Learning factory synergy: applied learning and problem-based pedagogy in the digital transformation ecosystem

Yau, P. C.Y. , Tso, E. and Wong, D. (2022) Learning factory synergy: applied learning and problem-based pedagogy in the digital transformation ecosystem. In: Arai, K. (ed.) Proceedings of the Future Technologies Conference. Series: Lecture Notes in Networks and Systems, 3 (561). Springer, pp. 734-741. ISBN 9783031183430 (doi: 10.1007/978-3-031-18344-7_52)

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The current manufacturing process has changed drastically in the last decade due to the many changes in both hardware and software in computing. It is thus worth investigating how people make use of these latest technologies in one single workplace to fully utilize the power given by the manufacturing business process, from learning, production, and then to further development. In this paper, we discuss the challenges and difficulties of how workplace synergy can be synchronous with academia in the form of research centers. We surveyed some key personnel who partnered with higher education institutes for collaboration work. Based on their experience, we would like to showcase and discuss the core factors to make the academic-industrial collaboration work successful. We will discuss the project plan, partner relationship, and knowledge sharing process between industry supporters, academic staff, and the students; including the pedagogy used and how the digital transformation takes place in the learning factory ecosystem and then transferred the output to the real world. We conclude that to achieve a good workplace synergy in the learning factory ecosystem, four elements are essential: a real-world scenario, a work-based learning pedagogy, a long-term industry partner, a knowledgeable manager, who is a professional with commercial experience, and with a technically trained background. We believed vocational education, applied learning, work-based learning and teaching are several critical educational elements to enhance economic growth.

Item Type:Book Sections
Additional Information:This research is supported by the Macao Polytechnic University research grant (Project code: RP/FCA-02/2022). The research of the third author is also supported by the National Research Foundation of Korea (NRF) grant funded by the Ministry of Science and ICT (MSIT), Korea (No. 2020R1F1A1A01070666).
Glasgow Author(s) Enlighten ID:Yau, Dr Peter C Y
Authors: Yau, P. C.Y., Tso, E., and Wong, D.
Subjects:L Education > L Education (General)
T Technology > T Technology (General)
College/School:College of Science and Engineering > School of Computing Science

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