Plasticity in fluid intelligence of older adults: An individual latent growth curve modeling application

This article is concerned with modeling the individual latent growth curves of older adults on measures of fluid intelligence in a 2‐group cognitive intervention study (Baltes, Dittmann‐Kohli, & Kliegl, 1986). Second‐order polynomial growth curves reflecting initial test performance improvement followed by relative stability/drop are fitted to the recorded scores of each participant. Experimental subjects are found to exhibit mean ability growth outperforming that shown by untrained subjects. Both the control and experimental groups, however, demonstrate the same pattern of interrelationships among the individual ability intercepts, linear slopes, and quadratic bend parameters of the growth curves. The results suggest substantial amount of plasticity in fluid intelligence of older adults, and that elders may be capable of considerably improving their performance on repeatedly presented fluid measures by capitalizing on interrelationships between fluid intelligence subabilities.     

Simultaneous study of individual and group patterns of latent longitudinal change using structural equation modeling

This article utilizes structural equation modeling for purposes of simultaneous study of individual and group latent change patterns on several longitudinally assessed variables. The approach is based on a special case of the comprehensive latent curve analysis by Meredith and Tisak (1990). Substantively interesting aspects of individual and group growth curves, as well as the interrelations among their patterns, are parameterized at the latent ability level. The method is illustrated on data from a two‐group study by Baltes, Dittmann‐Kohli, and Kliegl (1986).     

FLUID ABILITY TRAINING WITH AGED PEOPLE: A PAST WITH A FUTURE?

In an effort to define a future research agenda for gerontologically oriented cognitive training investigators, a number of issues crucial to the efficacy and utility of fluid (Gf) ability training with the aged are discussed. These issues involve (a) underlying mechanisms for fluid ability training, (b) individual differences in response to training, (c) practice effects in Gf performance, and (d) ecological validity. It is argued that these concerns have yet to be adequately understood as they bear on the modification of intellectual performance in elderly people and on the aging of intelligence.     

Cognitive training for children: Effects on inductive reasoning,deductive reasoning,and mathematics achievement in an Australian school setting

Inductive reasoning is a core cognitive process of fluid intelligence, predicting a variety of educational outcomes. The Cognitive Training for Children (CTC) program is an educational intervention designed to develop children's inductive reasoning skills, with previous investigations finding substantial effects of the program on both inductive reasoning ability and classroom learning. The present study assessed both individual and small‐group CTC training against a no‐treatment control condition to investigate the effects on inductive and deductive reasoning and mathematics achievement in a primary school‐aged Australian cohort. Students who received individual training outperformed those in the control condition on measures of inductive and deductive reasoning, and those in the small‐group condition also outperformed the control condition on a measure of inductive reasoning 3 months following training. However, hypotheses regarding transfer effects to mathematics achievement were not supported. Directions for future research, focusing on extended longitudinal studies and motivational variables, are discussed.     

‘Learning Style’: frameworks and instruments

In both education and training an important aspect of the design, development and delivery of learning is the role of individual differences between learners in terms of their ‘learning styles’. One may identify four broad categories of what have been termed ‘learning style’: (i) ‘cognitive personality elements’ (e.g. Witkin et al. 1977; Riding, 1991); (ii) ‘information‐processing style’ (e.g. Kolb, 1984; Honey & Mumford, 1992); (iii) ‘approaches to studying’ (e.g. Entwistle & Tait, 1994); (iv) ‘instructional preferences’ (e.g. Riechmann & Grasha, 1974). A study of 245 university undergraduates in business studies aimed to: (i) describe the range of individual differences present within the sample; (ii) investigate the relationship between learners’ cognitive styles, learning styles, approaches to studying and learning preferences; (iii) consider the implications of ‘learning style’ for teaching and learning in higher education. The present study suggested some overlap between the dimensions measured by the Learning Styles Questionnaire (Honey & Mumford, 1986; 1992) and the Revised Approaches to Studying Inventory (Entwistle & Tait, 1994). No statistically significant correlations were found between cognitive style, as measured by the Cognitive Styles Analysis (Riding, 1991) and any of the other ‘style’ constructs used. Further research is required to investigate these relationships, as is a large‐scale factor analytical study of the Honey and Mumford and Kolb instruments. The notions of whole brain functioning, integra‐tive approaches to studying and degree of learning activity are discussed.     

Infant Attention and Early Childhood Executive Function

Individual differences in infant attention are theorized to reflect the speed of information processing and are related to later cognitive abilities (i.e., memory, language, and intelligence). This study provides the first systematic longitudinal analysis of infant attention and early childhood executive function (EF; e.g., working memory, inhibitory control, cognitive flexibility). A group of 5‐month‐olds (n = 201) were classified as short or long lookers. At 24, 36, and 48 months of age, children completed age‐appropriate EF tasks. Infant short lookers (i.e., more efficient information processors) exhibited higher EF throughout early childhood as compared to infant long lookers, even after controlling for verbal ability (a potential indicator of intelligence). These findings are discussed in relation to the emergence of executive attention.     

A test of theoretical models that account for information processing demands

This study tested four theoretical models in terms of their fit with demands placed on our cognitive system by traditional tests of cognitive ability. We did so by administering seven tests of cognitive ability known to require varying types of processing demands to a large group of college undergraduates (N = 193). We compared the models using confirmatory factor analyses, including those based upon a unitary factor, speed and capacity, crystallized and fluid intelligence, and verbal and spatial ability. The crystallized/fluid model provided the best fit with the data. This finding is consistent with previous research. Implications for education and future research are discussed.     

Does Reading Cause Later Intelligence? Accounting for Stability in Models of Change

This study reanalyzes data presented by Ritchie, Bates, and Plomin (2015) who used a cross‐lagged monozygotic twin differences design to test whether reading ability caused changes in intelligence. The authors used data from a sample of 1,890 monozygotic twin pairs tested on reading ability and intelligence at five occasions between the ages of 7 and 16, regressing twin differences in intelligence on twin differences in prior intelligence and twin differences in prior reading ability. Results from a state–trait model suggest that reported effects of reading ability on later intelligence may be artifacts of previously uncontrolled factors, both environmental in origin and stable during this developmental period, influencing both constructs throughout development. Implications for cognitive developmental theory and methods are discussed.     

Prediction of reading by Ga and Gc specific cognitive abilities for low‐SES white and hispanic English‐speaking children

Based on previous findings (McGrew, Flanagan, Keith, & Vanderwood, 1997) that auditory processing (Ga) predicts reading decoding, and crystallized intelligence (Gc) predicts reading comprehension beyond the prediction of reading by g(broad general intelligence), this study examined the cross‐ethnic predictive validity of Ga and Gc for reading achievement among low‐SES English‐speaking White and Hispanic students. Subtests of the Woodcock‐Johnson Psycho‐Educational Battery‐Revised (WJ‐R) cognitive subtests were used to measure Ga and Gc, and the WJ‐R achievement subtests were used to measure basic reading skills and reading comprehension. Results indicated that there are no differences between ethnic groups in the prediction of reading ability, and that phonetic coding and crystallized intelligence together are strong predictors of reading achievement. © 2000 John Wiley & Sons, Inc.     

Proofreading as an index of crystallised intelligence

This paper reports on four studies that were all concerned with cognitive and non‐cognitive correlates of proofreading (PR) ability. A new, five‐minute PR test was devised and piloted. In the first pilot study (N = 191) it was correlated with a verbal reasoning test. In the second study (N = 103) PR scores were regressed onto measures of personality: approach to learning, general and fluid intelligence (verbal reasoning) as well as a test of general knowledge. All three cognitive ability measures were significant predictors of PR but when entered together, general knowledge alone remained significant and accounted for a third of the variance. The third study (N = 95) was similar, except it also included a measure of typical intellectual engagement. Fluid intelligence (verbal reasoning) and openness were the only significant predictors of PR. In the fourth study (N = 249) participants completed four tests: PR, fluid intelligence (verbal reasoning), vocabulary and spelling. PR was consistently correlated with verbal reasoning but more strongly correlated with measures of crystallised intelligence, namely general knowledge and vocabulary. Implications and limitations are considered.     

Does Learning to Read Improve Intelligence? A Longitudinal Multivariate Analysis in Identical Twins From Age 7 to 16

Evidence from twin studies points to substantial environmental influences on intelligence, but the specifics of this influence are unclear. This study examined one developmental process that potentially causes intelligence differences: learning to read. In 1,890 twin pairs tested at 7, 9, 10, 12, and 16 years, a cross‐lagged monozygotic‐differences design was used to test for associations of earlier within‐pair reading ability differences with subsequent intelligence differences. The results showed several such associations, which were not explained by differences in reading exposure and were not restricted to verbal cognitive domains. The study highlights the potentially important influence of reading ability, driven by the nonshared environment, on intellectual development and raises theoretical questions about the mechanism of this influence.     

Individual differences in speed of mental processing and human cognitive abilities: Toward a taxonomic model

Extensive research within the field of learning and individual differences focuses upon the relationship between general intelligence and process measures derived from elementary cognitive tasks (ECTs). This emphasis has ignored data indicating that cognitive abilities are best described by three levels (or strata). It has also been suggested that mental speed is a unitary construct, although it is more likely to have a complex structure. To address shortcomings evident in this literature, a multivariate investigation (N = 179) was conducted. Factor analysis of 25 psychometric indices gave seven factors postulated under the theory of fluid (G_f) and crystallized (G_c) intelligence. Correlations between cognitive abilities and parameters derived from 11 ECTs indicated that G_f (alone) was related to processing speed. This relationship is seemingly dependent upon experimental manipulations of task complexity. Regarding the factorial structure of mental speed, the results were unequivocal: Broad second-order factors may be derived from both ECTs and psychometric tests. These constructs are independent from abilities defined by accuracy scores and collectively define a general cognitive speed factor. Implications of these findings are discussed. It would appear that mental speed is more intricate than proposed, and that cognitive complexity (reflected in stimulus-response compatibility effects) plays a crucial role in its ontogenesis. In addition, several explanatory models linking intelligence to processing speed are untenable. It is likely that the search for a basic process of intelligence by means of mental speed frameworks (alone) is misguided.Recently, within the field of individual differences, there has been “an explosion of experimental studies into the speed of mental processes” (H.J. Eysenck 1995, p. 225). Various tasks, ranging from those paradigms assessing simple, psychomotor movements and on up through to measures of complex problem solving and psychometric test performance, have been employed (Stankov & Roberts 1997). The present study was designed to explore speed of processing constructs within a structural model of human cognitive abilities. Utilizing the evidence presented in Carroll's (1993) extensive reanalysis of the main data sets collected within the psychometric discipline this century, the structural model of cognitive abilities adopted is that known as the theory of fluid and crystallized intelligence (see Horn & Noll 1994; Stankov et al. 1995). In contrast, the mental speed measures selected for investigation in this study were chosen on the basis of both experimental and psychometric findings that rely on disparate accounts (e.g., information theory). Notably, mental speed constructs are not presently encapsulated within a single unifying model. Another major aim of the present study was to redress this imbalance by establishing a rapprochement between conceptual models of mental speed and human cognitive abilities.     

Differences in achievement not in intelligence in the north and south of Italy: Comments on ,

Lynn (2010a, 2010b) argued that individuals from south Italy have a lower IQ than individuals from north Italy, and that these differences in IQ are at the basis of north–south gap in income, education, infant mortality, stature, and literacy. In the present paper, we discuss several theoretical and methodological aspects which we regard as flaws of Lynn's studies. Moreover, we report scores of southern Italian children on Raven's Progressive Matrices and a north–south comparison for the PASS theory of intelligence as measured by the Cognitive Assessment System (Taddei & Naglieri, 2006). Both results reveal similar levels of performance of northern and southern Italian children in fluid intelligence and PASS (Planning, Attention, Simultaneous, and Successive) cognitive abilities.     

Predicting Long‐Term Growth in Students' Mathematics Achievement: The Unique Contributions of Motivation and Cognitive Strategies

This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long‐term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; M_age = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies.     

On the Concrete Nature of Human Thinking: content and context in analogical transfer

Although the development of abstract knowledge and critical thinking skills has often been extolled as an ideal and as the goal of education (Nisbett et al., 1987), much research in problem solving and other cognitive endeavours points to the role that concrete information and examples play in thinking (Medin & Ross, 1989; Reeves & Weisberg, in press). We discuss the concrete vs abstract knowledge debate in terms of the use of analogies in problem solving and conclude that exemplar‐specific details of problems and the context in which problems are learned guide the transfer of a solution principle from one base problem to a target. The content of problems—what they are about—is often more important than the more abstract, schematic solution principle in influencing retrieval of base analogues (Holyoak & Koh, 1987; Keane, 1987; Ross, 1987) and mapping of the solution principle from base to target (Gentner & Toupin, 1986; Ross, 1987, 1989; Fong & Nisbett, 1991). It is suggested that learning abstract solution principles in a domain (e.g. algebra, physics) benefits greatly when instruction is accompanied by examples illustrating those principles (Cheng et al., 1986; Fong et al., 1986) and that analogical transfer itself serves as a useful means to greater comprehension of a domain (Ross & Kennedy, 1990).     

Decreased Self-Reported Cognitive Failures after Memory Training

In recent years, attention has been focused on investigating the effectiveness of composite memory intervention programs with different age and diagnostics groups. The goal of this study was to measure changes in cognitive lapses by Cognitive Failure Questionnaire (CFQ) in a large trained, dementia free group (Mini-Mental State Examination [MMSE] > 26). The CFQ was administrated to older adults before training (Wave 1), after training (Wave 2), and in a six-month follow-up (Wave 3) to an experimental (N = 77; memory training) and control sample (N = 78, no intervention). Significant changes in subjective cognitive functioning in the experimental group and a plateau curve in the control group were observed. The results indicate support for the efficiency of a large memory-training group in promoting subjective cognitive functioning.     

Aging and Concurrent Task Performance: Cognitive Demand and Motor Control

A motor task that requires fine control of upper limb movements and a cognitive task that requires executive processing—first performing them separately and then concurrently—was performed by 18 young and 18 older adults. The motor task required participants to tap alternatively on two targets, the sizes of which varied systematically. The cognitive task required participants to generate a series of random numbers at fixed production rates. Participants' performance on the motor task decreased slightly from single- to concurrent-task condition, and the dual-task cost was age-independent. Older adults showed large cognitive dual-task costs as motor-control demands increased. Younger adults' cognitive performance was not affected by concurrent task demands. These results are discussed in light of the permeation model developed by Baltes and Lindenberger (1997 Baltes , P. B. & Lindenberger , U. ( 1997 ). Emergence of a powerful connection between sensory and cognitive functions across the adult life span: A new window to the study of cognitive aging? Psychology and Aging , 12 ( 1 ), 12 – 21 . [INFOTRIEVE] [CSA] [CROSSREF] [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). Practical implications and educational recommendations are presented.     

Intelligence and the tuning-in of brain networks

The phase-synchronization of Gamma-band oscillations has been postulated as a mechanism of “network binding” and implicated in various aspects of perception, memory, and cognition. The current study investigates a possible link between Gamma synchrony and individual differences in intelligence within the theory of fluid and crystallized intelligence, with due reference to Hebbian theory. The hypothesis is that there are significant correlations between cognitive performance and synchronous Gamma activity across diverse brain regions. EEG data were recorded from 35 healthy participants, and the peak magnitude and latency of early and late Gamma Synchrony were extracted using a method for quantifying phase synchronization across multiple sites. Participants also completed 11 diverse cognitive ability tests tapping fluid and crystallized intelligence. Overall, moderate-sized correlations were obtained between accuracy and speed composite scores, derived from the ability tests, and magnitude and latency indices of Gamma synchrony. Phase-synchronous Gamma activity provides a plausible physiological mechanism that might account for individual differences in cognitive abilities.     

The impact of individual differences and learning context on strategic skill acquisition and transfer

How individual differences in cognitive ability influence acquisition and transfer of strategic comparison skills was examined as a function of learning difficulty. Using a cognitive test battery, we classified forty-nine participants into three cognitive ability groups. Participants in each group were trained to compare similar (difficult training) or dissimilar (easy training) stimuli and then transferred to compare novel stimuli. Results suggest that overall individual differences in cognitive ability dictate the optimality of strategic skill development, though the effect of training difficulty on transfer performance varies with cognitive ability. Individuals with a midrange of cognitive ability are the most sensitive to the training context. Results are discussed with respect to the characteristics of strategic skills acquired and transferred.     

Increases in the verbal and fluid cognitive abilities of disadvantaged children attending preschool in the Netherlands

The current longitudinal study examined the development of general cognitive abilities of 4–6-year-old children of low-income, ethnic-minority families in preschool over two and a half years by determining the changes in general, and in verbal and fluid cognitive abilities, relative to age norms, using an intelligence test. The results revealed significant increases over time, relative to age norms, in full scale and in both verbal and fluid intelligence test scores of disadvantaged children, with medium effect sizes. These gains in measured intelligence were moderated by children's home language and age. Children who gained most also profited most from their increased abilities with respect to emergent school skills. Gains in verbal intelligence predicted emergent school vocabulary, but gains in fluid intelligence did not. Overall, gains in fluid intelligence predicted emergent math skills, and gains in verbal intelligence predicted emergent math skills only among older children.