Richard D. Roberts

The role of individual differences in the accuracy of confidence judgments.

Abstract Generally, self-assessment of accuracy in the cognitive domain produces overconfidence, whereas self-assessment of visual perceptual judgments results in under-confidence. Despite contrary empirical evidence, in models attempting to explain those phenomena, individual differences have often been disregarded. The authors report on 2 studies in which that shortcoming was addressed. In Experiment 1, participants (N = 520) completed a large number of cognitive-ability tests. Results indicated that individual differences provide a meaningful source of overconfidence and that a metacognitive trait might mediate that effect. In further analysis, there was only a relatively small correlation between test accuracy and confidence bias. In Experiment 2 (N = 107 participants), both perceptual and cognitive ability tests were included, along with measures of personality. Results again indicated the presence of a confidence factor that transcended the nature of the testing vehicle. Furthermore, a small relationship was found between that factor and some self-reported personality measures. Thus, personality traits and cognitive ability appeared to play only a small role in determining the accuracy of self-assessment. Collectively, the present results suggest that there are multiple causes of miscalibration, which current models of over- and underconfidence fail to encompass.

Development of Emotional Intelligence: Towards a Multi-Level Investment Model

This paper examines the development of emotional intelligence (EI) in childhood. It is proposed that ambiguities in conceptualizing EI may be resolved by distinguishing multiple levels of emotion-regulation processes. Temperament, rule-based skill acquisition, and self-aware emotion regulation are differentiat-ed as potential sources of individual differences. We review empirical studies that demonstrate multiple mechanisms linked to these levels. Temperament is shaped by genes, interacting with environmental influences such as patterns of infant-caregiver interaction. Early, language-dependent skill learning is governed by reinforcement and modeling processes. Subsequent, insightful learning is influenced by emotional discourse with parents and others, and cultural factors. Cognitive abilities may also influence individual differences in emotional function. At the same time, the biological and sociocultural factors that influence EI interact in complex and interrelated ways. We conclude this article by proposing a tentative ‘investment model’ for emotional competencies in children that accommodates the multifaceted nature of EI. Lower-level competencies may provide a platform for developing more sophisticated emotion-regulation skills, with competencies becoming increasingly differentiated over time.

Slow Down, You Move Too Fast: Emotional Intelligence Remains an "Elusive" Intelligence

Commentators on the R. D. Roberts, M. Zeidner, and G. Matthews (2001) article on the measurement of emotional intelligence (EI) made various pertinent observations that confirm the growing interest in this topic. This rejoinder finds general agreement on some key issues: learning from the history of ability testing, developing more sophisticated structural models of ability, studying emotional abilities across the life span, and establishing predictive and construct validity. However, scoring methods for tests of EI remain problematic. This rejoinder acknowledges recent improvements in convergence between different scoring methods but discusses further difficulties related to (a) neglect of group differences in normative social behaviors, (b) segregation of separate domains of knowledge linked to cognitive and emotional intelligences, (c) potential confounding of competence with learned skills and cultural factors, and (d) lack of specification of adaptive functions of EI. Empirical studies have not yet established that the Multi-Factor Emotional Intelligence Scale and related tests assess a broad EI factor of real-world significance.

Morningness–eveningness and intelligence: early to bed, early to rise will likely make you anything but wise!

Research examining various psychological correlates of circadian type (also known as diurnal preference) has been, over the years, quite expansive. A notable omission within this research program would appear a systematic exploration of the relation between intelligence and morningness-eveningness. The present study redressed this imbalance. 420 participants performed two self-report inventories assessing circadian type, as well as measures of intelligence from two psychometric batteries: CAM-IV and the ASVAB. The results indicate that, contrary to conventional folk wisdom, evening-types are more likely to have higher intelligence scores. This result is discussed in relation to current theories concerning the nature of human cognitive abilities.

The Emotional Intelligence, Health, and Well-Being Nexus: What Have We Learned and What Have We Missed?

This paper reviews the claimed pivotal role of emotional intelligence (EI) in well-being and health. Specifically, we examine the utility of EI in predicting health and well-being and point to future research issues that the field might profitably explore. EI is predictive of various indicators of well-being, as well as both physical and psychological health, but existing research has methodological limitations including over-reliance on self-report measures, and neglect of overlap between EI and personality measures. Interventions focusing on emotional perception, understanding and expression, and emotion regulation, seem potentially important for improving health and well-being, but research on EI has not yet made a major contribution to therapeutic practice. Future research, using a finer-grained approach to measurement of both predictors and criteria might most usefully focus on intra- and inter-personal processes that may mediate effects of EI on health. A video abstract of this article can be viewed at http://www.youtube.com/watch?v=2_8JZX1Uc4k.

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

Abstract 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 Carrolls (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.

Consensus scoring and empirical option weighting of performance-based Emotional Intelligence (EI) tests

Faces and Designs (N=102) from the Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) were scored using five different consensual-scoring methods: proportion, mode, lenient mode, distance, and adjusted distance. The aim was to determine which scoring methods were superior in terms of reliability, discriminability (distribution shape), and validity. Where possible, the Method of Reciprocal Averages (MRA)—used previously on dichotomously scored aptitude tests (to improve reliability)—was applied to consensus scores. Psychometric analyses suggested that the most promising techniques were proportion and mode scoring, with MRA scaling ameliorating some potential weaknesses apparent with these forms of consensual-scoring. Faces and Designs showed weak correlations with pro-social personality dimensions, with crystallized intelligence, and with visualization abilities. The study concludes with suggested remedies for addressing measurement problems endemic to EI research.

The Armed Services Vocational Aptitude Battery (ASVAB): Little more than acculturated learning (Gc)!?☆

The Armed Services Vocational Aptitude Battery (ASVAB) is administered to over 1 million participants in the USA each year, serving either as a screening test for military enlistees or as a guidance counseling device in high schools. In this paper, we examine the factorial composition of the ASVAB in relation to the theory of fluid and crystallized intelligence and Carrolls [1993. Human cognitive abilities: a survey of factor-analytic studies. New York: Cambridge Univ. Press.] three-stratum model. In two studies (N=349, N=6751), participants were administered both the ASVAB and tests designed to measure factors underlying these (largely) analogous models. Exploratory and confirmatory factor analyses (CFA) of correlational data suggested that the ASVAB primarily measures acculturated learning [crystallized intelligence (Gc)]. This evidence does not support the frequent claim that this test measures psychometric g. Our conclusion is that the ASVAB should be revised to incorporate the assessment of additional broad cognitive ability factors, particularly fluid intelligence and learning and memory constructs, if it is to maintain its postulated function.

Hick's Law, Competing-Task Performance, and Intelligence.

Abstract In recent times, psychologists have attempted to relate individual differences in intelligence either to differences in a subjects ability to divide attention or to differences in the speed with which they process the information offered by the environment. Because these approaches are not mutually exclusive and, indeed, have some important features in common, it was decided to examine the relationship between speed of processing and intelligence under conditions requiring divided attention. To this end, the Ravens Standard Progressive Matrices Test was administered to 48 subjects who subsequently performed a card-sorting task of varying information content under both single- and competing-task conditions. The obtained results point strongly to a more central role for complexity in speed of processing models of intelligence.

Mental speed is not the ‘basic’ process of intelligence☆

It is argued that a great deal of human intelligence research has unjustly overemphasised the role played by mental speed. While it is accepted that mental speed is an important aspect of intelligence, determination of this as the basic process underlying individual differences is a consequence of flawed logic. This may be attributed to several questionable research practices and/or theoretical shortcomings. These include: (a) The adoption of a narrow neo-Spearmanian model of intelligence; (b) Selective interpretation of the available empirical evidence wherein correlations between mental speed and intelligence measures are actually mediocre and certainly of no greater order of magnitude than many other elementary cognitive processes; (c) A failure to realise that the factorial composition of mental speed may be as complex as that for number correct (i.e. level) measures; (d) The acceptance of two main paradigms in the literature—Choice Reaction Time (CRT) and Inspection Time (IT)—both of which contain a number of unresolved controversies; (e) A tendency to examine in post hoc fashion those parameters of CRT and IT tasks that show correlations with measures of intelligence; (f) The absence of a satisfactory explanatory model to account for the correlations between mental speed and intelligence.