IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p14549-d964265.html
   My bibliography  Save this article

Developing AI Literacy for Primary and Middle School Teachers in China: Based on a Structural Equation Modeling Analysis

Author

Listed:
  • Leilei Zhao

    (School of Humanities, Jiangnan University, Wuxi 214122, China)

  • Xiaofan Wu

    (School of Humanities, Jiangnan University, Wuxi 214122, China)

  • Heng Luo

    (Faculty of Artificial Intelligence in Education, Central China Normal University, Wuhan 430079, China)

Abstract

As smart technology promotes the development of various industries, artificial intelligence (AI) has also become an important driving force for innovation and transformation in education. For teachers, how to skillfully apply AI in teaching and improve their AI literacy has become a necessary goal for their sustainable professional development. This research examines the correlations among the dimensions of AI literacy of teachers in order to promote the effectiveness of class teaching and the adoption of artificial intelligence literacy (AIL). Our findings are based on the analysis of 1013 survey results, where we tested the level of AI literacy of teachers, including Knowing and Understanding AI (KUAI), Applying AI (AAI), Evaluating AI Application (EAIA), and AI Ethics (AIE). We find that AAI had a significant, positive effect on the other three dimensions. Thus, based on the analysis, the government should take action to cultivate teachers’ AI literacy. In order to improve teachers’ AI literacy, the choice of curriculum, content, methods, and practical resources for special training should be diverse and committed to making AI literacy an essential enabler for teachers’ sustainable future development.

Suggested Citation

  • Leilei Zhao & Xiaofan Wu & Heng Luo, 2022. "Developing AI Literacy for Primary and Middle School Teachers in China: Based on a Structural Equation Modeling Analysis," Sustainability, MDPI, vol. 14(21), pages 1-16, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14549-:d:964265
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/14549/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/14549/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hyun Suk Lee & Junga Lee, 2021. "Applying Artificial Intelligence in Physical Education and Future Perspectives," Sustainability, MDPI, vol. 13(1), pages 1-16, January.
    2. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation, and Work," NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 197-236, National Bureau of Economic Research, Inc.
    3. James Johnson, 2019. "Artificial intelligence & future warfare: implications for international security," Defense & Security Analysis, Taylor & Francis Journals, vol. 35(2), pages 147-169, April.
    4. Corneliu Bjola, 2022. "AI for development: implications for theory and practice," Oxford Development Studies, Taylor & Francis Journals, vol. 50(1), pages 78-90, January.
    5. Daron Acemoglu & Pascual Restrepo, 2018. "Artificial Intelligence, Automation and Work," Boston University - Department of Economics - Working Papers Series dp-298, Boston University - Department of Economics.
    6. Carmen del Pilar Gallardo-Montes & Antonio Rodríguez Fuentes & María Jesús Caurcel Cara & Davide Capperucci, 2022. "Functionality of Apps for People with Autism: Comparison between Educators from Florence and Granada," IJERPH, MDPI, vol. 19(12), pages 1-17, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jason Ryan A. Pujeda, 2023. "A Systematic Review on Teachers’ Digital Competencies on the Adoption of Artificial Intelligence in Enhancing Learning Experiences," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 7(12), pages 373-383, December.
    2. Ewa, Moses Apie PhD, 2024. "Artificial Intelligence (AI) Literacy, An Investment for Enhancing Educators’ Skills in AI Powered Primary Schools in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(4), pages 1226-1238, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gilbert Cette & Lorraine Koehl & Thomas Philippon, 2019. "The Labor Share in the Long Term: A Decline?," Economie et Statistique / Economics and Statistics, Institut National de la Statistique et des Etudes Economiques (INSEE), issue 510-511-5, pages 35-51.
    2. Estrada, Mario Arturo Ruiz & Park, Donghyun & Staniewski, Marcin, 2023. "Artificial Intelligence (AI) can change the way of doing policy modelling," Journal of Policy Modeling, Elsevier, vol. 45(6), pages 1099-1112.
    3. Mahmut Ozer & Matjaž Perc, 2020. "Dreams and realities of school tracking and vocational education," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-7, December.
    4. David Rezza Baqaee & Emmanuel Farhi, 2018. "Macroeconomics with Heterogeneous Agents and Input-Output Networks," NBER Working Papers 24684, National Bureau of Economic Research, Inc.
    5. Eleni Giouli & Pisinas Yorgos & Anna-Maria Kanzola, 2021. "Human Capital and Production Structure: Evidence from Greece," European Journal of Economics and Business Studies Articles, Revistia Research and Publishing, vol. 7, January -.
    6. Zilian, Laura S. & Zilian, Stella S. & Jäger, Georg, 2021. "Labour market polarisation revisited: evidence from Austrian vacancy data," Journal for Labour Market Research, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany], vol. 55, pages 1-7.
    7. Keeheon Lee, 2021. "A Systematic Review on Social Sustainability of Artificial Intelligence in Product Design," Sustainability, MDPI, vol. 13(5), pages 1-29, March.
    8. Venturini, Francesco, 2022. "Intelligent technologies and productivity spillovers: Evidence from the Fourth Industrial Revolution," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 220-243.
    9. Heyman, Fredrik & Olsson, Martin, 2022. "Long-Run Effects of Technological Change: The Impact of Automation and Robots on Intergenerational Mobility," Working Paper Series 1451, Research Institute of Industrial Economics, revised 29 Jun 2023.
    10. Gabriel López-Martínez & Francisco Eduardo Haz-Gómez & José Eulogio Real Deus, 2023. "Are You Really Your Own Boss? Flexi-Vulnerability and False Consciousness of Autonomy in the Digital Labor Culture of Riders," Social Sciences, MDPI, vol. 12(8), pages 1-18, July.
    11. Artuc, Erhan & Bastos, Paulo & Rijkers, Bob, 2023. "Robots, tasks, and trade," Journal of International Economics, Elsevier, vol. 145(C).
    12. Colombo, Emilio & Mercorio, Fabio & Mezzanzanica, Mario, 2019. "AI meets labor market: Exploring the link between automation and skills," Information Economics and Policy, Elsevier, vol. 47(C), pages 27-37.
    13. Lu, Jing & Xiao, Qinglan & Wang, Taoxuan, 2023. "Does the digital economy generate a gender dividend for female employment? Evidence from China," Telecommunications Policy, Elsevier, vol. 47(6).
    14. Alejandro Micco, 2019. "The Impact of Automation in Developed Countries," Working Papers wp480, University of Chile, Department of Economics.
    15. Ajay Agrawal & Joshua Gans & Avi Goldfarb, 2019. "Economic Policy for Artificial Intelligence," Innovation Policy and the Economy, University of Chicago Press, vol. 19(1), pages 139-159.
    16. Andreas Irmen, 2021. "Automation, growth, and factor shares in the era of population aging," Journal of Economic Growth, Springer, vol. 26(4), pages 415-453, December.
    17. Zhu, Jun & Zhang, Jingting & Feng, Yiqing, 2022. "Hard budget constraints and artificial intelligence technology," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    18. Gregory Casey & Ryo Horii, 2019. "A Multi-factor Uzawa Growth Theorem and Endogenous Capital-Augmenting Technological Change," ISER Discussion Paper 1051, Institute of Social and Economic Research, Osaka University.
    19. Henrik Schwabe & Fulvio Castellacci, 2020. "Automation, workers’ skills and job satisfaction," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-26, November.
    20. Hidalgo, Camila & Micco, Alejandro, 2024. "Computerization, offshoring and trade: The effect on developing countries," World Development, Elsevier, vol. 180(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:14549-:d:964265. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.