- Apply for Authority
- E-ISSN2233-5382
- KCI
E-ISSN : 2233-5382
A Study on Artificial Intelligence Education Design for Business Major Students
SUH, Eung-Kyo
- Downloaded
- Viewed
Abstract
Purpose: With the advent of the era of the 4th industrial revolution, called a new technological revolution, the necessity of fostering future talents equipped with AI utilization capabilities is emerging. However, there is a lack of research on AI education design and competency-based education curriculum as education for business major. The purpose of this study is to design AI education to cultivate competency-oriented AI literacy for business major in universities. Research design, data and methodology: For the design of AI basic education in business major, three expert Delphi surveys were conducted, and a demand analysis and specialization strategy were established, and the reliability of the derived design contents was verified by reflecting the results. Results: As a result, the main competencies for cultivating AI literacy were data literacy, AI understanding and utilization, and the main detailed areas derived from this were data structure understanding and processing, visualization, web scraping, web crawling, public data utilization, and concept of machine learning and application. Conclusions: The educational design content derived through this study is expected to help establish the direction of competency-centered AI education in the future and increase the necessity and value of AI education by utilizing it based on the major field.
- keywords
- AI Education, Data Literacy, Business Major, Public Data
Reference
Cronbach, L. J., & Shavelson, R. J. (2004). My Current Thoughts on Coefficient Alpha and Successor Procedures. Educational and Psychological Measurement, 64(3), 391–418.
Diez, D., Barr, C., & Ç etinkaya-Rundel, M. (2016). OpenIntro Statistics (3rd ed.). Retrieved July 2, 2016, from https://doi.org/10.19232/uv4pb.2016.2.90
Frey, C. B., & Osborne, M. A. (2017). The future of employment:How susceptible are jobs to computerization. Technological forecasting and social change, 114(c), 254-280.
Graham, R. (2018). The global state of the art in engineering education. Cambridge, USA: Massachusetts Institute of Technology (MIT) Report, Retrieved Apr 10, 2021, from https://www.cti-commission.fr/wp-content/uploads/2017/10/Phase-1-engineering-education-benchmarking-study-2017.pdf
Hong, J. Y., & Kim, Y. S. (2020). Development of AI Data Science Education Program to Foster Data Literacy of Elementary School Students. Journal of The Korean Association of Information Education, 24(6), 633-641.
Institute of Information and Communications Technology Planning and Evaluation (IITP). (2017). Japanese AI policy isomorphism and implementation strategy. IITP Global ICT R&D Policy Trends, 2017(1), 1-24.
Jho, H. K. (2017). The Changes of Higher Education and the Tasks of General Education according to the Fourth Industrial Revolution. Korean Journal of General Education, 11(2), 53-89.
Kim, D. G., Kim, J. J., Kim, H. J., Kim, Y. S., & Choi, J. H. (2017). Future Job Prospects of the 4th Industrial Revolution. Chungcheongbuk-do, Korea: Korea Employment Information Service Report.
Kim, G. B. (2018). Humanities and History as a Liberal Arts in the Age of AI. Journal of history and culture, 67, 241-268.
Kim, S. A. (2019). Another Perspective for Education in the Age of Artificial Intelligence. Journal of Educational Principle, 24(1), 83-105.
Kim, Y. S. (2019). Global Trend of AI Talent Development Policy in Major Countries. Monthly Software Oriented Society, 62(8), 29-36.
Korea Foundation for the Advancement of Science and Creativity (KOFAC). (2019). 2019 Global SW Education Conference Issue Paper: Rethinking SW Education in the Era of AI. Seoul, Korea: Korea Science and Creativity Foundation.
Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel psychology, 28(4), 563-575.
Lee, E. K. (2020). A Comparative Analysis of Contents Related to Artificial Intelligence in National and International K-12. The Journal of Korean Association of Computer Education, 23(1), 37-44.
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. Hawaii, USA: Association for Computing Machinery.
Okoli, C., & Pawlowski, S. D. (2004). The Delphi method as a research tool: an example, design considerations and applications. Information & Management, 42(1), 15-29.
Park, D. R., Ahn, J. M., Jang, J. H., Yu, W. J., Kim, W. Y., Bae, Y. K., & Yoo, I. H. (2020). The Development of Software Teaching-Learning Model based on Machine Learning Platform. Journal of The Korea Association of Information Education, 24(1), 49-57.
Park, S. H. (2019). A Study on the Determination of Programming Language for Software Basic Education of Non-majors. The Journal of information systems, 28(4), 403-424.
Park, S. H. (2019). Design of Algorithm Thinking-Based Software Basic Education for Nonmajors. The Journal of Industrial Distribution & Business, 10(11), 71-80.
Rauch, W. G. (1979). The decision Delphi. Technological Forecasting and Social Change, 15, 159-169.
Richardson, I., & Delaney, Y. (2009). Problem based learning in the software engineering classroom. Proceedings of the 22nd Conference on Software Engineering Education and Training IEEE, (pp. 174-181). Hyderabad, India.
Roll, I., & Wylie, R. (2016). Evolution and revolution in artificial intelligence in education. International Journal of Artificial Intelligence Education, 26(2), 582-599.
Rowe, G., Wright, G., & Bolger, F. (1991). Delphi-a reevaluation of research and theory. Technological Forecasting and Social Change, 39(3), 235-251.
Ryu, H. I. & Cho, J. W. (2021). Development of Artificial Intelligence Education System for K-12 Based on 4P. Journal of Digital Convergence, 19(1), 141-149.
Ryu, M. Y., & Han, S. K. (2019). AI Education Programs for Deep-Learning Concepts. Journal of The Korean Association of Information Education, 23(6), 583–590.
Streiner, D. L., & Norman, G. R. (2015). Health measurement scales: A practical guide to their development and use (5th ed.). London, UK: Oxford.
Sung, J. S., Kim, S. H., & Kim, H. C. (2015). Analysis of Art and Humanity Major Learners Features in Programming Class. The Journal of Korean Association of Computer Education, 18(3), 25-35.
The Ministry of Science and ICT (MSIT). (2019). The artificial intelligence national strategy. Retrieved Apr 22, 2021, from https://www.msit.go.kr/bbs/view.do?sCode=user&mId=113&mPid=112&bbsSeqNo=94&nttSeqNo=2405727
World Economic Forum (WEF). (2016). World Economic Forum Annual Meeting 2016: Mastering the Fourth Industrial Revolution. Retrieved Jan 20-23, 2016, from http://www3.weforum.org/docs/WEF_AM16_Report.pdf
World Economic Forum (WEF). (2018). The Future of Jobs Report 2018. Retrieved Mar 15, 2021, from http://www3.weforum.org/docs/WEF_Future_of_Jobs_2018.pdf
Woo, H. S., Lee, H. J., Kim, J. M., & Lee, W. K. (2020). Analysis of Artificial Intelligence Curriculum of SW Universities. The Journal of Korean Association of Computer Education, 23(2), 13-20.
Woudenberg, F. (1991). An evaluation of Delphi. Technological Forecasting and Social Change, 40, 131-150.
Yoo, I. H., Kim, W. I., Jeon, J. C., Yu, W. J., & Bae, Y. K. (2020). A Study on the Future Directions according to Analysis of Necessity of AI Education. Journal of The Korean Association of Information Education, 24(5), 423-431.
Zhao, W., & Chang, Hong. (2019). The Zhilong X Plan allows artificial intelligence to empower the whole process of education. Retrieved Apr 10, 2021, from http://world.people.com.cn/n1/2019/0111/c351610-30516905.html
- Downloaded
- Viewed
- 0KCI Citations
- 0WOS Citations