The article deals with research on framing effects. First, I will start with classifying different approaches on framing. Subsequently, I will provide a definition of the concepts of frame, schema and framing, expand on framing research conducted so far – both theoretically and operationally. Having this equipment at hand, I will initiate a discussion on studies of framing-effects in terms of theory, methods and empirical results. This discussion leads to the conclusion that studies on framing effects are insufficiently concerned with (...) the more recent psychological constructs and theories. In merely focusing on the activation of schemata, most studies ignore the more elaborate types of framing-effects. Therefore, several empirical questions remain unanswered and some methodical chances seem to be wasted. (shrink)

Mental spatial knowledge processing often uses spatio-analogical or quasipictorial representation structures such as spatial mental models or mental images. The cognitive architecture Casimir is designed to provide a framework for computationally modeling human spatial knowledge processing relying on these kinds of representation formats. In this article, we present an overview of Casimir and its components. We briefly describe the long-term memory component and the interaction with external diagrammatic representations. Particular emphasis is placed on Casimir’s working memory and control mechanisms. Regarding (...) working memory, we describe the conceptual foundations and the processing mechanisms employed in mental spatial reasoning. With respect to control, we explain how it is realized as a distributed, emergent facility within Casimir. (shrink)

ABSTRACTHow accurate are insights compared to analytical solutions? In four experiments, we investigated how participants' solving strategies influenced their solution accuracies across different types of problems, including one that was linguistic, one that was visual and two that were mixed visual-linguistic. In each experiment, participants' self-judged insight solutions were, on average, more accurate than their analytic ones. We hypothesised that insight solutions have superior accuracy because they emerge into consciousness in an all-or-nothing fashion when the unconscious solving process is complete, (...) whereas analytic solutions can be guesses based on conscious, prematurely terminated, processing. This hypothesis is supported by the finding that participants' analytic solutions included relatively more incorrect responses than timeouts compared to their insight responses. (shrink)

Research into intuitive problem solving has shown that objective closeness of participants’ hypotheses were closer to the accurate solution than their subjective ratings of closeness. After separating conceptually intuitive problem solving from the solutions of rational incremental tasks and of sudden insight tasks, we replicated this finding by using more precise measures in a conceptual problem-solving task. In a second study, we distinguished performance level, processing style, implicit knowledge and subjective feeling of closeness to the solution within the problem-solving task (...) and examined the relationships of these different components with measures of intelligence and personality. Verbal intelligence correlated with performance level in problem solving, but not with processing style and implicit knowledge. Faith in intuition, openness to experience, and conscientiousness correlated with processing style, but not with implicit knowledge. These findings suggest that one needs to decompose processing style and intuitive components in problem solving to make predictions on effects of intelligence and personality measures. (shrink)

The contents and structure of semantic memory have been the focus of much recent research, with major advances in the development of distributional models, which use word co‐occurrence information as a window into the semantics of language. In parallel, connectionist modeling has extended our knowledge of the processes engaged in semantic activation. However, these two lines of investigation have rarely been brought together. Here, we describe a processing model based on distributional semantics in which activation spreads throughout a semantic network, (...) as dictated by the patterns of semantic similarity between words. We show that the activation profile of the network, measured at various time points, can successfully account for response times in lexical and semantic decision tasks, as well as for subjective concreteness and imageability ratings. We also show that the dynamics of the network is predictive of performance in relational semantic tasks, such as similarity/relatedness rating. Our results indicate that bringing together distributional semantic networks and spreading of activation provides a good fit to both automatic lexical processing (as indexed by lexical and semantic decisions) as well as more deliberate processing (as indexed by ratings), above and beyond what has been reported for previous models that take into account only similarity resulting from network structure. (shrink)

In this prcis we focus on phenomena central to the reaction against similarity-based theories that arose in the 1980s and that subsequently motivated the approach to semantic knowledge. Specifically, we consider (1) how concepts differentiate in early development, (2) why some groupings of items seem to form or coherent categories while others do not, (3) why different properties seem central or important to different concepts, (4) why children and adults sometimes attest to beliefs that seem to contradict their direct experience, (...) (5) how concepts reorganize between the ages of 4 and 10, and (6) the relationship between causal knowledge and semantic knowledge. The explanations our theory offers for these phenomena are illustrated with reference to a simple feed-forward connectionist model. The relationships between this simple model, the broader theory, and more general issues in cognitive science are discussed. (shrink)

Do AI programs just make it quicker and easier for humans to do what they can do already, or can the range of do-able things be extended? This paper suggests that cognitively-oriented technology can make it possible for humans to construct and carry out mental operations, which were previously impossible. Probable constraints upon possible human mental operations are identified and the impact of cognitive technology upon them is evaluated. It is argued that information technology functions as a cognitive prosthetic enhancing (...) human intelligence and planning capabilities. Boundaries and constraints which Kant, Whorf, and many post-modernist theorists have seen as intrinsic to human cognition now cease to apply. (shrink)

Question processing involves parsing, memory retrieval, question categorization, initiation of appropriate answer‐retrieval heuristics, answer formulation, and output. Computational and psychological models have traditionally treated these processes as separate, sequential, independent, and in pursuit of a single answer type at a time. Here this view is challenged and the implications of a theory in which question processes operate simultaneously on multiple question interpretations are explored. A highly interactive model is described in which an expectation‐driven parser generates multiple question candidates, including partially‐specified (...) candidates. Question candidates act as constraints for a matcher which activates memory items. An answer retrieval process examines question candidates and the active portions of memory in an attempt to generate answer candidates. Answer candidates are examined by an output process that derives the final answer. These processes run simultaneously and interact. Three experiments on human question answering are also described which provide evidence that working memory load during question reading is affected by processes related to answer retrieval. (shrink)

Metaphors can provide a conceptual framework for understanding complex topics and as such, they have frequently been used in COVID-19 discourse. As previous research indicates that conceptual metaphors can influence how people reason about complex topics, the metaphors used to communicate about the pandemic can influence how it is understood and how people respond. This paper investigates the influence of metaphorical framing on emotions and reasoning. An experimental study compares BATTLE and JOURNEY metaphor frames in a hypothetical text (adapted from (...) previous studies) about the pandemic. Our aim is to examine the influence of these frames on readers’ affective state, inferences about the attitudes of others and suggestions to stop the virus from spreading. The results suggest that compared to JOURNEY metaphors, BATTLE metaphors can negatively influence affective state and may influence people to suggest more restrictive solutions to reduce the spread of the virus. Yet, metaphors were not found to influence reasoning about the attitudes of others. We interpret these results in relation to previous studies, suggesting that metaphors may influence emotions and reasoning in some ways only. The results have implications for public communication surrounding the pandemic. Limitations and avenues for future research are discussed. (shrink)

This study was aimed at explaining how and under what conditions surface similarity leads to the retrieval of an analogous base problem in LTM. Some elements of a theory of the organisation of knowledge in memory are proposed. Two levels of representation are distinguished. The first level represents directly accessible, local surface properties. The second level represents more abstract information pertaining to the category with which each analogous problem can be associated. Some results will be described showing that access to (...) an analogue in LTM based on surface properties is determined by the existence of a similarity at a higher level of abstraction. This is a search-area effect, in that categorical information seems to delimit a memory search space, within which the connection between local surface properties is more likely to be made. (shrink)

The computational view of mind rests on certain intuitions regarding the fundamental similarity between computation and cognition. We examine some of these intuitions and suggest that they derive from the fact that computers and human organisms are both physical systems whose behavior is correctly described as being governed by rules acting on symbolic representations. Some of the implications of this view are discussed. It is suggested that a fundamental hypothesis of this approach is that there is a natural domain of (...) human functioning that can be addressed exclusively in terms of a formal symbolic or algorithmic vocabulary or level of analysis. Much of the paper elaborates various conditions that need to be met if a literal view of mental activity as computation is to serve as the basis for explanatory theories. The coherence of such a view depends on there being a principled distinction between functions whose explanation requires that we posit internal representations and those that we can appropriately describe as merely instantiating causal physical or biological laws. In this paper the distinction is empirically grounded in a methodological criterion called the " cognitive impenetrability condition." Functions are said to be cognitively impenetrable if they cannot be influenced by such purely cognitive factors as goals, beliefs, inferences, tacit knowledge, and so on. Such a criterion makes it possible to empirically separate the fixed capacities of mind from the particular representations and algorithms used on specific occasions. In order for computational theories to avoid being ad hoc, they must deal effectively with the "degrees of freedom" problem by constraining the extent to which they can be arbitrarily adjusted post hoc to fit some particular set of observations. This in turn requires that the fixed architectural function and the algorithms be independently validated. It is argued that the architectural assumptions implicit in many contemporary models run afoul of the cognitive impenetrability condition, since the required fixed functions are demonstrably sensitive to tacit knowledge and goals. The paper concludes with some tactical suggestions for the development of computational cognitive theories. (shrink)

Neurons repeatedly exposed to similar perceptual experiences fire together and wire together to form ‘meaning kernels’ of concepts. Pulvermueller argues that abstract concepts may be devoid of meaning kernels, because the perceptual experiences that construct abstract concepts are subject to great variation and share few common features. Abstract concept are therefore grounded in the brain through features that belong to ‘meaning halos’, rather than to ‘meaning kernels’.

Teachers´ attitudes toward their students have been associated with differential teachers´ expectations and, in turn, with students´ educational pathways. Theories of social cognition can explain the link between attitudes and behavior. In this regard, the distinction between implicit and explicit attitudes is worth to be considered, whereby implicit attitudes are automatically activated when the attitude object is present and guide automatic behavior. In contrast, explicit attitudes infer deliberation and reflection, hence affecting controlled behavior. As teachers often are required to act (...) immediately in situations that do not allow for thoughtful reflection due to time restraints, teachers´ implicit attitudes concerning different student groups with shared characteristics, such as gender or ethnicity, may be especially important when considering teachers´ behavior in relation to students´ educational pathways. This notion is reflected by an increased interest in adopting implicit methodology in the educational domain. Over the last 10 years, several studies have been conducted in different countries, involving in- and preservice teachers and investigating their attitudes toward different student groups. Estimates of effects have varied and may be affected by sampling bias. To systematically review and integrate data from different studies, this meta-analysis focuses on teachers´ implicit attitudes. Following the systematic search of the database and initial screening, 43 articles were identified from which 22, describing 34 studies, were retained for the meta-analysis after further inspection. First analyses revealed an estimated average effect size of 0.56 for implicit attitudes in favor of non-marginalized groups. As there was a large extent of heterogeneity between studies, several moderator variables, were investigated. Results showed that the employed implicit measure and stimulus materials as well as the student target group affected the effect sizes. Low or non-significant relationships were reported between implicit and explicit attitudes. Findings are discussed in terms of theory and future research. (shrink)

We advance a model of human probability judgment and apply it to the design of an extrapolation algorithm. Such an algorithm examines a person's judgment about the likelihood of various statements and is then able to predict the same person's judgments about new statements. The algorithm is tested against judgments produced by thirty undergraduates asked to assign probabilities to statements about mammals.