This article discusses the pressing need to integrate artificial intelligence (AI) into education to facilitate customizable, individualized, and on-demand learning pathways. At the same time, while AI has the potential to expand the learner base and improve learning outcomes, the development of NACE Competencies and durable skills – communication, critical thinking, creativity, leadership, adaptability, and emotional intelligence - must be purposefully integrated in curriculum design now more than ever. Recent studies have shown that AI-driven learning pathways can achieve outcomes more quickly, but this comes at the cost of the development of durable skills. Therefore, traditional student-to-student and student-to-teacher interactions must be prioritized. As such, this study proposes a balanced approach to curriculum design to ensure the best outcomes for learners, where durable skill development is prioritized alongside subject-specific skills and rote memorization. Additionally, the article highlights the need for a combination of Just in Time Training (JITT) approaches, facilitated by AI technology, to reach the implementation of durable skills. The article concludes by questioning how to develop human skills in an increasingly AI-driven education system and emphasizes the importance of curriculum design and traditional learning approaches in creating a cohesive learning experience that develops durable skills in students. It is necessary to recognize that AI-driven education cannot replace the development of human skills, and that traditional interactions play a crucial role in developing these skills.
Hutson, J.; Ceballos, J. Rethinking education in the age of AI: The importance of developing durable skills in the industry 4.0. Journal of Information Economics, 2023, 1, 9. https://doi.org/10.58567/jie01020002
AMA Style
Hutson J, Ceballos J. Rethinking education in the age of AI: The importance of developing durable skills in the industry 4.0. Journal of Information Economics; 2023, 1(2):9. https://doi.org/10.58567/jie01020002
Chicago/Turabian Style
Hutson, James; Ceballos, Jason 2023. "Rethinking education in the age of AI: The importance of developing durable skills in the industry 4.0" Journal of Information Economics 1, no.2:9. https://doi.org/10.58567/jie01020002
APA style
Hutson, J., & Ceballos, J. (2023). Rethinking education in the age of AI: The importance of developing durable skills in the industry 4.0. Journal of Information Economics, 1(2), 9. https://doi.org/10.58567/jie01020002
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Abrardi, L., Cambini, C., & Rondi, L. (2022). Artificial intelligence, firms and consumer behavior: A survey. Journal of Economic Surveys, 36(4), 969-991. https://doi.org/10.1111/joes.12455
Alam, A. (2022). Employing Adaptive Learning and Intelligent Tutoring Robots for Virtual Classrooms and Smart Campuses: Reforming Education in the Age of Artificial Intelligence. In Advanced Computing and Intelligent Technologies: Proceedings of ICACIT 2022 (pp. 395-406). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-19-2980-9_32
Ali, S. M., Hasan, Z. J., Hamdan, A., & Al-Mekhlaf, M. (2023). Artificial Intelligence (AI) in the Education of Accounting and Auditing Profession. In Digitalisation: Opportunities and Challenges for Business: Volume 2 (pp. 656-664). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-031-26956-1_61
Anderson, J. (2017). A free, teacher-less university in France is schooling thousands of future-proof programmers. Quartz. September 4, 2017, Retrieved from: https://qz.com/1054412/a-french-billionaires-free-teacher-less-university-is-designing-thousands-of-future-proof-employees
Autor, D. (2022). The labor market impacts of technological change: From unbridled enthusiasm to qualified optimism to vast uncertainty (No. w30074). National Bureau of Economic Research. https://doi.org/10.3386/w30074
Bennani, S., Maalel, A., & Ben Ghezala, H. (2022). Adaptive gamification in E‐learning: A literature review and future challenges. Computer Applications in Engineering Education, 30(2), 628-642. https://doi.org/10.1002/cae.22477
Bradberry, L. A., & De Maio, J. (2019). Learning by doing: The long-term impact of experiential learning programs on student success. Journal of Political Science Education, 15(1), 94-111. https://doi.org/10.1080/15512169.2018.1485571
Bühler, M. M., Jelinek, T., & Nübel, K. (2022). Training and Preparing Tomorrow’s Workforce for the Fourth Industrial Revolution. Education Sciences, 12(11), 782. https://doi.org/10.3390/educsci12110782
Campello de Souza, B., Serrano de Andrade Neto, A., & Roazzi, A. (2023). Are the New AIs Smart Enough to Steal Your Job? IQ Scores for ChatGPT, Microsoft Bing, Google Bard and Quora Poe. IQ Scores for ChatGPT, Microsoft Bing, Google Bard and Quora Poe (April 7, 2023). https://doi.org/10.2139/ssrn.4412505
Chen, X., Cheng, G., Zou, D., Zhong, B., & Xie, H. (2023). Artificial Intelligent Robots for Precision Education. Educational Technology & Society, 26(1), 171-186. https://doi.org/10.1007/s10639-022-11209-y
Cropley, D. H. (2019). Homo problematis solvendis–problem-solving man: a history of human creativity. Springer. https://doi.org/10.1007/978-981-13-3101-5
Devi, J. S., Sreedhar, M. B., Arulprakash, P., Kazi, K., & Radhakrishnan, R. (2022). A path towards child-centric Artificial Intelligence based Education. International Journal of Early Childhood, 14(03), 2022.
Dykstra, M., & Lasscock, B. (2021). Applied Artificial Intelligence in the Subsurface. In Abu Dhabi International Petroleum Exhibition & Conference. OnePetro. https://doi.org/10.2118/207242-ms
Fake, H., & Dabbagh, N. (2020). Personalized learning within online workforce learning environments: Exploring implementations, obstacles, opportunities, and perspectives of workforce leaders. Technology, Knowledge and Learning, 25, 789-809. https://doi.org/10.1007/s10758-020-09441-x
Ferreira, M., Martinsone, B., & Talić, S. (2020). Promoting sustainable social emotional learning at school through relationship-centered learning environment, teaching methods and formative assessment. Journal of Teacher Education for Sustainability, 22(1), 21-36. https://doi.org/10.2478/jtes-2020-0003
Harsma, E., Manderfeld, M., & Miller, C. L. (2021). Project-Based Learning Lesson Template. Maverick Learning and Educational Applied Research Nexus.
Hutson, J., Macdonald, E., Young, L., Edele, S., & Smentkowski, C. (2022). Fostering Durable Skills Development: Leveraging Student Worker Programs. Journal of Organizational Psychology, 22(3). https://doi.org/10.33423/jop.v22i3.5649
Hutson, J., Valenzuela, M., Hosto-Marti, B., & Wright, S. (2023). The Role of Higher Education in Developing Durable Skills: Reframing General Education. Journal of Organizational Psychology, 23(1). https://doi.org/10.33423/jop.v23i1.5851
Jain, H., Padmanabhan, B., Pavlou, P. A., & Raghu, T. S. (2021). Editorial for the special section on humans, algorithms, and augmented intelligence: The future of work, organizations, and society. Information Systems Research, 32(3), 675-687. https://doi.org/10.1287/isre.2021.1046
Jaiswal, A., Arun, C. J., & Varma, A. (2022). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. The International Journal of Human Resource Management, 33(6), 1179-1208. https://doi.org/10.1080/09585192.2021.1891114
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., ... & Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kester, L., Kirschner, P. A., van Merriënboer, J. J., & Baumer, A. (2001). Just-in-time information presentation and the acquisition of complex cognitive skills. Computers in human behavior, 17(4), 373-391. https://doi.org/10.1016/s0747-5632(01)00011-5
Kioupi, V., & Voulvoulis, N. (2019). Education for sustainable development: A systemic framework for connecting the SDGs to educational outcomes. Sustainability, 11(21), 6104. https://doi.org/10.3390/su11216104
Ke, F., & Liu, L. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. Educational Technology Research and Development, 69(2), 669-693.
Knoblauch, C. (2023). Concepts of Experiential Learning in Digital Collaboration: New Perspectives for the Higher Education Sector. International Journal of Advanced Corporate Learning, 16(1). https://doi.org/10.3991/ijac.v16i1.35871
Krause, A. J., & Moore, S. Y. (2022). Creating an online peer-to-peer mentoring program: Promoting student relationships, engagement, and satisfaction during the era of COVID-19. College Teaching, 70(3), 296-308. https://doi.org/10.1080/87567555.2021.1925624
Li, L. (2022). Reskilling and upskilling the future-ready workforce for industry 4.0 and beyond. Information Systems Frontiers, 1-16. https://doi.org/10.1007/s10796-022-10308-y
Little, J. W. (2012). Professional community and professional development in the learning-centered school. In Teacher learning that matters (pp. 42-64). Routledge.
Majid, S., Eapen, C. M., Aung, E. M., & Oo, K. T. (2019). The Importance of Soft Skills for Employability and Career Development: Students and Employers' Perspectives. IUP Journal of Soft Skills, 13(4).
McQuillin, S. D., Lyons, M. D., Becker, K. D., Hart, M. J., & Cohen, K. (2019). Strengthening and expanding child services in low resource communities: The role of task‐shifting and just‐in‐time training. American journal of community psychology, 63(3-4), 355-365. https://doi.org/10.1002/ajcp.12314
Miller, E. C., & Krajcik, J. S. (2019). Promoting deep learning through project-based learning: A design problem. Disciplinary and Interdisciplinary Science Education Research, 1(1), 1-10. https://doi.org/10.1186/s43031-019-0009-6
Müller, A. M., Goh, C., Lim, L. Z., & Gao, X. (2021). Covid-19 emergency elearning and beyond: Experiences and perspectives of university educators. Education Sciences, 11(1), 19. https://doi.org/10.3390/educsci11010019
National Research Council. (2012). Education for life and work: Developing transferable knowledge and skills in the 21st century. National Academies Press. https://doi.org/10.17226/13398
Ramadan, A. B., Liu, F., & Stapleton, C. (2021). A Case Study: Assessment of Civic Learning Knowledge amongst Informatics Faculty and Undergraduate Students' Attendees of Civic Workshops at Mercer University. Journal of Service-Learning in Higher Education, 12, 59-71. https://doi.org/10.1002/ncr.179
Rutherford, S. (2020). Using desirable difficulty concepts to enhance durable learning in design education. art, design & communication in higher Education, 19(1), 65-79. https://doi.org/10.1386/adch_00014_1
Schislyaeva, E. R., & Saychenko, O. A. (2022). Labor Market Soft Skills in the Context of Digitalization of the Economy. Social Sciences, 11(3), 91. https://doi.org/10.3390/socsci11030091
Seo, K., Tang, J., Roll, I., Fels, S., & Yoon, D. (2021). The impact of artificial intelligence on learner–instructor interaction in online learning. International journal of educational technology in higher education, 18, 1-23. https://doi.org/10.1186/s41239-021-00292-9
Sin, D. Y. E., Chew, T. C. T., Chia, T. K., Ser, J. S., Sayampanathan, A., & Koh, G. C. H. (2019). Evaluation of constructing care collaboration-nurturing empathy and peer-to-peer learning in medical students who participate in voluntary structured service learning programmes for migrant workers. BMC Medical Education, 19, 1-13. https://doi.org/10.1186/s12909-019-1740-6
Singh, T. (2023). The Impact of Large Language Multi-Modal Models on the Future of Job Market. arXiv preprint arXiv:2304.06123.
Slater, S., & Inagawa, M. (2019). Bridging cultural divides: Role reversal as pedagogy. Journal of Teaching in International Business, 30(3), 269-308. https://doi.org/10.1080/08975930.2019.1698395
Stephen, O. O., & Festus, O. O. (2022). Utilization of work-based learning program to develop employability skill of workforce (craftsmen) in construction industry towards industrial development. Indonesian Journal of Educational Research and Technology, 2(3), 179-188. https://doi.org/10.17509/ijert.v2i3.43970
Taecharungroj, V. (2023). “What Can ChatGPT Do?” Analyzing Early Reactions to the Innovative AI Chatbot on Twitter. Big Data and Cognitive Computing, 7(1), 35. https://doi.org/10.3390/bdcc7010035
Therisa Beena, K. K., & Sony, M. (2022). Student workload assessment for online learning: An empirical analysis during Covid-19. Cogent Engineering, 9(1), 2010509. https://doi.org/10.1080/23311916.2021.2010509
Trajtenberg, M. (2018). AI as the next GPT: a Political-Economy Perspective (No. w24245). National Bureau of Economic Research. https://doi.org/10.3386/w24245
Tucker, C. R. (2012). Blended learning in grades 4–12: Leveraging the power of technology to create student-centered classrooms. Corwin Press.
Vogler, J. S., Thompson, P., Davis, D. W., Mayfield, B. E., Finley, P. M., & Yasseri, D. (2018). The hard work of soft skills: augmenting the project-based learning experience with interdisciplinary teamwork. Instructional Science, 46, 457-488. https://doi.org/10.1007/s11251-017-9438-9
Walkington, C., & Bernacki, M. L. (2020). Appraising research on personalized learning: Definitions, theoretical alignment, advancements, and future directions. Journal of Research on Technology in Education, 52(3), 235-252. https://doi.org/10.1080/15391523.2020.1747757
Wright, M. C., McKay, T., Hershock, C., Miller, K., & Tritz, J. (2014). Better than expected: Using learning analytics to promote student success in gateway science. Change: The Magazine of Higher Learning, 46(1), 28-34. https://doi.org/10.1080/00091383.2014.867209
Xu, Y., Wang, D., Collins, P., Lee, H., & Warschauer, M. (2021). Same benefits, different communication patterns: Comparing Children's reading with a conversational agent vs. a human partner. Computers & Education, 161, 104059. https://doi.org/10.1016/j.compedu.2020.104059
Yilmaz, Y., Papanagnou, D., Fornari, A., & Chan, T. M. (2022). The Learning Loop: Conceptualizing Just‐in‐Time Faculty Development. AEM Education and Training, 6(1), e10722. https://doi.org/10.1002/aet2.10722
Yu, X., Xu, S., & Ashton, M. (2023). Antecedents and outcomes of artificial intelligence adoption and application in the workplace: The socio-technical system theory perspective. Information Technology & People, 36(1), 454-474. https://doi.org/10.1108/itp-04-2021-0254
Zhao, Z., Xu, P., Scheidegger, C., & Ren, L. (2021). Human-in-the-loop extraction of interpretable concepts in deep learning models. IEEE Transactions on Visualization and Computer Graphics, 28(1), 780-790. https://doi.org/10.1109/tvcg.2021.3114837
Zhang, L., Basham, J. D., & Yang, S. (2020). Understanding the implementation of personalized learning: A research synthesis. Educational Research Review, 31, 100339. https://doi.org/10.1016/j.edurev.2020.100339
Zheng, W., Shen, T., Chen, X., & Deng, P. (2022). Interpretability application of the Just-in-Time software defect prediction model. Journal of Systems and Software, 188, 111245. https://doi.org/10.1016/j.jss.2022.111245