This paper reports the initial findings from a National Science Foundation supported study of IT personnel transition. We used the revealed causal mapping method [1] to elicit barriers, enablers, and examples of IT personnel transition. This paper reveals new knowledge and insight into the dependent variables of transition. The data is presented in the form of respondent quotes and interpretati...

Online social media are increasingly facilitating our social interactions, thereby making available a massive "digital fossil" of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the...

This paper provides a background discussion of agent -based modeling (ABM) and simulation of strategic scenarios. Causal mapping is introduced as a structured method for situational formulation and analysis of unstructured strategic problems. Causal mapping includes specific processes and analytical approaches offering cognitive modeling support for problem formulation and scenario planning. A ...

Aggregation is commonly thought to improve animals' security. Within aquatic ecosystems, group-living prey can learn about immediate threats using cues perceived directly from predators, or from collective behaviours, for example, by reacting to the escape behaviours of companions. Combining cues from different modalities may improve the accuracy of prey antipredatory decisions. In this study, ...

2 Gopnik, A. andMeltzoff, A.N. (1996)Words, Thoughts and Theories, MIT Press 3 Gelman, S. and Wellman, H. (1992) Cognitive development: foundational theories of core domains. Annu. Rev. Psychol. 43, 337–375 4 Griffiths, T.L. et al. (2010) Probabilistic models of cognition: exploring representations and inductive biases. Trends Cogn. Sci. 14, 357–364 5 Gopnik, A. et al. (2004) A theory of causal...

Research on the effectiveness of concept maps on learning has long being neglecting three critical issues; i.e., the schematically structured maps, learners’ perceptions of the maps, and the various ways of presenting concept structures. When concepts are associated by logical or causal rather than by subsumption relations, variations in selecting concepts and describing their relations may pre...

Causation plays a critical role in many predictive and inference tasks. Bayesian networks (BNs) have been used to construct inference systems for diagnostics and decision making. More recently, fuzzy cognitive maps (FCMs) have gained considerable attention and offer an alternative framework for representing structured human knowledge and causal inference. In this paper I briefly introduce Bayes...

A cognitive map, also called a mental map, is a representation and reasoning model on causal knowledge. It is a directed, labeled and cyclic graph whose nodes represent causes or effects and whose arcs represent causal relations between these nodes such as “increases”, “decreases”, “supports”, and “disadvantages”. A cognitive map represents beliefs (knowledge) which we lay out about a given dom...

We study a generalization of globally coupled maps, where the elements are updated with probability p. When p is below a threshold p(c), the collective motion vanishes and the system is the stationary state in the large size limit. We present the linear stability analysis.