TheUniversity of Twente, SaxionUniversityofAppliedSciences, ROCofTwente(vocationaleducation), centre of expertise TechYourFuture and the H2Hub Twente, in which various regional hydrogen interested corporations are involved, work together to shape a learning community (LC) for the development of innovative hydrogen technology. The cooperation between company employees, researchers and students provides a means to jointly work on solutions for real-life problems within the energy transition. This involves a cross-chain collaboration of technical programs, professorships and (field) experts, supported by human capital specialists. In the LC, a decentralized hydrogen production unit with storage of green hydrogen is designed and built. The main question for this research is: how can the design and construction process of an alkaline electrolyzer be arranged in a challenge based LC in which students, company employees (specialists) and researchers from the three educational institutions can learn, innovate, build-up knowledge and benefit? In this project the concept of a LC is developed and implemented in collaboration with companies and knowledge institutions at different levels. The concrete steps are described below: 1. Joint session between Human Resource and Development (HRD) specialists and engineers/researchers to explore the important factors for a LC. The results of this session will be incorporated into a blueprint for the LC by the human capital specialists. 2. The project is carried out according to the agreements of the blueprint. The blueprint is continuously updated based on the periodic reflections and observed points for improvement. 3. Impact interviews and periodic reflection review the proceeding of the LC in this engineering process. The first impact interview reveals that the concept of the LC is very beneficial for companies. It increases overall knowledge on hydrogen systems, promotes cooperation and connection with other companies and aids to their market proposition as well. Students get the opportunity to work in close contact with multiple company professionals and build up a network of their own. Also the cooperation with students from different disciplines broadens their view as a professional, something which is difficult to achieve in a mono-disciplinary project.
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In Sicht von oben, ‘Powers of Ten’ und Bildpolitiken der Vertikalität (Spector Books, Leipzig, 2022) German media theorist and curator Vera Tollmann analyses the power aspects of the technical view from above. The context here is not so much the first manned flight with a balloon in 1783 in Paris but the iconic 1968/77 short film Powers of Ten by Charles and Ray Eames, which can be considered the first virtual camera trip. Her study can be seen as material image analysis along the lines of Friedrich Kittler’s optical media and is strongly informed by the work of Hito Steyerl. Part one deals with the verticality of the image regime, while part two focuses on the vertical aspect and part three theorizes scale and scalability.
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Despite the promises of learning analytics and the existence of several learning analytics implementation frameworks, the large-scale adoption of learning analytics within higher educational institutions remains low. Extant frameworks either focus on a specific element of learning analytics implementation, for example, policy or privacy, or lack operationalization of the organizational capabilities necessary for successful deployment. Therefore, this literature review addresses the research question “What capabilities for the successful adoption of learning analytics can be identified in existing literature on big data analytics, business analytics, and learning analytics?” Our research is grounded in resource-based view theory and we extend the scope beyond the field of learning analytics and include capability frameworks for the more mature research fields of big data analytics and business analytics. This paper’s contribution is twofold: 1) it provides a literature review on known capabilities for big data analytics, business analytics, and learning analytics and 2) it introduces a capability model to support the implementation and uptake of learning analytics. During our study, we identified and analyzed 15 key studies. By synthesizing the results, we found 34 organizational capabilities important to the adoption of analytical activities within an institution and provide 461 ways to operationalize these capabilities. Five categories of capabilities can be distinguished – Data, Management, People, Technology, and Privacy & Ethics. Capabilities presently absent from existing learning analytics frameworks concern sourcing and integration, market, knowledge, training, automation, and connectivity. Based on the results of the review, we present the Learning Analytics Capability Model: a model that provides senior management and policymakers with concrete operationalizations to build the necessary capabilities for successful learning analytics adoption.
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