FB1 Sozial- und Bildungswissenschaften
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Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics occurring in small groups (the dynamics problem). Machine learning helps to address the scaling problem, as massive computing power can be harnessed to multiply manual codings of group interactions. Computer simulations with artificially intelligent agents help to address the dynamics problem by implementing social psychological theory in data-generating algorithms that allow for sophisticated statements and tests of theory. We describe an ongoing research project aimed at computational analysis of virtual software development teams.
A topology of groups
(2020)
In this work, we study the collaboration patterns of open source software projects on GitHub by analyzing the pull request submissions and acceptances of repositories. We develop a group typology based on the structural properties of the corresponding directed graphs, and analyze how the topology is connected to the repositorys collective identity, hierarchy, productivity, popularity, resilience and stability. These analyses indicate significant differences between group types and thereby provide valuable insights on how to effectively organize collaborative software development. Identifying the mechanisms that underlie self-organized collaboration on digital platforms is important not just to better understand open source software development but also all other decentralized and digital work environments, a setting widely regarded as a key feature of the future work place.
The idea that a simple execution of an innovation invented by actors other than those who are expected to apply it is not likely to take place is a truism. We assume, however, in this paper the idea of a discursive production of knowledge on the application of an innovation across different levels of the education system. We aim to shed light on an innovation’s ‘journey’ from educational policy over training providers to teams of professionals in early childhood education and care (ECEC). By investigating knowledge and emotions associated with the introduction of an intended innovation using the example of “stimulation interactions” in day care-centers, the paper contributes to research on the transfer of innovations in education. To better understand challenges occurring during the transfer of innovations, we triangulate methods from discourse theory (coding techniques based on GTM) and cognitive science, namely cognitive-affective mapping (according to the scholarly conventions). The data corpus includes educational plans (N = 2), in-service training programs (N = 123) and group discussions of pedagogical teams (N = 6) who participated in an in-service training on the subject, stimulating interaction. Findings underline that similar messages from the inventors on the educational policy level are received and processed heterogeneously by the teams of pedagogues as a result of their preexisting views, routine practices and experiences with intended innovations through in-service trainings. Besides, a diffuse mixture of competing and contradictory information is communicated to the professionals and, hence, collides with the in-service training providers’ and educational policy actors’ expectations on the processing of the intended innovation. Specific knowledge elements and their valences are diametrically opposed to each other. Dissonances like these are considered as obstacles to social innovation. The obstacles are caused by the lack of a ‘common language’ beyond all levels. Hence, policy-makers and in-service-training providers should anticipate the supportive as well as competing knowledge-emotional complexes of professionals and take these into account when communicating an intended innovation.
We review Affect Control Theory (ACT) as a promising basis for equipping computational agents in social simulations with a sense of sociality. ACT is a computational theory that integrates sociological insights about the symbolic construction of the social order with psychological knowledge about cognitive-affective mechanisms. After explaining the theoretical foundations of ACT and applications of the theory at the dyadic and group level, we describe a case study applying the theory from an ongoing research project examining self-organized online collaboration in software development.
Theoretical and Empirical Modeling of Identity and Sentiments in Collaborative Groups (THEMIS.COG) was an interdisciplinary research collaboration of computer scientists and social scientists from the University of Waterloo (Canada), Potsdam University of Applied Sciences (Germany), and Dartmouth College (USA). This white paper summarizes the results of our research at the end of the grant term. Funded by the Trans-Atlantic Platform’s Digging Into Data initiative, the project aimed at theoretical and empirical modeling of identity and sentiments in collaborative groups. Understanding the social forces behind self-organized collaboration is important because technological and social innovations are increasingly generated through informal, distributed processes of collaboration, rather than in formal organizational hierarchies or through market forces. Our work used a data-driven approach to explore the social psychological mechanisms that motivate such collaborations and determine their success or failure. We focused on the example of GitHub, the world’s current largest digital platform for open, collaborative software development. In contrast to most, purely inductive contemporary approaches leveraging computational techniques for social science, THEMIS.COG followed a deductive, theory-driven approach. We capitalized on affect control theory, a mathematically formalized theory of symbolic interaction originated by sociologist David R. Heise and further advanced in previous work by some of the THEMIS.COG collaborators, among others. Affect control theory states that people control their social behaviours by intuitively attempting to verify culturally shared feelings about identities, social roles, and behaviour settings. From this principle, implemented in computational simulation models, precise predictions about group dynamics can be derived. It was the goal of THEMIS.COG to adapt and apply this approach to study the GitHub collaboration ecosystem through a symbolic interactionist lens. The project contributed substantially to the novel endeavor of theory development in social science based on large amounts of naturally occurring digital data.
Simulation tools aimed at enhancing cross-sectoral cooperation can support the transition from a traditional transport planning approach based on predictions towards more integrated and participatory urban mobility planning. This shift entails a broader appraisal of urban dynamics and transformations in the policy framework, capitalizing on new developments in urban modelling. In this paper, we argue that participatory social simulation can be used to solve these emerging challenges in mobility planning. We identify the functionalities that such a tool should have when supporting integrated mobility planning. Drawing on a transdisciplinary case study situated in Potsdam, Germany, we address through interviews and workshops stakeholders’ needs and expectations and present the requirements of an actionable tool for practitioners. As a result, we present three main challenges for participatory, simulation-based transport planning, including: (1) enhancement of the visioning process by testing stakeholders’ ideas under different scenarios and conditions to visualise complex urban relationships; (2) promotion of collective exchange as means to support stakeholder communication; and (3) credibility increase by early stakeholder engagement with model development. We discuss how our participatory modelling approach helps us to better understand the gaps in the knowledge of the planning process and present the coming steps of the project.
Germany has become the most important destination country for young refugees in Europe (Destatis, 2021). Vocational education and training can make an important contribution to overcome educational barriers and gain participation in society (Will & Hohmut, 2020). Since 2015, rural regions have faced new challenges in establishing effective support systems for young apprentices with forced migration experience (Ohliger et al., 2017). The participatory LaeneAs research project seeks to identify educational barriers and to promote successful educational pathways for young refugees in vocational training. In four distinct rural areas in Germany, stakeholders in formal, non-formal, and informal learning environments and young refugees will be brought together in real-world laboratories. The authors aim to open space for a co-constructive knowledge production process between scientific and political stakeholders, educational practitioners, and refugee youth. Real-world laboratories are a socio-spatial methodology that combines research and a sustainable capacity building process. The lifeworld expertise will be used for a contextual condition analysis of structural, societal, and individual barriers to education as well as for practice transfer. Building on the discussion of the current state of research and the identification of significant gaps in the practice and research landscape, this essay will focus on the critical discussion of the methodological implementation of the study.
The ability to refer to objects – singular reference – is arguably the decisive innovation on the way to human propositional cognition. This article argues that object individuation requires singular reference because basic singular terms, namely spatial indexicals, provide a symbolic frame of reference for object individuation. The authors suggest that singular reference is intrinsically connected to essential characteristics of propositionality: among other things, it guarantees the situation-independence of meaning, allows for the distinction between truth and falsehood, and enables us to think about possibilities. The authors sketch how singular reference gives rise to the development of predication, the powerful logical tool of quantification, and forms the basis for differentiating between belief and desire.
Virtual Reality (VR) applications play an increasingly important role in the context of mental health. While VR-based therapeutic interventions are increasingly well-established, the application of VR in the field of mental health awareness represents a novel and promising development. We present our mental health awareness VR application “hopohopo”, in which the user takes the perspective of a person suffering from social anxiety. Through the VR journey, the user experiences what it could feel like to suffer from constant fear of being negatively judged by others in everyday social situations. The aim of the application is to allow nonaffected users to expand their knowledge and to raise mental health awareness. In this paper, we report our findings on the potential of this immersive VR application for psychoeducation and destigmatization of social anxiety. In this respect, we provide the scope of our VR application and first results of its ongoing usability and usefulness evaluation process.
Understanding how individual or group behaviour are influenced by the presence of others is something both social psychology and agent-based social simulation are concerned with. However, there is only limited overlap between these two research communities, which becomes clear when terms such as “variable”, “prediction”, or “model” come into play, and we build on their different meanings. This situation challenges us when working together, since it complicates the uptake of relevant work from each community and thus hampers the potential impact that we could have when joining forces.