FB1 Sozial- und Bildungswissenschaften
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un/natural surrogates
(2021)
The visual essay is an extension of the 2019 online exhibition un/natural surrogates which was created as part of the research project "Postdigital Art Practices in Cultural Education". The essay contrasts thirteen artworks from that show with thirteen newly selected artworks from the last seventy years, based on aesthetic similarities, parallels in the subject matter, and other related characteristics of the works. In doing so, an ahistorical story without -isms is offered.
Social anxiety disorder (SAD) is one of the most commonly diagnosed anxiety disorders and a health concern that has a significant impact on the affected individuals’ quality of life. Although there is a need to develop methods and tools to support those affected by SAD, it is especially challenging to conduct participatory design with this psychologically vulnerable group of people. This paper presents the design, implementation and evaluation of a participatory format built on a toolkit, a cultural probe and an online prototyping workshop to gain insights into the challenges and needs experienced in the everyday lives of those affected by severe social anxiety. We provide the theoretical framework for designing a participatory format for this vulnerable group, introduce and discuss our methodological approach, and present the lessons learned from implementing and evaluating the format in two workshop sessions with a total of 15 participants.
Among the philosophical accounts of reference, Quine’s (1974) The Roots of Reference stands out in offering an integrated account of the acquisition of linguistic reference and object individuation. Based on a non-referential ability to distinguish bodies, the acquisition of sortals and quantification are crucial steps in learning to refer to objects. In this article, we critically re-assess Quine’s account of reference. Our critique will proceed in three steps with the aim of showing that Quine effectively presupposes what he sets out to explain, namely, reference to objects. We are going to argue (i) that sortals do not individuate, (ii) that bodies are already objects, and (iii) that the acquisition of variables presupposes a notion of identity. The result is diagnostic of a central desideratum for any theory of reference: an explanation of spatiotemporal object individuation.
Perner and Roessler (in: Aguilar J, Buckareff A (eds) Causing human action: new perspectives on the causal theory of action, MIT Press, Cambridge, MA, pp 199–228, 2010) hold that children who do not yet have an understanding of subjective perspectives, i.e., mental states, explain actions by appealing to objective facts. In this paper, we criticize this view. We argue that in order to understand objective facts, subjects need to understand perspectives. By analysing basic fact-expressing assertions, we show that subjects cannot refer to facts if they do not understand two types of perspectivity, namely, spatial and doxastic perspectivity. To avoid conceptual confusion regarding different ways of referring to facts, we distinguish between reference to facts de re and de dicto.
Emotion-specific vocabulary and its relation to emotion understanding in children and adolescents
(2024)
Among children and adolescents, emotion understanding relates to academic achievement and higher well-being. This study investigates the role of general and emotion-specific language skills in children’s and adolescents’ emotion understanding, building on previous research highlighting the significance of domain-specific language skills in conceptual development. We employ a novel inventory (CEVVT) to assess emotion-specific vocabulary. The study involved 10–11-year-old children (N = 29) and 16–17-year-old adolescents (N = 28), examining their emotion recognition and knowledge of emotion regulation strategies. Results highlight the ongoing development of emotion-specific vocabulary across these age groups. Emotion recognition correlated with general vocabulary in the younger group. In the older age group, emotion recognition was related to emotion-specific vocabulary size, but this effect only became apparent when controlling for the depth of emotion-specific vocabulary. Against expectation, there were no significant contributions of general or emotion-specific vocabulary to knowledge of emotion regulation strategies in either age group. These findings enhance our comprehension of the nuanced interplay between language and emotion across developmental stages.
Let’s Talk About Emotions
(2021)
Learning to use language in an adult-like way is a long-lasting process. This may particularly apply to complex conceptual domains such as emotions. The present study examined children’s and adults’ patterns of emotion word usage regarding their convergence and underlying semantic dimensions, and the factors influencing the ease of emotion word learning. We assessed the production of emotion words by 4- to 11-year-old children (N = 123) and 27 adults (M = 37 years) using a vignette test. We found that the older the children, the more emotion words they produced. Moreover, with increasing age, children’s pattern of emotion word usage converged with adult usage. The analysis for semantic dimensions revealed one clear criterion—the differentiation of positive versus negative emotions—for all children and adults. We further found that broad covering emotion words are produced earlier and in a more adult-like way.
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.
We argue that objectivity is acquired by learning to refer to particular situations, that is, by developing episodicity. This contrasts with the widespread idea that genericity is crucial in developing humans’ ability to conceive of an objective world. According to the collective intentionality account, objectivity is acquired by contrasting one’s particular perspective in the “here and now” with a generic group perspective on how things are generally. However, this line of argument rests on confusing two independent notions of genericity: social and worldly genericity. Holding these two notions apart shows that there is no coherent developmental route from episodicity to objectivity via genericity. In effect, the collective intentionality account presupposes objectivity. Alternatively, episodicity may develop by enculturation into the common practice of spatial-indexical use. This ability establishes an initial, socially shared spatiotemporal reference system comprising the basis for objectivity.
While research on object individuation assumes that even very young children are able to perceive objects as particulars, we argue that the results of relevant studies can be explained in terms of feature discrimination. We propose that children start out navigating the world with a feature‐based ontology and only later become able to individuate objects spatiotemporally. Furthermore, object individuation is a cognitively demanding achievement resting on a uniquely human form of enculturation, namely the acquisition of deictic demonstratives. We conclude by outlining empirical expectations for operationalizations of our proposal.
The current understanding of cognitive development rests on the premise that infants can individuate objects early on. However, the so-called object-first account faces severe difficulties explaining extant empirical findings in object individuation tasks while alternative, more parsimonious explanations are available. In this paper, we assume that children start as feature-thinkers without being able to individuate objects and show how this ability can be learned by thinkers who do not already implicitly possess the notion of an object. Based on Tugendhat's ideas on the relation between singular terms and object reference, we argue that spatial indexicals comprise the fundamental means of object individuation and describe how feature thinkers might acquire the complex substitutional system of spatial indexicals. In closing, two accounts of object cognition that do not rely on symbolic capacities, namely Pylyshyn's FINST indexes and Burge's perceptual objectivity, are critically discussed.
It counts as empirically proven that infants can individuate objects. Object individuation is assumed to be fundamental in the development of infants’ ontology within the object-first account. It crucially relies on an object-file (OF) system, representing both spatiotemporal (“where”) and categorical (“what”) information about objects as solid, cohesive bodies moving continuously in space and time. However, infants’ performance in tasks requiring them to use featural information to detect individuation violations appears to be at odds with the object-first account. In such cases, infants do not appear to be able to develop correct expectations about the numerosity of objects. Recently, proponents of the object-first account proposed that these individuation failures result from integration errors between the OF system and an additional physical reasoning system. We are going to argue that the predictions of a feature-based physical-reasoning (PR) system are sufficient for explaining infants’ behavior. The striking predictive power of the PR system calls into question the relevance of the OF system and, thereby, challenges the assumption that infants can individuate objects early on.
Human thought can be characterised as being situated in the ‘space of reasons’. That is to say that human thought is guided by the norms of theoretical and practical rationality which, in turn, enable autonomous thinking. But how do children learn to navigate the space of reasons? Building on the work of Tugendhat and Bakhurst, among others, we argue, first, that this process involves the acquisition of propositional thought and that it is an essentially social one in which both children and adults take an active role. Second, and more specifically, by drawing on Brandom's theory of meaning, we provide a philosophical analysis of empirical findings with respect to the efficacy of ‘Sustained Shared Thinking’ (SST) in early educational settings. We argue that the efficacy of SST is based on its emphasising, modelling and practising those elements of communication that are essential for gaining proficiency in ‘playing the game of giving and asking for reasons’, namely drawing inferences between propositions and concepts and providing justifications for one's assertions. This is achieved by making explicit the inferential relationships between concepts and propositions and by the use of modal and doxastic markers that function as an invitation to a joint search for reasons.
The interplay between intuitive and deliberative processing is known to be important for human decision making. As independent modes, intuitive processes can take on many forms from associative to constructive, while deliberative processes often rely on some notion of decision theoretic rationality or pattern matching. Dual process models attempt to unify these two modes based on parallel constraint networks or on socially or emotionally oriented adjustments to utility functions. This paper presents a new kind of dual process model that unifies decision theoretic deliberative reasoning with intuitive reasoning based on shared cultural affective meanings in a single Bayesian sequential model. Agents constructed according to this unified model are motivated by a combination of affective alignment (intuitive) and decision theoretic reasoning (deliberative), trading the two off as a function of the uncertainty or unpredictability of the situation. The model also provides a theoretical bridge between decision-making research and sociological symbolic interactionism. Starting with a high-level view of existing models, we advance Bayesian Affect Control Theory (BayesACT) as a promising new type of dual process model that explicitly and optimally (in the Bayesian sense) trades off motivation, action, beliefs and utility. We demonstrate a key component of the model as being sufficient to account for some aspects of classic cognitive biases about fairness and dissonance, and outline how this new theory relates to parallel constraint satisfaction models.
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.
Bayesian affect control theory is a model of affect-driven social interaction underconditions of uncertainty. In this paper, we investigate how the operationalization of uncertainty in the model can be related to the disruption of social orders—societal pressures to adapt to ongoing environmental and technological change. First, we study the theoretical tradeoffs between three kinds of uncertainty as groups navigate external problems: validity (the predictability of the environment, including of other agents), coherence (the predictability of interpersonal affective dynamics), and dependence (the predictability of affective meanings). Second, we discuss how these uncertainty tradeoffs are related to contemporary political conflict and polarization in the context of societal transitions. To illustrate the potential of our model to analyze the socio-emotional consequences of uncertainty, we present a simulation of diverging individual affective meanings of occupational identities under uncertainty in a climate change mitigation scenario based on events in Germany. Finally, we sketch a possible research agenda to substantiate the novel, but yet mostly conjectural, ideas put forward in this paper.
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.
This research investigated how German-speaking children learn color words, both in terms of centroid mappings and boundary delineation, and how they construct the color lexicon as a connected system. The results were compared to those of Japanese children to draw insights on general mechanisms that underlie the acquisition of words in the color lexicon. For both languages, input frequency and category size contributed to the ease of learning. In contrast, in both language groups, naming (in)consistency in adults predicted the adult-like boundary delineation.
In the current study, 24- to 27-month-old children (N = 37) used pointing gestures in a cooperative object choice task with either peer or adult partners. When indicating the location of a hidden toy, children pointed equally accurately for adult and peer partners but more often for adult partners. When choosing from one of three hiding places, children used adults’ pointing to find a hidden toy significantly more often than they used peers’. In interaction with peers, children's choice behavior was at chance level. These results suggest that toddlers ascribe informative value to adults’ but not peers’ pointing gestures, and highlight the role of children's social expectations in their communicative development.
Emotion theory needs to explain the relationship of language and emotions, and the embodiment of emotions, by specifying the computational mechanisms underlying emotion generation in the brain. We used Chris Eliasmith’s Semantic Pointer Architecture to develop POEM, a computational model that explains numerous important phenomena concerning emotions, including how some stimuli generate immediate emotional reactions, how some emotional reactions depend on cognitive evaluations, how bodily states influence the generation of emotions, how some emotions depend on interactions between physiological inputs and cognitive appraisals, and how some emotional reactions concern syntactically complex representations. We contrast our theory with current alternatives, and discuss some possible applications to individual and social emotions.