The 10 most recently published documents
The present work explores how theories of motivation can be used to enhance video game research. Currently, Flow-Theory and Self-Determination Theory are the most common approaches in the field of Human-Computer Interaction. The dissertation provides an in-depth look into Motive Disposition Theory and how to utilize it to explain interindividual differences in motivation. Different players have different preferences and make different choices when playing games, and not every player experiences the same outcomes when playing the same game. I provide a short overview of the current state of the research on motivation to play video games. Next, Motive Disposition Theory is applied in the context of digital games in four different research papers, featuring seven studies, totaling 1197 participants. The constructs of explicit and implicit motives are explained in detail while focusing on the two social motives (i.e., affiliation and power). As dependent variables, behaviour, preferences, choices, and experiences are used in different game environments (i.e., Minecraft, League of Legends, and Pokémon). The four papers are followed by a general discussion about the seven studies and Motive Disposition Theory in general. Finally, a short overview is provided about other theories of motivation and how they could be used to further our understanding of the motivation to play digital games in the future. This thesis proposes that 1) Motive Disposition Theory represents a valuable approach to understand individual motivations within the context of digital games; 2) there is a variety of motivational theories that can and should be utilized by researchers in the field of Human-Computer Interaction to broaden the currently one-sided perspective on human motivation; 3) researchers should aim to align their choice of motivational theory with their research goals by choosing the theory that best describes the phenomenon in question and by carefully adjusting each study design to the theoretical assumptions of that theory.
Heterogenität ist Teil des (Schul-)Alltags, was sich in den Lerngruppen widerspiegelt, die Lehrkräfte in der Schule vorfinden. Unterschiedlichen Bedürfnissen auf Seiten der Schüler/-innenschaft soll – und das ist in zahlreichen der Öffentlichkeit zugänglichen Dokumenten, wie Schulgesetzen, Schulordnungen und Standards für die Lehrerbildung festgeschrieben – in Form von Differenzierung begegnet werden. Innerhalb dieser Dissertation wird untersucht, wie Binnendifferenzierung auf Mikroebene in der Schulpraxis implementiert wird. Dabei werden die Einsatzhäufigkeit binnendifferenzierender Maßnahmen und Kontextvariablen von Binnendifferenzierung untersucht. Anhand einer Stichprobe von N = 295 Lehrkräften verschiedener Schulformen, die die Fächer Deutsch und/oder Englisch unterrichten, wurde u.a. gezeigt, dass Binnendifferenzierung allgemein nicht (sehr) häufig eingesetzt wird, dass manche Maßnahmen häufiger Einsatz finden als andere, dass an Gymnasien Binnendifferenzierung nicht so häufig eingesetzt wird, wie an anderen Schulformen und dass die Einsatzhäufigkeit bedingende Kontextfaktoren bspw. kollegiale Zusammenarbeit bei der Unterrichtsplanung und -durchführung, die wahrgenommene Qualität der Lehramtsausbildung hinsichtlich des Umgangs mit Heterogenität und die Bereitschaft zur Implementation von Binnendifferenzierung sind und auch Einstellungen zu Binnendifferenzierung und (Lehrer/-innen)Selbstwirksamkeitserwartungen in Zusammenhang mit dem Maßnahmeneinsatz stehen. Die durchgeführte Post-hoc Analyse zeigte bzgl. Einsatzhäufigkeit weiterhin Zusammenhänge zwischen der Persönlichkeit der Lehrkräfte und der Schulform, an der diese unterrichten. Die Ergebnisse entstammen der Schulpraxis und liefern deshalb praktische Implikationen, wie bspw. Hinweise zur Steigerung der Qualität der Lehramtsausbildung, die neben zukünftigen Forschungsansätzen im Rahmen dieser Arbeit expliziert werden.
In her poems, Tawada constructs liminal speaking subjects – voices from the in-between – which disrupt entrenched binary thought processes. Synthesising relevant concepts from theories of such diverse fields as lyricology, performance studies, border studies, cultural and postcolonial studies, I develop ‘voice’ and ‘in-between space’ as the frameworks to approach Tawada’s multifaceted poetic output, from which I have chosen 29 poems and two verse novels for analysis. Based on the body speaking/writing, sensuality is central to Tawada’s use of voice, whereas the in-between space of cultures and languages serves as the basis for the liminal ‘exophonic’ voices in her work. In the context of cultural alterity, Tawada focuses on the function of language, both its effect on the body and its role in subject construction, while her feminist poetry follows the general development of feminist academia from emancipation to embodiment to queer representation. Her response to and transformation of écriture féminine in her verse novels transcends the concept of the body as the basis of identity, moving to literary and linguistic, plural self-construction instead. While few poems are overtly political, the speaker’s personal and contextual involvement in issues of social conflict reveal the poems’ potential to speak of, and to, the multiply identified citizens of a globalised world, who constantly negotiate physical as well as psychological borders.
With the ongoing trend towards deep learning in the remote sensing community, classical pixel based algorithms are often outperformed by convolution based image segmentation algorithms. This performance was mostly validated spatially, by splitting training and validation pixels for a given year. Though generalizing models temporally is potentially more difficult, it has been a recent trend to transfer models from one year to another, and therefore to validate temporally. The study argues that it is always important to check both, in order to generate models that are useful beyond the scope of the training data. It shows that convolutional neural networks have potential to generalize better than pixel based models, since they do not rely on phenological development alone, but can also consider object geometry and texture. The UNET classifier was able to achieve the highest F1 scores, averaging 0.61 in temporal validation samples, and 0.77 in spatial validation samples. The theoretical potential for overfitting geometry and just memorizing the shape of fields that are maize has been shown to be insignificant in practical applications. In conclusion, kernel based convolutions can offer a large contribution in making agricultural classification models more transferable, both to other regions and to other years.
Many people are aware of the negative consequences of plastic use on the environment. Nevertheless, they use plastic due to its functionality. In the present paper, we hypothesized that this leads to the experience of ambivalence—the simultaneous existence of positive and negative evaluations of plastic. In two studies, we found that participants showed greater ambivalence toward plastic packed food than unpacked food. Moreover, they rated plastic packed food less favorably than unpacked food in response evaluations. In Study 2, we tested whether one-sided (only positive vs. only negative) information interventions could effectively influence ambivalence. Results showed that ambivalence is resistant to (social) influence. Directions for future research were discussed.
Energy transition strategies in Germany have led to an expansion of energy crop cultivation in landscape, with silage maize as most valuable feedstock. The changes in the traditional cropping systems, with increasing shares of maize, raised concerns about the sustainability of agricultural feedstock production regarding threats to soil health. However, spatially explicit data about silage maize cultivation are missing; thus, implications for soil cannot be estimated in a precise way. With this study, we firstly aimed to track the fields cultivated with maize based on remote sensing data. Secondly, available soil data were target-specifically processed to determine the site-specific vulnerability of the soils for erosion and compaction. The generated, spatially-explicit data served as basis for a differentiated analysis of the development of the agricultural biogas sector, associated maize cultivation and its implications for soil health. In the study area, located in a low mountain range region in Western Germany, the number and capacity of biogas producing units increased by 25 installations and 10,163 kW from 2009 to 2016. The remote sensing-based classification approach showed that the maize cultivation area was expanded by 16% from 7305 to 8447 hectares. Thus, maize cultivation accounted for about 20% of the arable land use; however, with distinct local differences. Significant shares of about 30% of the maize cultivation was done on fields that show at least high potentials for soil erosion exceeding 25 t soil ha−1 a−1. Furthermore, about 10% of the maize cultivation was done on fields that pedogenetically show an elevated risk for soil compaction. In order to reach more sustainable cultivation systems of feedstock for anaerobic digestion, changes in cultivated crops and management strategies are urgently required, particularly against first signs of climate change. The presented approach can regionally be modified in order to develop site-adapted, sustainable bioenergy cropping systems.
The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.
Social innovation became a widely discussed topic in politics, research funding programs, and business development. Recent European and US economic and science policies have set aside significant funds to generate and foster social innovation. In view of current challenges such as digitization, Work 4.0, inclusion or migrant integration, the question of how organizations can be empowered to develop new and innovative approaches and service models to social challenges is becoming increasingly urgent. This especially applies to organizations in the fields of education and social services. In education, implementing new ideas and concepts is usually discussed as educational reform, which mostly addresses changes in policy agendas with consequences for national and international education systems. The concept of social innovation however has a different starting point: the source of new ideas and services are identified new, emergent needs in society or re-conceptualized. Such need-based perspectives might bring new impulses to the field of education. Therefore, this paper identifies important existing strands of social innovation research, which need to be considered in the emerging academic discourse on social innovation in education. Looking at social innovation through an education research lens reveals the close relation between learning, creativity, and innovation. Individuals, teams, and even organizations learn, engage in creative problem solving to create new and innovative products and services. From an organizational education perspective, the questions arise, how social innovation emerges and even more important, how the process of developing social innovation can be supported. After a brief introduction in the concept of social innovation, the paper discusses therefore the sites, where social innovation emerges, social innovators, approaches to foster social innovation as well as promoting and hindering factors for social innovation.
Designing a Randomized Trial with an Age Simulation Suit—Representing People with Health Impairments
(2020)
Due to demographic change, there is an increasing demand for professional care services, whereby this demand cannot be met by available caregivers. To enable adequate care by relieving informal and formal care, the independence of people with chronic diseases has to be preserved for as long as possible. Assistance approaches can be used that support promoting physical activity, which is a main predictor of independence. One challenge is to design and test such approaches without affecting the people in focus. In this paper, we propose a design for a randomized trial to enable the use of an age simulation suit to generate reference data of people with health impairments with young and healthy participants. Therefore, we focus on situations of increased physical activity.
Digitalization primarily takes place in and through organizations. Despite this prominent role, however, the importance of organizational structure-building processes in the digital transformation is still underexposed in discourse. The fact that ongoing digitalization is linked to an established phenomenon and its own logic, is regularly not addressed due to the attraction potential of the semantics of the digital revolution. Digital revolution and the reordering of societal relationships, though, manifest themselves primarily in processes of reorganization. Structural automation processes in the ongoing digital transformation are limiting the scope for action, necessitating forms of structural structurelessness in organizations that cultivate opportunities for chance. Since organizations realize their operations as a dual of structure and individual, and the principle of organization is therefore based on the complementarity of structural formality and unpredictable informality. The paper discusses the topicality of the classical form of modern organization in the digital age and reflects on approaches to a contemporary design of spaces of opportunity. The reflexive handling of future openness is the central task of management and leadership in order to enable variation and innovation in organizations.
