http://hdl.handle.net/10900/42132 Fri, 12 Jun 2026 14:59:32 GMT 2026-06-12T14:59:32Z http://hdl.handle.net/10900/180750 AI in biomedicine and healthcare: Sociological perspectives on personalized HIV therapy and skin cancer detection tools Baumgartner, Renate AI-based technologies in biomedicine and healthcare are gaining more importance due to the new hype around AI and the increasing concerns about future challenges in healthcare. It is assumed that the logic within these tools, depending on which data can be digitalized in the first place, what is considered relevant, and the way data and information is used within these tools, influences knowledge constructions within the field they are used, including which information is seen as relevant. If we want to understand how medicine and healthcare might change through the usage of AI-based tools, a sociological analysis of how these tools influence constructions of knowledge in the context in which there are used is paramount. This cumulative dissertation chose two cases of AI-based tools for this endeavor: HIV treatment optimization tools as one of the first successful AI-based tools within personalized medicine, and skin cancer detection tools. These were analyzed through the lenses of sociology of categorization and classification, sociology of risk and uncertainty, and feminist science and technology studies. A key goal of the work was to explore the categories made relevant in the AI-based tools compared to categories made relevant within the context of use. The situational analysis of HIV treatment optimization tools concluded how patients, as marginalized implicated actors are discursively constructed by other social worlds. The feminist STS analysis of skin cancer detection tools identified how racial discrimination in the field led to racially biased AI-tools. The comparative analysis between the two cases studies shows how different categories of people are made relevant in the tools and which categories were regarded as relevant to solve the problem at stake. Only a minor part of the relevant categories in the field found their way into the digital tools. While social constructions inform actions in the field of HIV treatment optimization tools, the AI-based tool itself is solely based on genetic data. Differently, for skin cancer detection tools, the social category of race can become highly relevant. The dissertation concludes that AI-based tools can lead to further naturalization of social categories such as race, even more so as categorization is increasing in relevance to account for fairness through AI-based tools. Fri, 12 Jun 2026 00:00:00 GMT http://hdl.handle.net/10900/180750 2026-06-12T00:00:00Z http://hdl.handle.net/10900/180623 Recognition of social identities as a mechanism to increase the resilience of individuals, liberal democracies, and societies Babst, Axel This Ph.D. thesis investigates how recognition of social identities may serve as a mechanism to increase the resilience of individuals, liberal democracies, and societies. This topic is highly relevant in political and societal terms due to the polycrisis of Western societies. I present a possible mechanism for overcoming the polycrisis in the form of the recognition of social identities to in-crease resilience. My dissertation makes three contributions to expand the current state of re-search. 1) From a theoretical perspective, I synthesize Tajfel and Turner's Social Identity Theory (SIT, 1979) with Honneth’s (1992) and Fukuyama's (2019) work on recognition. 2) Methodologically, I develop new items for measuring the recognition of occupational and social class identities. 3) Substantively, I demonstrate in three empirical, peer-reviewed journal articles the assumed connection between the degree of perceived recognition and indicators of resilience in relation to three different crises. The first paper shows that occupational groups that were particularly challenged during the pandemic (“essential” occupations, careworkers, “base workers”) did experience an increase in symbolic recognition, but that this did not translate into financial compensation. At the same time, it is evident that recognition of occupational identities promotes compliance with infection control measures, enhancing societal resilience during a pandemic. Study 2 addresses the rise of populism. It shows that a lack of recognition of social identities is a significant predictor of populist attitudes, which has hardly been discussed in the extensive literature on the causes of populism to date. In the third paper, I show that the recognition of social class identities correlates positively with the acceptance of climate change mitigation measures. Despite limitations (cross-sectional data, sample, selection of social identities), the results are promising and already provide a basis for relevant policy recommendations such as increasing the salaries of essential and base workers, involving citizens in policy design, and transparent and honest political communication that also takes citizens' needs into account. With my dissertation, I am making an important contribution to labor market research, and political sociology, and provide a foundation on which future research on the recognition of social identities and its effects on the resilience of individuals, liberal democracies, and societies can build. References: Fukuyama, F. (2019). Identität: Wie der Verlust der Würde unsere Demokratie gefährdet (3. Auflage). Hoffmann und Campe. Honneth, A. (1992). Kampf um Anerkennung: Zur moralischen Grammatik sozialer Konflikte. Suhrkamp. Tajfel, H., & Turner, J. C. (1979). An integrative theory of intergroup conflict. In S. Worchel & W. G. Austin (Eds.), The social psychology of intergroup relations (pp. 33–47). Brooks Cole. Wed, 10 Jun 2026 00:00:00 GMT http://hdl.handle.net/10900/180623 2026-06-10T00:00:00Z http://hdl.handle.net/10900/180164 From Knowledge to Action in Technology-Enhanced Teaching: An Integrative Approach to Action-Oriented Teacher Professionalization Gazar, Franziska Teaching with technology is a demanding task that requires teachers to respond to rapidly unfolding classroom events. A central competence is teachers’ professional vision – the ability to notice instructionally relevant events and interpret them using professional knowledge (knowledge-based reasoning). Research shows that pre-service teachers often focus on salient features and struggle to use knowledge to interpret and respond to classroom situations, underscoring the need to foster professional vision early in teacher education. Despite substantial work on professional knowledge, professional vision, and video-based learning, an integrative, action-oriented account of professionalization for technology-enhanced teaching remains limited. First, little is known about how professional knowledge is connected and applied across instructional contexts, so it is not readily usable for noticing and reasoning. Second, evidence is fragmented regarding which design features of video-based analysis reliably foster professional vision and how learner prerequisites shape effects. To address these gaps, this dissertation pursued two complementary aims across four studies using context-based assessments. First, it examined knowledge integration across systematically varied instructional contexts involving technology use and across levels of teaching experience (Study 1). Findings indicated context-sensitive differences in knowledge application, consistent with more fragmented patterns among pre-service teachers and more connected patterns among in-service teachers. Second, it investigated how video-based analysis can be designed to foster professional vision by disentangling technological affordances (annotation tool) from instructional guidance (prompts, modeling examples) and considering prior knowledge and cognitive load (Studies 2-4). Tool support primarily strengthened noticing; modeling examples supported knowledge-based reasoning; prompt-based guidance was not beneficial and could disadvantage learners with low prior knowledge, and cognitive load effects were less pronounced than expected. Overall, the dissertation advances an integrative, context-specific account of action-oriented professionalization in technology-enhanced teaching and shows that fostering professional vision in video analysis requires differentiated support rather than one-size-fits-all guidance.; Die Dissertation ist gesperrt bis zum 19. Mai 2028 ! Fri, 19 May 2028 00:00:00 GMT http://hdl.handle.net/10900/180164 2028-05-19T00:00:00Z http://hdl.handle.net/10900/180162 Business ethics and digital inquiry-based learning: exploring students’ competence development Estler, Victoria Business ethics education is gaining increasing importance in times of global crisis, technological innovation, and social polarization. Questions of responsibility, fairness, and sustainability are economically relevant and essential for the functioning of democracy. As part of contemporary citizenship education, engaging with business ethics in schools contributes significantly to the development of students’ moral judgment, value orientations, and reflective participation in society. Schools thus play a key role in promoting responsible judgment and action-oriented competences. However, this requires innovative pedagogical approaches that actively involve learners in addressing complex moral questions. Inquiry-based learning (IBL) is considered a particularly promising pedagogical approach in this respect, as it supports independent thinking, critical analysis, and reflective moral reasoning. The digital implementation of IBL further enhances its potential by promoting collaboration, offering adaptive support, and fostering the development of key digital competences. Despite the widely recognized potential of digital IBL, there is still a lack of systematic research linking business ethics education with digital IBL at the secondary level. To address this research gap, this dissertation examines how digitally supported IBL can contribute to the development of business ethical competences in secondary education and what factors influence its effectiveness by connecting the social scientific field of business ethics with a pedagogical approach originally developed in the natural sciences. The aim of this dissertation is to systematically analyze the key factors identified in the literature as influencing the effectiveness of digital learning—learner and teacher characteristics, contextual conditions, and learning engagement—across three empirical studies. By examining these elements, it investigates the effectiveness of digital IBL in the social sciences. Focusing on learner characteristics, the first study, which employed a qualitative interview design, examined the conceptions of 33 eighth-grade students regarding business ethical issues. The findings showed that students reflected on business ethics predominantly in a fragmented and individual-ethical manner. Although some students demonstrated various conceptions of ethical economic behavior, their reasoning largely remained limited to consumer decisions, while political dimensions were scarcely considered. This narrow perspective was further reflected in misconceptions about governmental and corporate responsibilities as well as the distribution of economic power in competitive markets. The second study, which included 445 students, employed a quasi-experimental design to investigate the effectiveness of digitally supported IBL on competence development, considering contextual and teacher-related influences. While no evidence was found for a significant overall effect compared to traditional instruction, gender-specific differences emerged: for female students, digital IBL led to higher economic interest and intrinsic motivation, whereas male students showed a decrease in economic interest. The third study examined the role of student engagement, which is widely recognized as a key success factor in digital learning environments. Based on log data from 285 students, the quantitative analysis revealed that higher levels of behavioral engagement were associated with greater knowledge gains and stronger development of business-related competences. Interactive and visually oriented learning formats proved particularly beneficial. Learners who exhibited balanced use of various activity types—termed “all-rounders”—achieved the best learning outcomes and displayed higher levels of digital competence. Building on the findings of individual studies, this dissertation develops, for the first time, a subject-specific, empirically grounded framework model for the effectiveness of digital IBL in the social sciences. By illustrating and extending existing knowledge through the inclusion of learner and teacher characteristics, contextual factors, and student engagement, this work provides new empirical and theoretical insights into business ethics education at the secondary level and demonstrates how digital learning environments can be designed to foster critical reflection, sound moral judgment, and a sense of responsibility. Furthermore, the dissertation offers conceptual implications for teacher education—for instance, in further developing adaptive, multiperspectival, and gender-sensitive approaches to instructional design—and educational policy, particularly concerning cross-curricular frameworks and infrastructural provisions. In doing so, it establishes an empirically substantiated foundation for future research and practice-oriented developments aimed at promoting innovative teaching and learning concepts that support democratic and ethically grounded citizenship education in the digital age. Mon, 01 Jun 2026 00:00:00 GMT http://hdl.handle.net/10900/180162 2026-06-01T00:00:00Z