Metacognition and Reflection by Interdisciplinary Experts: Insights from Cognitive Science and Philosophy

Interdisciplinary understanding requires integration of insights from different perspectives, yet it appears questionable whether disciplinary experts are well prepared for this. Indeed, psychological and cognitive scientific studies suggest that expertise can be disadvantageous because experts are often more biased than non-experts, for example, or fixed on certain approaches, and less flexible in novel situations or situations outside their domain of expertise. An explanation is that experts’ conscious and unconscious cognition and behavior depend upon their learning and acquisition of a set of mental representations or knowledge structures. Compared to beginners in a field, experts have assembled a much larger set of representations that are also more complex, facilitating fast and adequate perception in responding to relevant situations. This article argues how metacognition should be employed in order to mitigate such disadvantages of expertise: By metacognitively monitoring and regulating their own cognitive processes and representations, experts can prepare themselves for interdisciplinary understanding. Interdisciplinary collaboration is further facilitated by team metacognition about the team, tasks, process, goals, and representations developed in the team. Drawing attention to the need for metacognition, the article explains how philosophical reflection on the assumptions involved in different disciplinary perspectives must also be considered in a process complementary to metacognition and not completely overlapping with it. (Disciplinary assumptions are here understood as determining and constraining how the complex mental representations of experts are chunked and structured.) The article concludes with a brief reflection on how the process of Reflective Equilibrium should be added to the processes of metacognition and philosophical reflection in order for experts involved in interdisciplinary collaboration to reach a justifiable and coherent form of interdisciplinary integration. An Appendix of “Prompts or Questions for Metacognition” that can elicit metacognitive knowledge, monitoring, or regulation in individuals or teams is included at the end of the article

The Mechanics of Embodiment: A Dialogue on Embodiment and Computational Modeling

Embodied theories are increasingly challenging traditional views of cognition by arguing that conceptual representations that constitute our knowledge are grounded in sensory and motor experiences, and processed at this sensorimotor level, rather than being represented and processed abstractly in an amodal conceptual system. Given the established empirical foundation, and the relatively underspecified theories to date, many researchers are extremely interested in embodied cognition but are clamouring for more mechanistic implementations. What is needed at this stage is a push toward explicit computational models that implement sensory-motor grounding as intrinsic to cognitive processes. In this article, six authors from varying backgrounds and approaches address issues concerning the construction of embodied computational models, and illustrate what they view as the critical current and next steps toward mechanistic theories of embodiment. The first part has the form of a dialogue between two fictional characters: Ernest, the �experimenter�, and Mary, the �computational modeller�. The dialogue consists of an interactive sequence of questions, requests for clarification, challenges, and (tentative) answers, and touches the most important aspects of grounded theories that should inform computational modeling and, conversely, the impact that computational modeling could have on embodied theories. The second part of the article discusses the most important open challenges for embodied computational modelling

Constructing futures: a social constructionist perspective on foresight methodology

The aim of this paper is to demonstrate the relationship between a particular epistemological perspective and foresight methodology. We draw on a body of social theory concerned with the way that meaning is produced and assimilated by society; specifically, the social construction of knowledge, which is distinguished from its nearneighbour constructivism by its focus on inter-subjectivity. We show that social constructionism, at least in its weak form, seems to be implicit in many epistemological assumptions underlying futures studies. We identify a range of distinctive methodological features in foresight studies, such as time, descriptions of difference, participation and values, and examine these from a social constructionist perspective. It appears that social constructionism is highly resonant with the way in which knowledge of the future is produced and used. A social constructionism perspective enables a methodological reflection on how, with what legitimacy, and to what social good, knowledge is produced. Foresight that produces symbols without inter-subjective meaning neither anticipates, nor produces futures. Our conclusion is that foresight is both a social construction, and a mechanism for social construction. Methodologically, foresight projects should acknowledge the socially constructed nature of their process and outcomes as this will lead to greater rigour and legitimacy

A dual process account of creative thinking

This article explicates the potential role played by type 1 thinking (automatic, fast) and type 2 thinking (effortful, logical) in creative thinking. The relevance of Evans's (2007) models of conflict of dual processes in thinking is discussed with regards to creative thinking. The role played by type 1 thinking and type 2 thinking during the different stages of creativity (problem finding and conceptualization, incubation, illumination, verification and dissemination) is discussed. It is proposed that although both types of thinking are active in creativity, the extent to which they are active and the nature of their contribution to creativity will vary between stages of the creative process. Directions for future research to test this proposal are outlined; differing methodologies and the investigation of different stages of creative thinking are discussed. © Taylor & Francis Group, LLC

Teachers' and children's personal epistemologies for moral education: Case studies in early years elementary education

While there is strong interest in teaching values in Australia and internationally there is little focus on young children’s moral values learning in the classroom. Research shows that personal epistemology influences teaching and learning in a range of education contexts, including moral education. This study examines relationships between personal epistemologies (children’s and teachers’), pedagogies, and school contexts for moral learning in two early years classrooms. Interviews with teachers and children and analysis of school policy revealed clear patterns of personal epistemologies and pedagogies within each school. A whole school approach to understanding personal epistemologies and practice for moral values learning is suggested

The Pragmatic Turn in Explainable Artificial Intelligence (XAI)

In this paper I argue that the search for explainable models and interpretable decisions in AI must be reformulated in terms of the broader project of offering a pragmatic and naturalistic account of understanding in AI. Intuitively, the purpose of providing an explanation of a model or a decision is to make it understandable to its stakeholders. But without a previous grasp of what it means to say that an agent understands a model or a decision, the explanatory strategies will lack a well-defined goal. Aside from providing a clearer objective for XAI, focusing on understanding also allows us to relax the factivity condition on explanation, which is impossible to fulfill in many machine learning models, and to focus instead on the pragmatic conditions that determine the best fit between a model and the methods and devices deployed to understand it. After an examination of the different types of understanding discussed in the philosophical and psychological literature, I conclude that interpretative or approximation models not only provide the best way to achieve the objectual understanding of a machine learning model, but are also a necessary condition to achieve post hoc interpretability. This conclusion is partly based on the shortcomings of the purely functionalist approach to post hoc interpretability that seems to be predominant in most recent literature

Occupational Cultures as a Challenge to Technological Innovation

This paper explains conflict over technological process innovation in cultural terms, drawing primarily on a case study of electric power distribution and strategies to automate its operation