Scalable Science Education via Online Cooperative Questioning

How can the scalable powers of peer learning and online technologies be most effectively used to support conceptual understanding in science education? This paper reviews cognitive science research on how people learn via question answering and authoring and evaluates a promising novel learning design that applies these principles.

From Something Old to Something New: Functionalist Lessons for the Cognitive Science of Scientific Creativity

An intuitive view is that creativity involves bringing together what is already known and familiar in a way that produces something new. In cognitive science, this intuition is typically formalized in terms of computational processes that combine or associate internally represented information. From this computationalist perspective, it is hard to imagine how non-representational approaches in embodied cognitive science could shed light on creativity, especially when it comes to abstract conceptual reasoning of the kind scientists so often engage in. The present article offers an entry point to addressing this challenge. The scientific project of embodied cognitive science is a continuation of work in the functionalist tradition in psychology developed over a century ago by William James and John Dewey, among others. The focus here is on how functionalist views on the nature of mind, thought, and experience offer an alternative starting point for cognitive science in general, and for the cognitive science of scientific creativity in particular. The result may seem paradoxical. On the one hand, the article claims that the functionalist conceptual framework motivates rejecting mainstream cognitive views of creativity as the combination or association of ideas. On the other hand, however, the strategy adopted here—namely, revisiting ideas from functionalist psychology to inform current scientific theorizing—can itself be described as a process of arriving at new, creative ideas from combinations of old ones. As is shown here, a proper understanding of cognition in light of the functionalist tradition resolves the seeming tension between these two claims.

Mentalizing Mistakes: Distinguishing Mentalizing Ability from Bias in God Beliefs

The claim that religions are by-products of evolutionary adaptations has been at the center of the cognitive science of religion since its inception nearly three decades ago. It has been argued that religious beliefs are manifestations of evolved hyperactive agent detection and other mentalizing biases, whose development required pan-human mentalizing abilities. Much of the current research on the cognitive underpinnings of religiosity seems to rest on the assumption that not only mentalizing biases but also mentalizing abilities give rise to god beliefs in the minds of contemporary individuals. However, this presupposes that the higher capacity an individual has for mentalizing the more likely he or she is to make mentalizing mistakes. We illustrate the conceptual confusion that results from this way of framing the discussion and point to empirical evidence that challenges this notion.

Static-Dynamic Hybridity in Dynamical Models of Cognition

Dynamical models of cognition have played a central role in recent cognitive science. In this paper, we consider a common strategy by which dynamical models describe their target systems neither as purely static nor as purely dynamic, but rather using a hybrid approach. This hybridity reveals how dynamical models involve representational choices that are important for understanding the relationship between dynamical and non-dynamical representations of a system.

Cognition, complexity and context as other minds: a tribute to T. Givón

Linguistics is made up of great individuals. Throughout its not so long history as compared with other sciences, linguistics boasts many remarkable contributors who paved the way for human language study and thus led us into exploring the rising, development and evolution not only of natural languages, but also that of our own species. This book is a tribute to one of those great contributors to linguistics, T. Givón. As he argues for an evolutionary approach to communication and language, Givón has covered various research fields in linguistics such as morphosyntax, semantics, pragmatics, discourse and text, second language acquisition, pidgins and creoles, language universals, grammaticalization, and cognitive science.

Listening Effort Informed Quality of Experience Evaluation

Perceived quality of experience for speech listening is influenced by cognitive processing and can affect a listener's comprehension, engagement and responsiveness. Quality of Experience (QoE) is a paradigm used within the media technology community to assess media quality by linking quantifiable media parameters to perceived quality. The established QoE framework provides a general definition of QoE, categories of possible quality influencing factors, and an identified QoE formation pathway. These assist researchers to implement experiments and to evaluate perceived quality for any applications. The QoE formation pathways in the current framework do not attempt to capture cognitive effort effects and the standard experimental assessments of QoE minimize the influence from cognitive processes. The impact of cognitive processes and how they can be captured within the QoE framework have not been systematically studied by the QoE research community. This article reviews research from the fields of audiology and cognitive science regarding how cognitive processes influence the quality of listening experience. The cognitive listening mechanism theories are compared with the QoE formation mechanism in terms of the quality contributing factors, experience formation pathways, and measures for experience. The review prompts a proposal to integrate mechanisms from audiology and cognitive science into the existing QoE framework in order to properly account for cognitive load in speech listening. The article concludes with a discussion regarding how an extended framework could facilitate measurement of QoE in broader and more realistic application scenarios where cognitive effort is a material consideration.

The Perception of Automation Reliability and Acceptance of Automated Advice

Objective Examine (1) the extent to which humans can accurately estimate automation reliability and calibrate to changes in reliability, and how this is impacted by the recent accuracy of automation; and (2) factors that impact the acceptance of automated advice, including true automation reliability, reliability perception, and the difference between an operator’s perception of automation reliability and perception of their own reliability. Background Existing evidence suggests humans can adapt to changes in automation reliability but generally underestimate reliability. Cognitive science indicates that humans heavily weight evidence from more recent experiences. Method Participants monitored the behavior of maritime vessels (contacts) in order to classify them, and then received advice from automation regarding classification. Participants were assigned to either an initially high (90%) or low (60%) automation reliability condition. After some time, reliability switched to 75% in both conditions. Results Participants initially underestimated automation reliability. After the change in true reliability, estimates in both conditions moved towards the common true reliability, but did not reach it. There were recency effects, with lower future reliability estimates immediately following incorrect automation advice. With lower initial reliability, automation acceptance rates tracked true reliability more closely than perceived reliability. A positive difference between participant assessments of the reliability of automation and their own reliability predicted greater automation acceptance. Conclusion Humans underestimate the reliability of automation, and we have demonstrated several critical factors that impact the perception of automation reliability and automation use. Application The findings have potential implications for training and adaptive human-automation teaming.

Strategic Digital Informing and Its Challenges in the 21st Century

This chapter examines the challenges faced by digital informing technologies and civilization in the 21st century. The chapter begins by analyzing (1) the stages of development of strategic information technologies from the early 20th century up to the present as well as (2) the strategies adopted by informing science specializations (such as cognitive science, software engineering, etc.). Next, the chapter surveys major innovations in the history of strategic information technologies. This is followed by an analysis and evaluation of the concept of a laborless economy. The chapter concludes by positing a set of rules for workers in the digital economy that will ensure the wise development of civilization.

Cognitive Science of Tourism Experiences

While other disciplinary approaches such as sociology and anthropology are important, this chapter introduces a cognitivist psychology approach to experience research. Such theoretical discussion may seem of little practical use, but the chapter argues that it is fundamental to understanding how and why experiences are created. The chapter applies theory and concepts from cognitive science (cognitive psychology and neuroscience) in the study of tourism experiences. This provides a different psychological paradigm to the behavioural approach currently in use in much research. The chapter describes the scope of cognitive psychology and neuroscience, its main concepts of cognitive psychology (perception, attention, emotion, memory, consciousness, learning), and their neuronal basis (neuroscience). These concepts are then applied in three topic areas related to tourism experiences: decision making, emotion, and attention. Several applications to tourism experience research are noted. Finally, the chapter discusses the way cognitive psychology concepts can be used in tourism research.