Psychometric g—a statistical factor capturing intercorrelations between scores on different IQ tests—is of theoretical interest despite being a low-fidelity model of both folk psychological intelligence and its cognitive/neural underpinnings. Psychometric g idealizes away from those aspects of cognitive/neural mechanisms that are not explanatory of the relevant variety of folk psychological intelligence, and it idealizes away from those varieties of folk psychological intelligence that are not generated by the relevant cognitive/neural substrate. In this manner, g constitutes a high-fidelity bridge model of (...) the relationship between its two targets and, thereby, helps demystify the relationship between folk and scientific psychology. (shrink)

Some prominent scientists and philosophers have stated openly that moral and political considerations should influence whether we accept or promulgate scientific theories. This widespread view has significantly influenced the development, and public perception, of intelligence research. Theories related to group differences in intelligence are often rejected a priori on explicitly moral grounds. Thus the idea, frequently expressed by commentators on science, that science is “self-correcting”—that hypotheses are simply abandoned when they are undermined by empirical evidence—may not be correct in all (...) contexts. In this paper, documentation spanning from the early 1970s to the present is collected, which reveals the influence of scientists’ moral and political commitments on the study of intelligence. It is suggested that misrepresenting findings in science to achieve desirable social goals will ultimately harm both science and society. (shrink)

This paper elaborates the hypothesis that the unique demography and sociology of Ashkenazim in medieval Europe selected for intelligence. Ashkenazi literacy, economic specialization, and closure to inward gene flow led to a social environment in which there was high fitness payoff to intelligence, specifically verbal and mathematical intelligence but not spatial ability. As with any regime of strong directional selection on a quantitative trait, genetic variants that were otherwise fitness reducing rose in frequency. In particular we propose that the well-known (...) clusters of Ashkenazi genetic diseases, the sphingolipid cluster and the DNA repair cluster in particular, increase intelligence in heterozygotes. Other Ashkenazi disorders are known to increase intelligence. Although these disorders have been attributed to a bottleneck in Ashkenazi history and consequent genetic drift, there is no evidence of any bottleneck. Gene frequencies at a large number of autosomal loci show that if there was a bottleneck then subsequent gene flow from Europeans must have been very large, obliterating the effects of any bottleneck. The clustering of the disorders in only a few pathways and the presence at elevated frequency of more than one deleterious allele at many of them could not have been produced by drift. Instead these are signatures of strong and recent natural selection. (shrink)

Macphail’s comparative approach to intelligence focused on associative processes, an orientation inconsistent with more multifaceted lay and scientific understandings of the term. His ultimate emphasis on associative processes indicated few differences in intelligence among vertebrates. We explore options more attuned to common definitions by considering intelligence in terms of richness of representations of the world, the interconnectivity of those representations, the ability to flexibly change those connections, knowledge, and individual differences. We focus on marine mammals, represented by the amphibious pinnipeds (...) and the aquatic cetaceans and sirenians, as animals that transitioned from a terrestrial existence to an aquatic one, experiencing major changes in ecological pressures. They adapted with morphological transformations related to streamlining the body, physiological changes in respiration and thermoregulation, and sensory/perceptual changes, including echolocation capabilities and diminished olfaction in many cetaceans, both in-air and underwater visual focus, and enhanced senses of touch in pinnipeds and sirenians. Having a terrestrial foundation on which aquatic capacities were overlaid likely affected their cognitive abilities. Vocal and behavioral observational learning capabilities in the wild and in laboratory experiments suggest versatility in group coordination. Empirical reports on aspects of intelligent behavior like problem-solving, spatial learning, and concept learning by various species of cetaceans and pinnipeds, suggest rich cognitive abilities. The high energy demands of the brain suggest brain-intelligence relationships might be fruitful areas for the study when specific hypotheses are considered, e.g., brain mapping indicates hypertrophy of specific sensory areas in marine mammals. Modern neuroimaging techniques provide ways to study neural connectivity, and the patterns of connections between sensory, motor, and other cortical regions provide a biological framework for exploring how animals represent and flexibly use information in navigating and learning about their environment. At this stage of marine mammal research, it would still be prudent to follow Macphail’s caution that it is premature to make strong comparative statements without more empirical evidence, but an approach that includes learning more about how animals flexibly link information across multiple representations could be a productive way of comparing species by allowing them to use their specific strengths within comparative tasks. (shrink)

In this paper, we present a competency model for complex problem solving by building on the categories of Knowledge, Skills, Abilities, and Other components. We highlight domain-general and domain-specific components in each of these categories, review established conceptualizations of CPS, and present a new model of CPS competency that is meant to provide a starting point for systematic research on training and assessment. The model highlights the idea that complex problems differ with regard to the KSAO components they demand from (...) a problem solver and that performance in one problem does not necessarily predict performance in a different problem. Implications for research on the training and assessment of CPS competency are discussed, and a selection of well-established tests for various components of the KSAO model is provided. (shrink)

The Serial Reaction Time Task (SRTT) was designed to measure motor sequence learning and is widely used in many fields in cognitive science and neuroscience. However, the common performance measures derived from SRTT—reaction time (RT) difference scores—may not provide valid measures of sequence learning. This is because RT-difference scores may be subject to floor effects and otherwise not sufficiently reflective of learning. A ratio RT measure might minimize floor effects. Furthermore, measures derived from predictive accuracy may provide a better assessment (...) of sequence learning. Accordingly, we developed a Predictive Sequence Learning Task (PSLT) in which performance can be assessed via both RT and predictive accuracy. We compared performance of N = 99 adults on SRTT and PSLT in a within-subjects design and also measured fluid abilities. The RT-difference scores on both tasks were generally not related to fluid abilities, replicating previous findings. In contrast, a ratio RT measure on SRTT and PSLT and accuracy measures on PSLT were related to fluid abilities. The accuracy measures also indicated an age-related decline in performance on PSLT. The current patterns of results were thus inconsistent across different measures on the same tasks, and we demonstrate that this discrepancy is potentially due to floor effects on the RT difference scores. This may limit the potential of SRTT to measure sequence learning and we argue that PSLT accuracy measures could provide a more accurate reflection of learning ability. (shrink)

In the field of mathematics education, one of the main questions remaining under debate is whether students’ development of mathematical reasoning and problem-solving is aided more by solving tasks with given instructions or by solving them without instructions. It has been argued, that providing little or no instruction for a mathematical task generates a mathematical struggle, which can facilitate learning. This view in contrast, tasks in which routine procedures can be applied can lead to mechanical repetition with little or no (...) conceptual understanding. This study contrasts Creative Mathematical Reasoning (CMR), in which students must construct the mathematical method, with Algorithmic Reasoning (AR), in which predetermined methods and procedures on how to solve the task are given. Moreover, measures of fluid intelligence and working memory capacity are included in the analyses alongside the students’ math tracks. The results show that practicing with CMR tasks was superior to practicing with AR tasks in terms of students’ performance onpracticed test tasksandtransfer test tasks. Cognitive proficiency was shown to have an effect on students’ learning for both CMR and AR learning conditions. However, math tracks (advanced versus a more basic level) showed no significant effect. It is argued that going beyond step-by-step textbook solutions is essential and that students need to be presented with mathematical activities involving a struggle. In the CMR approach, students must focus on the relevant information in order to solve the task, and the characteristics of CMR tasks can guide students to the structural features that are critical for aiding comprehension. (shrink)

This target article considers the relation of fluid cognitive functioning to general intelligence. A neurobiological model differentiating working memory/executive function cognitive processes of the prefrontal cortex from aspects of psychometrically defined general intelligence is presented. Work examining the rise in mean intelligence-test performance between normative cohorts, the neuropsychology and neuroscience of cognitive function in typically and atypically developing human populations, and stress, brain development, and corticolimbic connectivity in human and nonhuman animal models is reviewed and found to provide evidence of (...) mechanisms through which early experience affects the development of an aspect of cognition closely related to, but distinct from, general intelligence. Particular emphasis is placed on the role of emotion in fluid cognition and on research indicating fluid cognitive deficits associated with early hippocampal pathology and with dysregulation of the hypothalamic-pituitary-adrenal axis stress-response system. Findings are seen to be consistent with the idea of an independent fluid cognitive construct and to assist with the interpretation of findings from the study of early compensatory education for children facing psychosocial adversity and from behavior genetic research on intelligence. It is concluded that ongoing development of neurobiologically grounded measures of fluid cognitive skills appropriate for young children will play a key role in understanding early mental development and the adaptive success to which it is related, particularly for young children facing social and economic disadvantage. Specifically, in the evaluation of the efficacy of compensatory education efforts such as Head Start and the readiness for school of children from diverse backgrounds, it is important to distinguish fluid cognition from psychometrically defined general intelligence. (Published Online April 5 2006) Key Words: cognition; cognition-emotion reciprocity; developmental disorders; emotion; fluid cognition; Flynn effect; general intelligence; limbic system; neuroscience; phenylketonuria; prefrontal cortex; psychometrics; schizophrenia. (shrink)