Die Debatte über den Einsatz von digitalen Werkzeugen in der mathematischen Frühförderung ist hoch aktuell. Lernspiele werden konstruiert, mit dem Ziel, mathematisches, informelles Wissen aufzubauen und so einen besseren Schulstart zu ermöglichen. Doch allein die digitale und spielerische Aufarbeitung führt nicht zwingend zu einem Lernerfolg. Daher ist es umso wichtiger, die konkrete Implementation der theoretischen Konstrukte und Interaktionsmöglichkeiten mit den Werkzeugen zu analysieren und passend aufzubereiten. In dieser Masterarbeit wird dazu exemplarisch ein mathematisches Lernspiel namens „Fingu“ für den Einsatz im vorschulischen Bereich theoretisch und empirisch im Rahmen der Artifact-Centric Activity Theory (ACAT) untersucht. Dazu werden zunächst die theoretischen Hintergründe zum Zahlensinn, Zahlbegriffserwerb, Teil-Ganze-Verständnis, der Anzahlwahrnehmung und -bestimmung, den Anzahlvergleichen und der Anzahldarstellung mithilfe von Fingern gemäß der Embodied Cognition sowie der Verwendung von digitalen Werkzeugen und Multi-Touch-Geräten umfassend beschrieben. Anschließend wird die App Fingu erklärt und dann theoretisch entlang des ACAT-Review-Guides analysiert. Zuletzt wird die selbstständig durchgeführte Studie mit zehn Vorschulkindern erläutert und darauf aufbauend Verbesserungs- und Entwicklungsmöglichkeiten der App auf wissenschaftlicher Grundlage beigetragen. Für Fingu lässt sich abschließend festhalten, dass viele Prozesse wie die (Quasi-)Simultanerfassung oder das Zählen gefördert werden können, für andere wie das Teil-Ganze-Verständnis aber noch Anpassungen und/oder die Begleitung durch Erwachsene nötig ist.

Es wird ein Überblick über verschiedene spektroskopische Techniken, mit denen dünne organische Schichten, wie sie in der Fotovoltaik, bei Leuchtdioden oder organischen Halbleitern Anwendung finden, gegeben. Mit einfachen Zusatzgeräten lassen sich Schichtdicke, Schichtaufbau und Zusammensetzung untersuchen. Die Schichtdicke kann monomolekular sein. Unter bestimmten Voraussetzungen sind einzelne Moleküle in einer Schicht charakterisierbar.

Nutrient storage, transform and transport are important processes for achieving environmental and ecological health, as well as conducting water management plans. Nitrogen is one of the most noticeable elements due to its impacts on tremendous consequences of eutrophication in aquatic systems. Among all nitrogen components, researches on nitrate are blooming because of widespread deployments of in-situ high-frequency sensors. Monitoring and studying nitrate can become a paradigm for any other reactive substances that may damage environmental conditions and cause economic losses. Identifying nitrate storage and its transport within a catchment are inspiring to the management of agricultural activities and municipal planning. Storm events are periods when hydrological dynamics activate the exchange between nitrate storage and flow pathways. In this dissertation, long-term high-frequency monitoring data at three gauging stations in the Selke river were used to quantify event-scale nitrate concentration-discharge (C-Q) hysteretic relationships. The Selke catchment is characterized into three nested subcatchments by heterogeneous physiographic conditions and land use. With quantified hysteresis indices, impacts of seasonality and landscape gradients on C-Q relationships are explored. For example, arable area has deep nitrate legacy and can be activated with high intensity precipitation during wetting/wet periods (i.e., the strong hydrological connectivity). Hence, specific shapes of C-Q relationships in river networks can identify targeted locations and periods for agricultural management actions within the catchment to decrease nitrate output into downstream aquatic systems like the ocean. The capacity of streams for removing nitrate is of both scientific and social interest, which makes the quantification motivated. Although measurements of nitrate dynamics are advanced compared to other substances, the methodology to directly quantify nitrate uptake pathways is still limited spatiotemporally. The major problem is the complex convolution of hydrological and biogeochemical processes, which limits in-situ measurements (e.g., isotope addition) usually to small streams with steady flow conditions. This makes the extrapolation of nitrate dynamics to large streams highly uncertain. Hence, understanding of in-stream nitrate dynamic in large rivers is still necessary. High-frequency monitoring of nitrate mass balance between upstream and downstream measurement sites can quantitatively disentangle multi-path nitrate uptake dynamics at the reach scale (3-8 km). In this dissertation, we conducted this approach in large stream reaches with varying hydro-morphological and environmental conditions for several periods, confirming its success in disentangling nitrate uptake pathways and their temporal dynamics. Net nitrate uptake, autotrophic assimilation and heterotrophic uptake were disentangled, as well as their various diel and seasonal patterns. Natural streams generally can remove more nitrate under similar environmental conditions and heterotrophic uptake becomes dominant during post-wet seasons. Such two-station monitoring provided novel insights into reach-scale nitrate uptake processes in large streams. Long-term in-stream nitrate dynamics can also be evaluated with the application of water quality model. This is among the first time to use a data-model fusion approach to upscale the two-station methodology in large-streams with complex flow dynamics under long-term high-frequency monitoring, assessing the in-stream nitrate retention and its responses to drought disturbances from seasonal to sub-daily scale. Nitrate retention (both net uptake and net release) exhibited substantial seasonality, which also differed in the investigated normal and drought years. In the normal years, winter and early spring seasons exhibited extensive net releases, then general net uptake occurred after the annual high-flow season at later spring and early summer with autotrophic processes dominating and during later summer-autumn low-flow periods with heterotrophy-characteristics predominating. Net nitrate release occurred since late autumn until the next early spring. In the drought years, the late-autumn net releases were not so consistently persisted as in the normal years and the predominance of autotrophic processes occurred across seasons. Aforementioned comprehensive results of nitrate dynamics on stream scale facilitate the understanding of instream processes, as well as raise the importance of scientific monitoring schemes for hydrology and water quality parameters.

Economic agents often irrationally base their decision-making on irrelevant information. This research analyzes whether men and women react to futile information about past outcomes. For this purpose, we run a laboratory experiment (Study 1) and use field data (Study 2). In both studies, the behavior of men is consistent with falsely assumed negative autocorrelation, often referred to as gambler’s fallacy Women’s behavior aligns with falsely assumed positive autocorrelation, a notion of the hot hand fallacy. On the aggregate, the two fallacies cancel out. Even when individuals are, on average, rational, the biases in the decision-making of subgroups might cause inefficient outcomes. In a mediation analysis, we find that a) the agents stated perceived probabilities of future outcomes are not blurred by irrelevant information and b) about 40 % of the observed biases are driven by differences in the perceived attractiveness of available choices caused by the irrelevant information.

Divergent thinking is the ability to produce numerous and diverse responses to questions or tasks, and it is used as a predictor of creative achievement. It plays a significant role in the business organization’s innovation process and the recognition of new business opportunities. Drawing upon the cumulative process model of creativity in entrepreneurship, we hypothesize that divergent thinking has a lasting effect on post-launch entrepreneurial outcomes related to innovation and growth, but that this relation might not always be linear. Additionally, we hypothesize that domain-specific experience has a moderating role in this relation. We test our hypotheses based on a representative longitudinal sample of 457 German business founders, which we observe up until 40 months after start-up. We find strong relative effects for innovation and growth outcomes. For survival we find conclusive evidence for non-linearities in the effects of divergent thinking. Additionally, we show that such effects are moderated by the type of domain-specific experience that entrepreneurs gathered pre-launch, as it shapes the individual’s ideational abilities to fit into more sophisticated strategies regarding entrepreneurial creative achievement. Our findings have relevant policy implications in characterizing and identifying business start-ups with growth and innovation potential, allowing a more efficient allocation of public and private funds.