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:394 下載:140 |
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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.
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).