Antonymy and ten modern English color-names

One-hundred college-age monolingual speakers of American English were asked to indicate in writing the color that they believed to be the opposite of each of ten English color-names:white, black, red, green, blue, yellow, brown, tan, orange, andpink. The results of this experiment indicate that adult speakers of Modern English do not attribute the same degree of antonymy to all ten of these color-names.Black andwhite were clearly viewed by the subjects as having a high degree of antonymy. In fact, they were viewed as being the opposite of each other. Less antonymy was attributed to the other color-names, withorange andpink receiving the lowest scores on the Index of Relative Antonymy. Although this experiment was not designed to evaluate the Berlin and Kay (1969) hypothesis that color-names have been added to the languages of the world in accordance with an evolutionary sequence, a surprisingly high correlation (=0.94) was obtained between the relative antonymy of color-names found in this study and the evolutionary sequence of color-name acquisition postulated by Berlin and Kay. This finding suggests that the greater the antiquity of an English color-name, the greater the degree of antonymy attributed to it by adult speakers of Modern English.     

Exploring the Relationship Between Mathematics Anxiety and Performance: An Eye‐Tracking Approach

The mechanisms underpinning the relationship between math anxiety and arithmetic performance are not fully understood. This study used an eye‐tracking approach to measure a range of eye movements of 78 undergraduate students in response to performance on an arithmetic verification task. Results demonstrated a significant positive relationship between self‐reported math anxiety and response time, indicating reduced processing efficiency. Analysis of eye‐movement data reinforced the utility of an eye‐tracking approach in studying arithmetic performance; specific digit fixations, dwell time, saccades, and regressions all significantly predicted response time. Furthermore, findings highlighted significant positive correlations between math anxiety and fixations, dwell time, and saccades. Despite there being little evidence that eye movements mediate the math anxiety‐to‐performance relationship, relationships observed between math anxiety and eye movements provide a useful starting point for research using an eye‐tracking methodology in studying math anxiety and performance; the present findings suggest future work should focus on calculation strategy. Copyright © 2014 John Wiley & Sons, Ltd.     

A bifurcation theory for the instabilities of optimization and design

The world I grew up in believed that change and development in life are part of a continuous process of cause and effect, minutely and patiently sustained throughout the millenniums. With the exception of the initial act of creation ..., the evolution of life on earth was considered to be a slow, steady and ultimately demonstrable process. No sooner did I begin to read history, however, than I began to have my doubts. Human society and living beings, it seemed to me, ought to be excluded from so calm and rational a view. The whole of human development, far from having been a product of steady evolution, seemed subject to only partially explicable and almost invariably violent mutations. Entire cultures and groups of individuals appeared imprisoned for centuries in a static shape which they endured with long-suffering indifference, and then suddenly, for no demonstrable cause, became susceptible to drastic changes and wild surges of development. It was as if the movement of life throughout the ages was not a Darwinian caterpillar but a startled kangaroo, going out towards the future in a series of unpredictable hops, stops, skips and bounds. Indeed, when I came to study physics I had a feeling that the modern concept of energy could perhaps throw more light on the process than any of the more conventional approaches to the subject. It seemed that species, society and individuals behaved more like thunder-clouds than scrubbed, neatly clothed and well-behaved children of reason. Throughout the ages life appeared to build up great invisible charges, like clouds and earth of electricity, until suddenly in a sultry hour the spirit moved, the wind rose, a drop of rain fell acid in the dust, fire flared in the nerve, and drums rolled to produce what we call thunder and lightening in the heavens and chance and change in human society and personality.LAURENS VAN DER POST, The Lost World of the Kalahari     

How much “effort” should be devoted to memory?

We focus on the issue of whether cognitive effort is causally related to memory. We begin with a discussion of the concept of cognitive effort as derived from capacity models of attention. We then suggest that the theoretical analysis of memory may involve concepts from different levels of psychological analysis, and we draw a distinction between concepts that represent boundary conditions and sufficient cause. When applied to memory phenomena, attentional concepts serve only as a boundary--or limiting--function in memory theory. In contrast, concepts that represent memorial processes serve as a sufficient cause function. In some instances, cognitive effort appears to have been used as a sufficient cause concept, resulting in some confusion. A review of the literature reveals a haphazard correlation between indexes of cognitive effort and of memory performance. Alternatively, the application of cognitive effort or capacity to the memory performance of certain populations (clinical, children, and elderly) illustrates a potentially more appropriate use of the concept.     

Connectionist and rule-based representations of expert knowledge

Research in computer science has led to the development of two broad classes of models of knowledge representation: rule-based and connectionist systems. Both techniques solve the same abstract problem, that is, the assignment of cases to classes. Connectionist modeling techniques have been applied to three classification situations in which one would expect rule-based models to be applicable. Two of the situations involved the diagnosis of problems in and operation of a fictitious power plant. The third situation involved the classification of misconceptions held by elementary physics students. Connectionist modeling developed adequate simulations of behavior in all three cases.