄一 AI素養測驗態度量表-預試問卷 117 附錄二 AI素養測驗知識與技能測驗-預試問卷 119 附錄三 AI素養測驗態度量表-正式問卷 132 附錄四 AI素養測驗知識與技能測驗-正式問卷 134 附錄五 《AI知識與技能測驗》參考答案 144

    一、中文部分
    日本經濟新聞社(2019)。和AI一起生活一起工作。臺北市:遠足文化。
    行政院新聞傳播處(2017)。運用人工智慧教育 提升學生競爭力與創意。https://www.ey.gov.tw/Page/9277F759E41CCD91/70882f5c-5b3f-4a4e-8ff5-5ec1148ef830
    李建樹主編(2019a)。和AI做朋友〈相逢篇〉人工智慧有意思。臺北市:教育部。
    李建樹主編(2019b)。和AI做朋友〈相識篇〉開啟AI任意門。臺北市:教育部。
    李建樹主編(2019c)。和AI做朋友〈相知篇〉從0開始學AI。臺北市:教育部。
    李堅萍(2006)。培育科技創造力應重視實作技能的教學與自我效能的激發。生活科技教育,39(8),21-28。
    李開復、王詠剛(2017)。人工智慧來了。臺北市:遠見天下文化出版股份有限公司。
    林志忠(1998)。科技素養教育的哲學分析。國立臺灣師範大學教育學系博士論文,未出版,臺北市。
    邱皓政(2010)。量化研究與統計分析(五版)。臺北:五南圖書。
    邱皓政(2012)。量化研究法:測驗原理與量表發展技術。臺北:雙葉。
    洪國峰(2016)。國中生的科技素養測驗發展及其表現之研究。(博士論文)。取自:140.122.127.138/bitstream/20.500.12235/96462/1/
    089671002701.pdf
    張玉山(2019)。人工智慧的教育研發與應用成效——人工智慧融入STEAM教學模組之教學成效。行政院科技部專題研究計畫,編號:HSS04。
    教育部(2016)。十二年國民基本教育課程綱要:科技領域(草案)。臺北:教育部。
    教育部(2017)。人工智慧技術及應用人才培育計畫。取自https://www.edu.tw/News_Content.aspx?n=D33B55D537402BAA&s=8E0AD699C8A79256
    教育部(2017)。十二年國民基本教育課程綱要國民中學暨普通型高級中等學校:科技領域課程手冊。臺北市:教育部。
    教育部(2018)。十二年國民基本教育課程綱要國民中學暨普通型高級中等學校─科技領域。臺北市:教育部。
    郭生玉(1996)。心理與教育測驗。臺北市:精華書局。
    陳信希、郭大維、李傑主編(2019)。人工智慧導論。新北市:全華圖書。
    游光昭、韓豐年、徐毅穎、林坤誼(2005)。國中學生科技態度量表之發展。高雄師大學報,19,69-83。
    黃臺珠主編(2014)。2012年臺灣公民科技素養概況。高雄:國立中山大學公民素養推動研究中心。
    潘志傑(2009)。應用樂高機器人於人工智慧教育之教案設計、教學評量及支援教學平台輔助工具開發之研究。國立屏東科技大學碩士學位論文,1-117。
    謝榕、李霞(2014)。人工智能課程教學案例庫建設及案例教學實踐。計算機教育,19,93-97。

    二、外文部分
    Carmines, E. G., & Zeller, R. A. (1979). Reliability and validity assessment. Beverly Hills, CA: Sage.
    Ching, T., Himmelstein, D. S., Beaulieu-Jones, B. K., Kalinin, A. A., Do, B. T., Way, G. P., ... & Xie, W. (2018). Opportunities and obstacles for deep learning in biology and medicine. Journal of The Royal Society Interface, 15(141), 20170387.
    De Vore, P. W. (1985). Differentiating between science and technology. Paper presented at the annual conference of the international technology education association. ERIC ED 265407.
    Domingos, P. (2015). The master algorithm: How the quest for the ultimate learning machine will remake our world. Basic Books.
    Draskovic, D., Cvetanovic, M., & Nikolic, B. (2018). SAIL—Software system for learning AI algorithms. Computer Applications in Engineering Education, 26(5), 1195-1216. doi.org/10.1002/cae.21988
    Dyrenfurth, M. J. (1991). Technological literacy synthesized. In M. J.Dyrenfurth & M. R. Kozak (Eds.), Technological literacy: Council on Techology Teacher Education 40th yearbook (pp. 138-183). Peoria, IL:Macmillan McGraw-Hill.
    Fernandes, M. A. (2016). Problem‐based learning applied to the artificial intelligence course. Computer Applications in Engineering Education, 24(3), 388-399.
    Furey, H., & Martin, F. (2019). AI education matters: a modular approach to AI ethics education. AI Matters, 4(4), 13-15.
    Goldberg, Y. (2016). A primer on neural network models for natural language processing. Journal of Artificial Intelligence Research, 57, 345-420.
    Guzman, A. L. (2018). Voices in and of the machine: Source orientation toward mobile virtual assistants. Computers in Human Behavior, 90, 343-350.
    Hassabis, D., Kumaran, D., Summerfield, C., & Botvinick, M. (2017). Neuroscience-inspired artificial intelligence. Neuron, 95(2), 245-258.
    Helmstaedter, M. (2015). The mutual inspirations of machine learning and neuroscience. Neuron, 86(1), 25-28.
    Istenič Starčič, A. (2019). Human learning and learning analytics in the age of artificial intelligence. British Journal of Educational Technology, 50(6). 2974-2976. doi.org/10.1111/bjet.12879.
    Kaiser, H. F. (1974). Little jiffy, mark IV. Educational and Psychological Measurement, 34, 111-117.
    Kandlhofer, M., Steinbauer, G., Hirschmugl-Gaisch, S., & Huber, P. (2016). Artificial intelligence and computer science in education: From kindergarten to university. In 2016 IEEE Frontiers in Education Conference (FIE), 1-9.
    Kimbell, R., Stables, K., & Green, R. (2002) .The nature and purpose of design and technology. In G. Owen-Jackson (Ed.), Teaching design and technology in secondary schools (pp.19-30). Landon: Routledge Falmer.
    Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30(3), 607-610.
    Kumar, D., & Meeden, L. (1998). A robot laboratory for teaching artificial intelligence. ACM SIGCSE Bulletin, 30(1), 341-344.
    Li, X., & Zhang, T. (2017). An exploration on artificial intelligence application: From security, privacy and ethic perspective. In Cloud Computing and Big Data Analysis (ICCCBDA), 2017 IEEE 2nd International Conference on (pp. 416-420).
    Liu, J. Y. S. (2019). The dynamic control of space travel and the application of artificial intelligence. East-Asia Review, 503, 17-24.
    McCormick, R. (2004). Issues of learning and knowledge in technology education. International Journal of Technology and Design Education, 14(1), 21-44.
    National Assessment Governing Board (2018). Technology and engineering literacy assessment and item specifications for the 2018 National assessment of educational progress. San Francisco, CA: WestEd.
    Neumann, M. (2019). AI education matters: a first introduction to modeling and learning using the data science workflow. AI Matters, 5(3), 21-24.
    Russell, S. J., & Norvig, P. (2010). Artificial intelligence: A modern approach. USA; PearsonEducation,Inc.
    Schmidhuber, J. (2015). Deep learning in neural networks: An overview. Neural Networks, 61, 85-117.
    Skilton, M., & Hovsepian, F. (2017). The 4th industrial revolution: Responding to the impact of artificial intelligence on business. New York: Springer.
    Smalley, L., & Brady, S. (1984). Technological literacy test. Unpublished report supported by a grant form the American Council on Industrial Arts Teacher Education. Menomonie, WI: Author, University of Wisconsin -Stout. ERIC ED 255637.
    Soltani, A. A., Huang, H., Wu, J., Kulkarni, T. D., & Tenenbaum, J. B. (2017). Synthesizing 3d shapes via modeling multi-view depth maps and silhouettes with deep generative networks. In The IEEE conference on computer vision and pattern recognition (CVPR) (Vol. 3, p. 4).
    Stashak, G. (1981). Technological literacy: The publisher’s role. ERIC ED 206915
    Voke, K.S., & Yip, W. M. (1999). Gender and technology in Hong Kong: A study of pupils’ attitudes toward technology. International Journal of Technology and Design Education, 9, 57-71.
    Voke, K.S., Yip, W. M., & Lo, T.K. (2003). Hong Kong pupils’ attitudes toward technology: The impact of design and technology programs. Journal of Technology Education, 15(1), 48-63.
    Weber, K. & Custer, R.(2005). Gender-based preferences toward technology education content, activities, and instructional methods. Journal of Technology Education, 16(2), 55-71.
    Yu, K. C., Lin, K. Y., Han, F. N., & Hsu, I. Y. (2012). A model of junior high school students' attitudes toward technology. International Journal of Technology and Design Education, 22(4), 423-436.
    Yu, K. H., Beam, A. L., & Kohane, I. S. (2018). Artificial intelligence in healthcare. Nature Biomedical Engineering, 2(10), 719-731.
    Zhou, H., Zhang, H., Zhou, Y., Wang, X., & Li, W. (2018, July). Botzone: an online multi-agent competitive platform for AI education. In Proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education (pp. 33-38).

    下載圖示
    QR CODE