Evaluation of Korea’s National-Level SWᐧAI Education Camp Program for K-12 Students

Yunjae Jang (1), Hosung Woo (2), Hansung Kim (3)
(1) Div. of Liberal Arts and General Education, Gangneung-Wonju National University, Gangneung, Republic of Korea
(2) Department of EduTech, Graduate School, Korea National Open University, Seoul, Republic of Korea
(3) Department of Software Engineering, The Cyber University of Korea, Seoul, Republic of Korea
Fulltext View | Download
How to cite (IJASEIT) :
[1]
Y. Jang, H. Woo, and H. Kim, “Evaluation of Korea’s National-Level SWᐧAI Education Camp Program for K-12 Students”, Int. J. Adv. Sci. Eng. Inf. Technol., vol. 15, no. 3, pp. 701–707, Jun. 2025.
This study explores ways to enhance digital competencies by conducting an in-depth analysis of 255 representative cases from the Digital NewSac educational programs implemented in Korea in 2022. The research selected 255 programs—those most frequently offered at each school level—from a total of 1,116 programs submitted by 89 out of 90 institutions. These programs were classified and analyzed based on Bloom’s Digital Taxonomy, a digital literacy framework, and the usage status of programming languages and computing tools. The analysis revealed that approximately 53% of the programs focused on “Applying,” while 42.7% focused on “Creating,” whereas the levels of “Understanding,” “Analyzing,” and “Evaluating” accounted for less than 4% of the overall programs. In terms of educational content, the areas of “Utilization of Digital Devices” and “Utilization of Artificial Intelligence” accounted for 74.5% and 68.2%, respectively, while “Digital Information Protection” and “Digital Communication” had very low proportions, below 1%. The analysis of educational tools revealed that 66.3% of the programs utilized block-based languages, 17.6% employed text-based languages, and physical computing tools were used in 82% of the cases. These findings suggest that the Digital NewSac programs remain primarily experience-based, limiting the development of higher-order cognitive and specialized programming skills, and thus propose the need for future educational program designs that, in conjunction with the national curriculum, incorporate specialized areas such as digital ethics and data science tailored to students' levels.

D. Silver et al., "Mastering the game of Go with deep neural networks and tree search," Nature, vol. 529, no. 7587, pp. 484-489, Jan. 2016, doi: 10.1038/nature16961.

B. R. Kiran et al., "Deep reinforcement learning for autonomous driving: A survey," IEEE Trans. Intell. Transp. Syst., vol. 23, no. 6, pp. 4909-4926, Jun. 2022, doi: 10.1109/TITS.2021.3054625.

Y. K. Dwivedi et al., "Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions," Technol. Forecast. Soc. Change, vol. 192, Art. no. 122579, Jul. 2023, doi: 10.1016/j.techfore.2023.122579.

M. Mauro et al., "Digital transformation in healthcare: Assessing the role of digital technologies for managerial support processes," Technol. Forecast. Soc. Change, vol. 209, Art. no. 123781, Dec. 2024, doi:10.1016/j.techfore.2024.123781.

O. Selesi-Aina et al., "The future of work: A human-centric approach to AI, robotics, and cloud computing," SSRN, Art. no. 5001604, Oct. 2024, doi: 10.9734/jerr/2024/v26i111315.

S. Das and V. Gupta, "Revolutionizing healthcare with AI and deep learning: Smart health monitoring for early detection and enhanced patient care," Front. Health Inform., pp. vol.13, no.8, pp 2538-2554, Jan. 2024.

D. T. K. Ng et al., "Conceptualizing AI literacy: An exploratory review," Comput. Educ. Artif. Intell., vol. 2, Art. no. 100041, Jan. 2021, doi: 10.1016/j.caeai.2021.100041.

K. Lee et al., "Special topic: The impact of ChatGPT in society, business, and academia," Asia Pac. J. Inf. Syst., vol. 33, no. 4, pp. 957-976, Dec. 2023, doi: 10.14329/apjis.2023.33.4.957.

Y. Jang, I. Yoon, and H. Woo, "Development of AI liberal arts curriculum for the general public," Int. J. Adv. Sci. Eng. Inf. Technol., vol. 13, no. 5, pp. 1978-1983, Oct. 2023, doi:10.18517/ijaseit.13.5.19057.

T. K. F. Chiu et al., "What are artificial intelligence literacy and competency? A comprehensive framework to support them," Comput. Educ. Open, vol. 6, Art. no. 100171, Jun. 2024, doi:10.1016/j.caeo.2024.100171.

L. Casal-Otero et al., "AI literacy in K-12: A systematic literature review," Int. J. STEM Educ., vol. 10, no. 1, Art. no. 29, Apr. 2023, doi:10.1186/s40594-023-00418-7.

J. Southworth et al., "Developing a model for AI across the curriculum: Transforming the higher education landscape via innovation in AI literacy," Comput. Educ. Artif. Intell., vol. 4, Art. no. 100127, Jan. 2023, doi: 10.1016/j.caeai.2023.100127.

K. Stolpe and J. Hallström, "Artificial intelligence literacy for technology education," Comput. Educ. Open, vol. 6, Art. no. 100159, Jun. 2024, doi: 10.1016/j.caeo.2024.100159.

D. T. K. Ng, E. K. C. Chan, and C. K. Lo, "Opportunities, challenges and school strategies for integrating generative AI in education," Comput. Educ. Artif. Intell., vol. 8, Art. no. 100373, Jun. 2025, doi: 10.1016/j.caeai.2025.100373.

Y. H. Cheah, J. Lu, and J. Kim, "Integrating generative artificial intelligence in K-12 education: Examining teachers' preparedness, practices, and barriers," Comput. Educ. Artif. Intell., vol. 8, Art. no. 100363, Jun. 2025, doi: 10.1016/j.caeai.2025.100363.

P. Chandel and F. V. Lim, "Generative AI and literacy development in the language classroom: A systematic review of literature," Ubiquitous Learn., vol. 18, no. 2, pp. 31-49, 2025, doi: 10.18848/1835-9795/CGP/v18i02/31-49.

J. Bae, J. Lee, and J. Cho, "Analysis of AI ethical competence to computational thinking," JOIV Int. J. Inform. Vis., vol. 6, no. 2-2, pp. 506-515, Aug. 2022, doi: 10.30630/joiv.6.2-2.1126.

I. Celik, "Exploring the determinants of artificial intelligence (AI) literacy: Digital divide, computational thinking, cognitive absorption," Telemat. Inform., vol. 83, Art. no. 102026, Sep. 2023, doi: 10.1016/j.tele.2023.102026.

P. Svoboda, "Digital competencies and artificial intelligence for education: Transformation of the education system," Int. Adv. Econ. Res., vol. 30, no. 2, pp. 227-230, May 2024, doi: 10.1007/s11294-024-09896-z.

H. Moon and Y. Lee, "The effects of data literacy-based SW convergence education on elementary school student's computational thinking," J. Korean Assoc. Comput. Educ., vol. 27, no. 4, pp. 247-259, Jul. 2024, doi: 10.32431/kace.2024.27.4.019.

Ministry of Education, "Informatics curriculum," Ministry of Education, Rep. no. 2022-33, 2022.

"NewSac." Accessed: Feb. 22, 2025. [Online]. Available: https://newsac.kosac.re.kr/

Y. Jeong and Y. Sung, "A study on development strategies through performance analysis of the digital new software · AI camp," KOFAC, Rep. no. 23-B552111-00002-01, Jul. 2023. [Online]. Available: https://www.kosac.re.kr/menus/244/boards/457/posts/39216

S. Park and E. Yang, "Study on the effectiveness of SW and AI education camps," KOFAC, Rep. no. D23050004, May 2023. [Online]. Available: https://www.kosac.re.kr/menus/244/boards/457/posts/39224

A. Churches, "Bloom's digital taxonomy." Accessed: Feb. 22, 2025. [Online]. Available: http://burtonslifelearning.pbworks.com/f/BloomDigitalTaxonomy2001.pdf

J. Kim et al., "Development of digital literacy education guidelines linked to curriculum," KERIS, Rep. no. CR 2023-1, 2023.

C. U. Park and H. J. Kim, "Measurement of inter-rater reliability in systematic review," Hanyang Med. Rev., vol. 35, no. 1, pp. 44-49, Feb. 2015, doi: 10.7599/hmr.2015.35.1.44.

A. S. George, "Preparing students for an AI-driven world: Rethinking curriculum and pedagogy in the age of artificial intelligence," Partn. Univ. Innov. Res. Publ., vol. 1, pp. 112-136, 2023, doi:10.5281/zenodo.10245675.

R. Zheng et al., "The impact of artificial general intelligence-assisted project-based learning on students' higher order thinking and self-efficacy," IEEE Trans. Learn. Technol., vol. 17, pp. 2153-2160, 2024, doi: 10.1109/TLT.2024.3488086.

T. K. F. Chiu, "A holistic approach to the design of artificial intelligence (AI) education for K-12 schools," TechTrends, vol. 65, no. 5, pp. 796-807, Sep. 2021, doi: 10.1007/s11528-021-00637-1.

J. Kim, H. Lee, and Y. H. Cho, "Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education," Educ. Inf. Technol., vol. 27, no. 5, pp. 6069-6104, Jun. 2022, doi: 10.1007/s10639-021-10831-6.

H. S. Kim et al., "Development and application of education program on understanding artificial intelligence and social impact," J. Korean Assoc. Comput. Educ., vol. 23, no. 2, pp. 21-29, Mar. 2020.

E. Gebre, "Conceptions and perspectives of data literacy in secondary education," Br. J. Educ. Technol., vol. 53, no. 5, pp. 1080-1095, 2022, doi: 10.1111/bjet.13246.

J. Jeong and Y. Lee, "Development of data literacy competency system for K-12," Int. J. Adv. Sci. Eng. Inf. Technol., vol. 14, no. 6, pp. 2130-2140, Dec. 2024, doi: 10.18517/ijaseit.14.6.12373.

D. Weintrop and U. Wilensky, "Transitioning from introductory block-based and text-based environments to professional programming languages in high school computer science classrooms," Comput. Educ., vol. 142, Art. no. 103646, Dec. 2019, doi:10.1016/j.compedu.2019.103646.

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
    2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
    3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).