Skip to main content

AI Literacy Education in Secondary Schools

  • Chapter
  • First Online:
AI Literacy in K-16 Classrooms

Abstract

As AI literacy has grown its popularity across countries and regions around the world to design and implement AI curricula in secondary school levels. According to the report of UNESCO (2022), 11 member states have designed, endorsed, and implemented AI government-endorsed curricula. In the review of Ng et al. (2021b), over 14 countries around the world (including the United States, China, Spain, Hong Kong, Finland, Brazil, and Germany) have begun to promote secondary students’ AI competences and equip them with related knowledge, skills, and attitudes.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 129.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Chai, C. S., Lin, P. Y., Jong, M. S. Y., Dai, Y., Chiu, T. K., & Huang, B. (2020, August). Factors influencing students; behavioral intention to continue artificial intelligence learning. In 2020 International Symposium on Educational Technology (ISET) (pp. 147–150). IEEE.

    Google Scholar 

  • Chai, C. S., Lin, P. Y., Jong, M. S. Y., Dai, Y., Chiu, T. K., & Qin, J. (2021). Perceptions of and behavioral intentions towards learning artificial intelligence in primary school students. Educational Technology & Society, 24(3), 89–101.

    Google Scholar 

  • Chiu, T. K., Meng, H., Chai, C. S., King, I., Wong, S., & Yam, Y. (2021). Creation and evaluation of a pretertiary artificial intelligence (AI) curriculum. IEEE Transactions on Education., 65, 30–39.

    Article  Google Scholar 

  • Deng, W., Huang, X., Liu, Q., & Wang, Z. (2021, December). Curriculum design of artificial intelligence in middle school-taking posture recognition as an example. In 2021 Tenth International Conference of Educational Innovation Through Technology (EITT) (pp. 310–315). IEEE.

    Google Scholar 

  • Druga, S., Vu, S. T., Likhith, E., & Qiu, T. (2019). Inclusive AI literacy for kids around the world. In Proceedings of FabLearn 2019 (pp. 104–111).

    Google Scholar 

  • Estevez, J., Garate, G., & Graña, M. (2019). Gentle introduction to artificial intelligence for high-school students using scratch. IEEE Access, 7, 179027–179036.

    Article  Google Scholar 

  • Fernández-MartĂ­nez, C., Hernán-Losada, I., & Fernández, A. (2021). Early introduction of AI in Spanish middle schools. A motivational study. KI-KĂĽnstliche Intelligenz, 35(2), 163–170.

    Article  Google Scholar 

  • Gao, J., & Wang, L. (2019, August). Reverse thinking teaching discussion in high school information technology under new curriculum standards. In 2019 14th International Conference on Computer Science & Education (ICCSE) (pp. 222–226). IEEE.

    Google Scholar 

  • Glaser, B. G. (1965). The constant comparative method of qualitative analysis. Social Problems, 12(4), 436–445.

    Google Scholar 

  • Gong, X., Wu, Y., Ye, Z., & Liu, X. (2018, June). Artificial intelligence course design: iSTREAM-based visual cognitive smart vehicles. In 2018 IEEE Intelligent Vehicles Symposium (IV) (pp. 1731–1735). IEEE.

    Google Scholar 

  • Gunasilan, U. (2021). Debate as a learning activity for teaching programming: A case in the subject of machine learning. Higher Education, Skills and Work-based Learning, 12, 705–718.

    Article  Google Scholar 

  • Kahn, K. M., Megasari, R., Piantari, E., & Junaeti, E. (2018). AI programming by children using snap! Block programming in a developing country. Retrieved from https://ecraft2learn.github.io/ai/publications/EC-TEL_2018_source-files_48%20kk%20edits%20changes%20accepted.pdf

  • Kaspersen, M. H., Bilstrup, K. E. K., Van Mechelen, M., Hjorth, A., Bouvin, N. O., & Petersen, M. G. (2021, June). VotestratesML: A high school learning tool for exploring machine learning and its societal implications. In FabLearn Europe/MakeEd 2021-An international conference on computing, design and making in education (pp. 1–10).

    Google Scholar 

  • Lee, I., Ali, S., Zhang, H., DiPaola, D., & Breazeal, C. (2021). Developing middle school students’ AI literacy. In Proceedings of the 52nd ACM technical symposium on computer science education (pp. 191–197).

    Google Scholar 

  • Marques, L. S., Gresse von Wangenheim, C., & Hauck, J. C. (2020). Teaching machine learning in school: A systematic mapping of the state of the art. Informatics in Education, 19(2), 283–321.

    Article  Google Scholar 

  • Morris, T. H. (2020). Experiential learning–a systematic review and revision of Kolb’s model. Interactive Learning Environments, 28(8), 1064–1077.

    Article  Google Scholar 

  • Ng, D. T. K., & Chu, S. K. W. (2021). Motivating students to learn AI through social networking sites: A case study in Hong Kong. Online Learning, 25(1), 195–208.

    Article  Google Scholar 

  • Ng, D. T. K., Leung, J. K. L., Chu, K. W. S., & Qiao, M. S. (2021a). AI literacy: Definition, teaching, evaluation and ethical issues. Proceedings of the Association for Information Science and Technology, 58(1), 504–509.

    Article  Google Scholar 

  • Ng, D. T. K., Leung, J. K. L., Chu, S. K. W., & Qiao, M. S. (2021b). Conceptualizing AI literacy: An exploratory review. Computers and Education: Artificial Intelligence, 2, 100041.

    Google Scholar 

  • Norouzi, N., Chaturvedi, S., & Rutledge, M. (2020, April). Lessons learned from teaching machine learning and natural language processing to high school students. In Proceedings of the AAAI conference on artificial intelligence (vol. 34, no. 09, pp. 13397–13403).

    Google Scholar 

  • Reed, D. A., & Dongarra, J. (2015). Exascale computing and big data. Communications of the ACM, 58(7), 56–68.

    Article  Google Scholar 

  • Reyes, A. A., Elkin, C., Niyaz, Q., Yang, X., Paheding, S., & Devabhaktuni, V. K. (2020, August). A Preliminary work on visualization-based education tool for high school machine learning education. In 2020 IEEE Integrated STEM Education Conference (ISEC) (pp. 1–5). IEEE.

    Google Scholar 

  • RodrĂ­guez-GarcĂ­a, J. D., Moreno-LeĂłn, J., Román-González, M., & Robles, G. (2020, October). Introducing artificial intelligence fundamentals with LearningML: artificial intelligence made easy. In Eighth international conference on technological ecosystems for enhancing multiculturality (pp. 18–20).

    Google Scholar 

  • Sabuncuoglu, A. (2020). Designing one year curriculum to teach artificial intelligence for middle school. In Proceedings of the 2020 ACM conference on innovation and technology in computer science education (pp. 96–102).

    Google Scholar 

  • Sakulkueakulsuk, B., Witoon, S., Ngarmkajornwiwat, P., Pataranutaporn, P., Surareungchai, W., Pataranutaporn, P., & Subsoontorn, P. (2018, December). Kids making AI: Integrating machine learning, gamification, and social context in STEM education. In 2018 IEEE international conference on Teaching, Assessment, and Learning for Engineering (TALE) (pp. 1005–1010). IEEE.

    Google Scholar 

  • Sanusi, I. T., Oyelere, S. S., Agbo, F. J., & Suhonen, J. (2021, October). Survey of resources for introducing machine learning in K-12 context. In 2021 IEEE Frontiers in Education Conference (FIE) (pp. 1–9). IEEE.

    Google Scholar 

  • Sintov, N., Kar, D., Nguyen, T., Fang, F., Hoffman, K., Lyet, A., & Tambe, M. (2016, March). From the lab to the classroom and beyond: extending a game-based research platform for teaching AI to diverse audiences. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 30, No. 1).

    Google Scholar 

  • Tamborg, A. L., Elicer, R., & Spikol, D. (2022). Programming and computational thinking in mathematics education. KI-KĂĽnstliche Intelligenz, 1–9.

    Google Scholar 

  • Touretzky, D., Gardner-McCune, C., Martin, F., & Seehorn, D. (2019, July). Envisioning AI for K-12: What should every child know about AI? In Proceedings of the AAAI conference on artificial intelligence (vol. 33, no. 01, pp. 9795–9799).

    Google Scholar 

  • UNESCO. (2022). K-12 AI curricula: A mapping of government-endorsed AI curricula. Retrieved from https://unesdoc.unesco.org/ark:/48223/pf0000380602

  • Vachovsky, M. E., Wu, G., Chaturapruek, S., Russakovsky, O., Sommer, R., & Fei-Fei, L. (2016, February). Toward more gender diversity in CS through an artificial intelligence summer program for high school girls. In Proceedings of the 47th ACM technical symposium on computing science education (pp. 303–308).

    Google Scholar 

  • Wan, X., Zhou, X., Ye, Z., Mortensen, C. K., & Bai, Z. (2020, June). SmileyCluster: Supporting accessible machine learning in K-12 scientific discovery. In Proceedings of the interaction design and children conference (pp. 23–35).

    Google Scholar 

  • Zhang, J., & Du, H. (2008, December). The PBL’s application research on prolog language’s instruction. In 2008 international workshop on education technology and training & 2008 international workshop on geoscience and remote sensing (vol. 1, pp. 112–114). IEEE.

    Google Scholar 

  • Zimmermann-Niefield, A., Turner, M., Murphy, B., Kane, S. K., & Shapiro, R. B. (2019, June). Youth learning machine learning through building models of athletic moves. In Proceedings of the 18th ACM international conference on interaction design and children (pp. 121–132).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Ng, D.T.K., Leung, J.K.L., Su, M.J., Yim, I.H.Y., Qiao, M.S., Chu, S.K.W. (2022). AI Literacy Education in Secondary Schools. In: AI Literacy in K-16 Classrooms. Springer, Cham. https://doi.org/10.1007/978-3-031-18880-0_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-18880-0_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-18879-4

  • Online ISBN: 978-3-031-18880-0

  • eBook Packages: EducationEducation (R0)

Publish with us

Policies and ethics