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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Interview with German Media Theorist Vera Tollmann on View from Above By Geert Lovink This interview was previously published on October 11, 2023 on Geert Lovink’s blog, Net Critique, at: https://networkcultures.org/geert/2023/10/11/interview-with-german-media-theorist-vera-tollmann-on-view-from-above/
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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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