Supporting Mass Collaborative Learning Communities Through Digital Innovation Hubs

Zamiri, Majid; Sarraipa, Joao; Marcelino-Jesus, Elsa; Jardim-Goncalves, Ricardo

doi:10.1109/cscs59211.2023.00064

Cited by 2 publications

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“…Generally, DIHs are created and built up by research and technology organizations (RTOs) and/or university labs and serve as not-for-profit organizations, service points, and one-stop shops (that provide a number of different services or might sell some products in one place). DIHs foster the mindset of developing an innovative ecosystem where all economic sectors (e.g., companies) and nonprofit organizations (e.g., public sectors, training institutes) can reap the benefits of digital investment and (digital) TT [12]. In this study, the focus of attention is on (digital) TT to economic sectors, particularly companies.…”

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confidence: 99%

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A Learning Framework for Supporting Digital Innovation Hubs

et al. 2023

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With the increasing demand for digital transformation and (digital) technology transfer (TT), digital innovation hubs (DIHs) are the new piece of the puzzle of our economy and industries’ landscapes. Evidence shows that DIHs can provide good opportunities to access needed innovations, technologies, and resources at a higher level than other organizations that can normally access them. However, it is critically important to note that DIHs are still evolving, under research, and under development. That is, there are many substantial aspects of DIHs that should be considered. For example, DIHs must cater to a wide spectrum of needs for TT. From this perspective, the contribution of this work is proposing a generic and flexible learning framework, aiming to assist DIHs in providing suitable education, training, and learning services that support the process of (digital) TT to companies. The proposed learning framework was designed, evaluated, and improved with the support of two EU projects, and these processes are discussed in brief. The primary and leading results gained in this way show that the learning framework has immense potential for application to similar cases, and it can facilitate and expedite the process of TT to companies. The study is concluded with some directions for future works.

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Section: Introductionmentioning

confidence: 99%

“…Data collection presents the methods and techniques we used for providing evidence to support the predictions derived from the hypothesis, which include published literature sources (e.g., our prior related publications) [12,15] and observations (watching and recording) of prior and existing use cases.…”

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A Learning Framework for Supporting Digital Innovation Hubs

et al. 2023

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Integration of AI Use Cases in Training to Support Industry 4.0

Nazarenko,

Zamiri,

Sarraipa

et al. 2024

JAIT

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As the demand for Artificial Intelligence (AI) continues to grow across industries, there is a need for effective training programs that support the successful deployment of AI in various organizational contexts. This study aims to bring attention to the importance of training programs in preparing industry professionals for AI implementation and highlights key considerations for designing effective training initiatives. It identifies the needs of the industry, hands-on learning experiences, and continuous skill development to ensure the optimal utilization of AI technologies in the context of Industry 4.0. In line with the objective of this work and with the support of an EU project and an associated Digital Innovation Hub (DIH), three comprehensive training programs in Maintenance, Production, and Quality are being developed. Industries can benefit from these training programs, which foster a workforce that is equipped with the necessary knowledge, skills, and awareness to enhance the implementation of Industry 4.0-related technologies and concepts, including AI and supportive technologies. The paper is terminated with concluding remarks and briefly looks into possible future work.

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Supporting Mass Collaborative Learning Communities Through Digital Innovation Hubs

Cited by 2 publications

References 22 publications

A Learning Framework for Supporting Digital Innovation Hubs

A Learning Framework for Supporting Digital Innovation Hubs

Integration of AI Use Cases in Training to Support Industry 4.0

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