Revolutionizing Education with Industry 5.0: Challenges and Future Research Agendas

Authors

  • Mostafa Al-Emran The British University in Dubai
  • Mohammed A. Al-Sharafi Universiti Teknologi Malaysia

Abstract

Industry 5.0 refers to the collaboration of advanced technologies, such as robotics and intelligent solutions, with humans to improve efficiency and performance. In education, Industry 5.0 refers to the cooperation between these technologies and educators and students to enhance the efficiency and effectiveness of teaching and learning. Industry 5.0 technologies have the potential to revolutionize the way students learn, and teachers teach. This study provides an overview of Industry 5.0 in education and explores several challenges that might face its implementation. The study also presents a number of potential research agendas to help overcome these challenges and promote the successful adoption of Industry 5.0 in education. The research agendas cover large-scale areas, such as pedagogical approaches, technology adoption, technology integration and learning performance, social and emotional development, sustainability, partnerships and collaborations, and personalized learning. This research provides a valuable and timely understanding of Industry 5.0 and its implementation in education, considering the progression of Industry 5.0 technology development.

Author Biography

Mostafa Al-Emran, The British University in Dubai

Mostafa Al-Emran is an Assistant Professor in Computer Science at The British University in Dubai, UAE. He received his Ph.D. degree in Computer Science from Universiti Malaysia Pahang, the MSc degree in Informatics from The British University in Dubai (with distinction), and the BSc degree in Computer Science from Al Buraimi University College (with honors). He is among the top 2% scientists in the world, according to the reports published by Stanford University in October 2020, October 2021, and October 2022. He has published over 110 research articles, and his main contributions have appeared in highly reputed journals, such as International Journal of Information Management, Computers & Education, Computers in Human Behavior, Telematics and Informatics, IEEE Transactions on Engineering Management, Technology in Society, Journal of Enterprise Information Management, Interactive Learning Environments, International Journal of Human–Computer Interaction, Journal of Educational Computing Research, and Education and Information Technologies, among many others. Most of his publications were indexed under the ISI Web of Science and Scopus. He has edited a number of books published by Springer. His current research interests include Human-Computer Interaction, Knowledge Management, Educational Technology, and Artificial Intelligence.

References

Al-Emran, M. (2021). Evaluating the Use of Smartwatches for Learning Purposes through the Integration of the Technology Acceptance Model and Task-Technology Fit. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2021.1921481

Al-Emran, M., Al-Nuaimi, M. N., Arpaci, I., Al-Sharafi, M. A., & Anthony Jnr, B. (2022). Towards a wearable education: Understanding the determinants affecting students’ adoption of wearable technologies using machine learning algorithms. Education and Information Technologies, 1–20. https://doi.org/10.1007/S10639-022-11294-Z/METRICS

Al-Emran, M., Arpaci, I., & Al-Sharafi, M. A. (2023). Development and Initial Testing of Google Meet Use Scale (GMU-S) in Educational Activities During and Beyond the COVID-19 Pandemic. International Conference on Information Systems and Intelligent Applications, 759–770. https://doi.org/10.1007/978-3-031-16865-9_60/COVER

Al-Emran, M., Granić, A., Al-Sharafi, M. A., Ameen, N., & Sarrab, M. (2021). Examining the roles of students’ beliefs and security concerns for using smartwatches in higher education. Journal of Enterprise Information Management, 34(4), 1229–1251. https://doi.org/10.1108/JEIM-02-2020-0052

Al-Emran, M., & Mezhuyev, V. (2019). Examining the Effect of Knowledge Management Factors on Mobile Learning Adoption Through the Use of Importance-Performance Map Analysis (IPMA). International Conference on Advanced Intelligent Systems and Informatics, 449–458. https://doi.org/10.1007/978-3-030-31129-2_41

Al-Nuaimi, M. N., & Al-Emran, M. (2021). Learning management systems and technology acceptance models: A systematic review. Education and Information Technologies, 1–35. https://doi.org/10.1007/s10639-021-10513-3

Al-Sharafi, M. A., Al-Emran, M., Arpaci, I., Marques, G., Namoun, A., & Iahad, N. A. (2022). Examining the Impact of Psychological, Social, and Quality Factors on the Continuous Intention to Use Virtual Meeting Platforms During and beyond COVID-19 Pandemic: A Hybrid SEM-ANN Approach. International Journal of Human–Computer Interaction. https://doi.org/10.1080/10447318.2022.2084036

Al-Tahitah, A. N., Al-Sharafi, M. A., & Abdulrab, M. (2021). How COVID-19 Pandemic Is Accelerating the Transformation of Higher Education Institutes: A Health Belief Model View. In Studies in Systems, Decision and Control (Vol. 348). https://doi.org/10.1007/978-3-030-67716-9_21

Andres, B., Sempere-Ripoll, F., Esteso, A., & Alemany, M. M. E. (2022). Mapping between Industry 5.0 and Education 5.0. EDULEARN22 Proceedings, 1, 2921–2926. https://doi.org/10.21125/EDULEARN.2022.0739

Arpaci, I., Al-Emran, M., Al-Sharafi, M. A., & Shaalan, K. (2020). A Novel Approach for Predicting the Adoption of Smartwatches Using Machine Learning Algorithms. In Recent Advances in Intelligent Systems and Smart Applications (pp. 185–195). Springer.

Koohang, A., Nord, J., Ooi, K., Tan, G., Al-Emran, M., Aw, E., Baabdullah, A., Buhalis, D., Cham, T., Dennis, C., Dutot, V., Dwivedi, Y., Hughes, L., Mogaji, E., Pandey, N., Phau, I., Raman, R., Sharma, A., Sigala, M., … Wong, L. (2023). Shaping the metaverse into reality: multidisciplinary perspectives on opportunities, challenges, and future research. Journal of Computer Information Systems.

Leng, J., Sha, W., Wang, B., Zheng, P., Zhuang, C., Liu, Q., Wuest, T., Mourtzis, D., & Wang, L. (2022). Industry 5.0: Prospect and retrospect. Journal of Manufacturing Systems, 65, 279–295. https://doi.org/10.1016/J.JMSY.2022.09.017

Maddikunta, P. K. R., Pham, Q. V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., Ruby, R., & Liyanage, M. (2022). Industry 5.0: A survey on enabling technologies and potential applications. Journal of Industrial Information Integration, 26, 100257. https://doi.org/10.1016/J.JII.2021.100257

Mohd Rahim, N. I., A. Iahad, N., Yusof, A. F., & A. Al-Sharafi, M. (2022). AI-Based Chatbots Adoption Model for Higher-Education Institutions: A Hybrid PLS-SEM-Neural Network Modelling Approach. Sustainability, 14(19), 12726. https://doi.org/10.3390/SU141912726

Wahdan, A., Hantoobi, S., Al-Emran, M., & Shaalan, K. (2021). Early Detecting Students at Risk Using Machine Learning Predictive Models. International Conference on Emerging Technologies and Intelligent Systems, 322, 321–330. https://doi.org/10.1007/978-3-030-85990-9_27

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Published

2023-01-12

Issue

Vol. 6 No. 3 (2022)

Section

Articles

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