Cognitive scientists have a variety of approaches to studying cognition: experimental psychology, computer science, robotics, neuroscience, educational psychology, philosophy of mind, and psycholinguistics, to name but a few. In addition, they also differ in their approaches to cognition - some of them consider that the mind works basically like a computer, involving programs composed of abstract, amodal, and arbitrary symbols. Others claim that cognition is embodied - that is, symbols must be grounded on perceptual, motoric, and emotional experience. The existence (...) of such different approaches has consequences when dealing with practical issues such as understanding brain disorders, designing artificial intelligence programs and robots, improving psychotherapy, or designing instructional programs. The symbolist and embodiment camps seldom engage in any kind of debate to clarify their differences. This book is the first attempt to do so. It brings together a team of outstanding scientists, adopting symbolist and embodied viewpoints, in an attempt to understand how the mind works and the nature of linguistic meaning. As well as being interdisciplinary, all authors have made an attempt to find solutions to substantial issues beyond specific vocabularies and techniques. (shrink)

It is often assumed that engaging in a one‐on‐one dialogue with a tutor is more effective than listening to a lecture or reading a text. Although earlier experiments have not always supported this hypothesis, this may be due in part to allowing the tutors to cover different content than the noninteractive instruction. In 7 experiments, we tested the interaction hypothesis under the constraint that (a) all students covered the same content during instruction, (b) the task domain was qualitative physics, (c) (...) the instruction was in natural language as opposed to mathematical or other formal languages, and (d) the instruction conformed with a widely observed pattern in human tutoring: Graesser, Person, and Magliano's 5‐step frame. In the experiments, we compared 2 kinds of human tutoring (spoken and computer mediated) with 2 kinds of natural‐language‐based computer tutoring (Why2‐Atlas and Why2‐AutoTutor) and 3 control conditions that involved studying texts. The results depended on whether the students' preparation matched the content of the instruction. When novices (students who had not taken college physics) studied content that was written for intermediates (students who had taken college physics), then tutorial dialogue was reliably more beneficial than less interactive instruction, with large effect sizes. When novices studied material written for novices or intermediates studied material written for intermediates, then tutorial dialogue was not reliably more effective than the text‐based control conditions. (shrink)

The proposed multilevel framework of discourse comprehension includes the surface code, the textbase, the situation model, the genre and rhetorical structure, and the pragmatic communication level. We describe these five levels when comprehension succeeds and also when there are communication misalignments and comprehension breakdowns. A computer tool has been developed, called Coh-Metrix, that scales discourse (oral or print) on dozens of measures associated with the first four discourse levels. The measurement of these levels with an automated tool helps researchers track (...) and better understand multilevel discourse comprehension. Two sets of analyses illustrate the utility of Coh-Metrix in discourse theory and educational practice. First, Coh-Metrix was used to measure the cohesion of the text base and situation model, as well as potential extraneous variables, in a sample of published studies that manipulated text cohesion. This analysis helped us better understand what was precisely manipulated in these studies and the implications for discourse comprehension mechanisms. Second, Coh-Metrix analyses are reported for samples of narrative and science texts in order to advance the argument that traditional text difficulty measures are limited because they fail to accommodate most of the levels of the multilevel discourse comprehension framework. (shrink)

It is often assumed that engaging in a one‐on‐one dialogue with a tutor is more effective than listening to a lecture or reading a text. Although earlier experiments have not always supported this hypothesis, this may be due in part to allowing the tutors to cover different content than the noninteractive instruction. In 7 experiments, we tested the interaction hypothesis under the constraint that (a) all students covered the same content during instruction, (b) the task domain was qualitative physics, (c) (...) the instruction was in natural language as opposed to mathematical or other formal languages, and (d) the instruction conformed with a widely observed pattern in human tutoring: Graesser, Person, and Magliano's 5‐step frame. In the experiments, we compared 2 kinds of human tutoring (spoken and computer mediated) with 2 kinds of natural‐language‐based computer tutoring (Why2‐Atlas and Why2‐AutoTutor) and 3 control conditions that involved studying texts. The results depended on whether the students' preparation matched the content of the instruction. When novices (students who had not taken college physics) studied content that was written for intermediates (students who had taken college physics), then tutorial dialogue was reliably more beneficial than less interactive instruction, with large effect sizes. When novices studied material written for novices or intermediates studied material written for intermediates, then tutorial dialogue was not reliably more effective than the text‐based control conditions. (shrink)

Events have beginnings, ends, and often overlap in time. A major question is how perceivers come to parse a stream of multimodal information into meaningful units and how different event boundaries may vary event processing. This work investigates the roles of these three types of event boundaries in constructing event temporal relations. Predictions were made based on how people would err according to the beginning state, end state, and overlap heuristic hypotheses. Participants viewed animated events that include all the logical (...) possibilities of event temporal relations, and then made temporal relation judgments. The results showed that people make use of the overlap between events and take into account the ends and beginnings, but they weight ends more than beginnings. Neural network simulations showed a self‐organized distinction when learning temporal relations between events with overlap versus those without. (shrink)

Most areas of the cognitive and social sciences assume that knowledge representations are constructed and used during communication and that much of its content is social. Those of us who build computer models of comprehension and conversation are forced to be explicit about the nature of these knowledge representations and affiliated processes. There are some conditions when knowledge is not sufficiently social, and other conditions when knowledge is overly grounded in social mechanisms. The argument is advanced that constraints, coherence, and (...) precision are very much at the heart of an explanation of the nature and amount of social knowledge. Asocial content reigns supreme when the referential world knowledge is highly constrained, coherently structured, and precisely specified. The social context of knowledge construction becomes progressively more influential to the extent to that world knowledge is vague, open-ended, imprecise, underspecified, and fragmentary. (shrink)

Top-down dynamical models of cognitive processes, such as the one presented by Thelen et al., are important pieces in understanding the development of cognitive abilities in humans and biological organisms. Unlike standard symbolic computational approaches to cognition, such dynamical models offer the hope that they can be connected with more bottom-up, neurologically inspired dynamical models to provide a complete view of cognition at all levels. We raise some questions about the details of their simulation and about potential limitations of top-down (...) dynamical models. (shrink)

Researchers in the field of discourse processing have investigated how mental models are constructed when adults comprehend stories. They have explored the process of encoding various classes of inferences “on-line” when these mental microworlds are constructed during comprehension. This commentary addresses the extent to which these inferences and mental microworlds are “embodied.”.

The meanings of abstract concepts depend on context. Perceptual symbol systems (PSS) provide a powerful framework for representing such context. Whereas a few expected difficulties for simulations are consistent with empirical findings, the theory does not clearly predict simulations of specific abstract concepts in a testable way and does not appear to distinguish abstract noun concepts (like truth) from their stem concepts (such as true).

Schyns, Goldstone & Thibaut present reasonable arguments for feature creation in category learning. We argue, however, that they do not provide unequivocal evidence either for the necessity or for the occurrence of feature creation. In an effort to sharpen the debate, we take the stand that a fixed feature approach is to be preferred in the absence of compelling evidence.