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Die Erfahrung, "…dass alles auch ganz anders sein könnte" ist die wohl wichtigste Erfahrung in Bildungsprozessen. Die Entdeckung von Möglichkeiten, Perspektivwechseln und transformatorischen Selbst-Bildungsprozessen ist zentral für eine gelungene kulturelle Bildungssituation. (Birgit Mandel, 2005).
Die Hessischen Schülerakademien zur Förderung besonders engagierter und begabter junger Menschen wurden bewusst als ein Unterfangen des Forschenden Lernens gegründet und fühlen sich diesem Leitgedanken im Kontext kultureller Bildung verpflichtet. Dieser Satz klingt zunächst einmal gut und zeitgemäß. Doch was steckt genau dahinter?
Das Akademiejahr 2018 hatte neben den beiden Schülerakademien für die Mittelstufe und die Oberstufe noch einen weiteren Höhepunkt: das Symposium "Kulturelle Bildung auf dem Weg" (vom 2. bis 4. März 2018, ausgerichtet von Burg Fürsteneck gemeinsam mit dem Schulentwicklungsprogramm KulturSchule des Hessischen Kultusministeriums und dem Weiterbildungsmaster Kulturelle Bildung an Schulen der Uni Marburg). Es wurde von unserem Schirmherrn, Kultusminister Prof. Dr. R. Alexander Lorz, eröffnet und hatte unter anderem das Ziel, in der Begegnung von Bildungsexpert*innen und -praktiker*innen eine Fachdebatte über "Qualitätsbedingungen in der Kulturellen Bildung am Beispiel der Schülerakademien und der Kulturschulen in Hessen" anzustoßen.
Strong convergence rates for numerical approximations of stochastic partial differential equations
(2018)
In this thesis and in the research articles which this thesis consists of, respectively, we focus on strong convergence rates for numerical approximations of stochastic partial differential equations (SPDEs). In Part I of this thesis, i.e., Chapter 2 and Chapter 3, we study higher order numerical schemes for SPDEs with multiplicative trace class noise based on suitable Taylor expansions of the Lipschitz continuous coefficients of the SPDEs under consideration. More precisely, Chapter 2 proves strong convergence rates for a linear implicit Euler-Milstein scheme for SPDEs and is based on an unpublished manuscript written by the author of this thesis. This chapter extends an earlier result1 by slightly lowering the assumptions posed on the diffusion coefficient and a different approximation of the semigroup. In Chapter 3 we introduce an exponential Wagner-Platen type numerical scheme for SPDEs and prove that this numerical approximation method converges in the strong sense with oder up to 3/2−. Moreover, we illustrate how the (mixed) iterated stochastic-deterministic integrals, that are part of our numerical scheme, can be simulated exactly under suitable assumptions.
The second part of this thesis, i.e. Chapter 4 and Chapter 5, is devoted to strong convergence rates for numerical approximations of SPDEs with superlinearly growing nonlinearities driven by additive space-time white noise. More specifically, in Chapter 4, we prove strong convergence with rate in the time variable for a class of nonlinearity-truncated numerical approximation schemes for SPDEs and provide examples that fit into our abstract setting like stochastic Allen-Cahn equations. Finally, in Chapter 5, we extend this result with spatial approximations and establish strong convergence rates for a class of full-discrete nonlinearity truncated numerical approximation schemes for SPDEs. Moreover, we apply our strong convergence result to stochastic Allen-Cahn equations and provide lower and upper bounds which show that our strong convergence result can, in general, not essentially be improved.
In 1957, Craig Mooney published a set of human face stimuli to study perceptual closure: the formation of a coherent percept on the basis of minimal visual information. Images of this type, now known as “Mooney faces”, are widely used in cognitive psychology and neuroscience because they offer a means of inducing variable perception with constant visuo-spatial characteristics (they are often not perceived as faces if viewed upside down). Mooney’s original set of 40 stimuli has been employed in several studies. However, it is often necessary to use a much larger stimulus set. We created a new set of over 500 Mooney faces and tested them on a cohort of human observers. We present the results of our tests here, and make the stimuli freely available via the internet. Our test results can be used to select subsets of the stimuli that are most suited for a given experimental purpose.