Journal of Intelligence

19 pages, 2545 KiB

Open AccessEditor’s ChoiceArticle

Alpha Suppression Is Associated with the Tip-of-the-Tongue (TOT) State Whereas Alpha Expression Is Associated with Knowing That One Does Not Know

by Edmund Qian-Long Shen, David Friedman, Paul Alexander Bloom and Janet Metcalfe

J. Intell. 2022, 10(4), 121; https://doi.org/10.3390/jintelligence10040121 - 8 Dec 2022

Cited by 2 | Viewed by 3100

Abstract

The tip-of-the-tongue (TOT) state is a spontaneously occurring metacognitive state that indicates that the answer to a query is almost, but not quite, at hand, i.e., that resolution is imminent. Since the time of William James, a distinctive feeling of nagging frustration has [...] Read more.

The tip-of-the-tongue (TOT) state is a spontaneously occurring metacognitive state that indicates that the answer to a query is almost, but not quite, at hand, i.e., that resolution is imminent. Since the time of William James, a distinctive feeling of nagging frustration has been observed to be associated with TOT states. On a more positive note, TOT states are also associated with intense goal-directed curiosity and with a strong desire to know that translates into successful mental action. The present study showed that prior to the presentation of resolving feedback to verbal queries—if the individual was in a TOT state—alpha suppression was in evidence in the EEG. This alpha suppression appears to be a marker of a spontaneously occurring, conscious, and highly motivating goal-directed internal metacognitive state. At the same time, alpha expression in the same time period was associated with the feeling of not knowing, indicating a more discursive state. Both alpha and alpha suppression were observed broadly across centro-parietal scalp electrodes and disappeared immediately upon presentation of the resolving feedback. Analyses indicated that the occurrence of alpha suppression was associated with participants’ verbal affirmations of being in a TOT state, which is also related to subsequent expression of a late positivity when feedback is provided, and to enhanced memory. Full article

(This article belongs to the Special Issue Metareasoning: Theoretical and Methodological Developments)

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15 pages, 520 KiB

Open AccessEditor’s ChoiceCase Report

Bored, Distracted, and Confused: Emotions That Promote Creativity and Learning in a 28-Month-Old Child Using an iPad

by Shiva Khalaf, Hechmi Kilani, Melissa B. Razo and Elena L. Grigorenko

J. Intell. 2022, 10(4), 118; https://doi.org/10.3390/jintelligence10040118 - 2 Dec 2022

Cited by 4 | Viewed by 3872

Abstract

Digital technology is increasingly becoming a part of daily life, including the lives of children. Portable digital devices are omnipresent and integrated into activities that did not previously require them. The related skills are often referred to as 21st-century skills, constituting a new [...] Read more.

Digital technology is increasingly becoming a part of daily life, including the lives of children. Portable digital devices are omnipresent and integrated into activities that did not previously require them. The related skills are often referred to as 21st-century skills, constituting a new type of literacy: digital literacy. These devices and skills bring unique, innovative elements to the learning experience; yet, we do not know the extent to which behavior, emotion, and socialization are affected by such experience. For preschool-aged children, interactions with digital devices and games for the purposes of learning can lead to a state of confusion and boredom, an emotional driving force that may generate mind-wandering and exploration, which, in turn, may facilitate learning. Our interdisciplinary observational case study examined the behavioral patterns linked to digital game-based learning (DGBL) by observing how a child’s mind-wandering contributed to iPad use when they were allowed to freely engage with the device and explore independently during the learning process. Building on a previous case study of a 28-month-old boy, “Ryan”, we evaluated the effects of bouts of mind-wandering as he played various DGBL applications (apps) by examining the length of time that Ryan exhibited relevant affective and behavioral states, iPad manipulations, and social interaction during the playtime. Ryan’s interactions with the iPad were video recorded for five weeks, and the video footage was coded using a detailed rubric. The results indicated that negative emotions, such as boredom, distraction, and confusion, if coupled with attentiveness and persistence, led to positive mind-wandering and positive learning outcomes. However, when boredom was coupled with frustration, it led to negative mind-wandering and a lack of learning outcomes. In conclusion, our study presents evidence that DGBL apps may improve learning by capitalizing on positive and avoiding negative mind-wandering. Full article

(This article belongs to the Special Issue Creativity, Intelligence, and Collaboration in 21st Century Education: An Interdisciplinary Challenge)

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16 pages, 2653 KiB

Open AccessEditor’s ChoiceArticle

Pupillometry as a Window into Young Children’s Sustained Attention

by Viridiana L. Benitez and Matthew K. Robison

J. Intell. 2022, 10(4), 107; https://doi.org/10.3390/jintelligence10040107 - 16 Nov 2022

Cited by 5 | Viewed by 3456

Abstract

Sustained attention is critical to cognition, social competence, and academic success. Importantly, sustained attention undergoes significant development over the early childhood period. Yet, how sustained attention fluctuates over time on task has not been clearly outlined, particularly in young children. In this study, [...] Read more.

Sustained attention is critical to cognition, social competence, and academic success. Importantly, sustained attention undergoes significant development over the early childhood period. Yet, how sustained attention fluctuates over time on task has not been clearly outlined, particularly in young children. In this study, we provide a first test of whether the pupillary response can be used as an indicator of moment-to-moment sustained attention over time on task in young children. Children aged 5 to 7 years (N = 41) completed a psychomotor vigilance task, where they were asked to press a button as fast as possible at the onset of a target stimulus. We measured reaction times over the course of the task, pupil size prior to target onset (baseline pupil size), and pupil size in response to target onset (task-evoked pupil size). The results showed a stereotypical vigilance decrement in children’s response times: as time on task increased, reaction times increased. Critically, children’s task-evoked pupil size decreased over time on task, while no such change was present in baseline pupil size. These results suggest that young children’s waning sustained attention may be linked to a decrease in alertness while overall arousal is maintained. We discuss the importance of leveraging pupillometry to understand the mechanisms of sustained attention over individuals and development. Full article

(This article belongs to the Special Issue The Development of Working Memory and Attention)

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18 pages, 557 KiB

Open AccessEditor’s ChoiceArticle

Fluid Intelligence Emerges from Representing Relations

by Adam Chuderski

J. Intell. 2022, 10(3), 51; https://doi.org/10.3390/jintelligence10030051 - 2 Aug 2022

Cited by 4 | Viewed by 4793

Abstract

Based on recent findings in cognitive neuroscience and psychology as well as computational models of working memory and reasoning, I argue that fluid intelligence (fluid reasoning) can amount to representing in the mind the key relation(s) for the task at hand. Effective representation [...] Read more.

Based on recent findings in cognitive neuroscience and psychology as well as computational models of working memory and reasoning, I argue that fluid intelligence (fluid reasoning) can amount to representing in the mind the key relation(s) for the task at hand. Effective representation of relations allows for enormous flexibility of thinking but depends on the validity and robustness of the dynamic patterns of argument–object (role–filler) bindings, which encode relations in the brain. Such a reconceptualization of the fluid intelligence construct allows for the simplification and purification of its models, tests, and potential brain mechanisms. Full article

(This article belongs to the Special Issue Cognitive Flexibility: Concepts, Issues and Assessment)

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29 pages, 2064 KiB

Open AccessEditor’s ChoiceArticle

Intelligence IS Cognitive Flexibility: Why Multilevel Models of Within-Individual Processes Are Needed to Realise This

by Damian P. Birney and Jens F. Beckmann

J. Intell. 2022, 10(3), 49; https://doi.org/10.3390/jintelligence10030049 - 1 Aug 2022

Cited by 14 | Viewed by 4425

Abstract

Despite substantial evidence for the link between an individual’s intelligence and successful life outcomes, questions about what defines intelligence have remained the focus of heated dispute. The most common approach to understanding intelligence has been to investigate what performance on tests of intellect [...] Read more.

Despite substantial evidence for the link between an individual’s intelligence and successful life outcomes, questions about what defines intelligence have remained the focus of heated dispute. The most common approach to understanding intelligence has been to investigate what performance on tests of intellect is and is not associated with. This psychometric approach, based on correlations and factor analysis is deficient. In this review, we aim to substantiate why classic psychometrics which focus on between-person accounts will necessarily provide a limited account of intelligence until theoretical considerations of within-person accounts are incorporated. First, we consider the impact of entrenched psychometric presumptions that support the status quo and impede alternative views. Second, we review the importance of process-theories, which are critical for any serious attempt to build a within-person account of intelligence. Third, features of dynamic tasks are reviewed, and we outline how static tasks can be modified to target within-person processes. Finally, we explain how multilevel models are conceptually and psychometrically well-suited to building and testing within-individual notions of intelligence, which at its core, we argue is cognitive flexibility. We conclude by describing an application of these ideas in the context of microworlds as a case study. Full article

(This article belongs to the Special Issue Cognitive Flexibility: Concepts, Issues and Assessment)

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10 pages, 313 KiB

Open AccessEditor’s ChoiceArticle

Selecting for Learning Potential: Is Implicit Learning the New Cognitive Ability?

by Luke M. Montuori and Lara Montefiori

J. Intell. 2022, 10(2), 24; https://doi.org/10.3390/jintelligence10020024 - 15 Apr 2022

Cited by 1 | Viewed by 4778

Abstract

For decades, the field of workplace selection has been dominated by evidence that cognitive ability is the most important factor in predicting performance. Meta-analyses detailing the contributions of a wide-range of factors to workplace performance show that cognitive ability’s contribution is partly mediated [...] Read more.

For decades, the field of workplace selection has been dominated by evidence that cognitive ability is the most important factor in predicting performance. Meta-analyses detailing the contributions of a wide-range of factors to workplace performance show that cognitive ability’s contribution is partly mediated by the learning of task-relevant skills and job-specific declarative knowledge. Further, there is evidence to suggest that this relationship is a function of task complexity, and partially mediated by learning performance in workplace induction and training activities. Simultaneously, evidence is mounting that stable individual differences in implicit learning exist, which are at least partially independent of traditional measures of intelligence. In this article we provide an overview of recent advances in our understanding of implicit learning, outline some of the advantages offered by its measurement, and highlight some of the challenges associated with its adoption as a measure of interest. Full article

(This article belongs to the Special Issue Intelligence and the Future of Work: Assessment, Relevance and Application of Cognitive and Other Abilities in the Age of Artificial Intelligence)

21 pages, 459 KiB

Open AccessEditor’s ChoiceArticle

Student Characteristics, Institutional Factors, and Outcomes in Higher Education and Beyond: An Analysis of Standardized Test Scores and Other Factors at the Institutional Level with School Rankings and Salary

by Jonathan Wai and Bich Tran

J. Intell. 2022, 10(2), 22; https://doi.org/10.3390/jintelligence10020022 - 1 Apr 2022

Cited by 2 | Viewed by 5485

Abstract

When seeking to explain the eventual outcomes of a higher education experience, do the personal attributes and background factors students bring to college matter more than what the college is able to contribute to the development of the student through education or other [...] Read more.

When seeking to explain the eventual outcomes of a higher education experience, do the personal attributes and background factors students bring to college matter more than what the college is able to contribute to the development of the student through education or other institutional factors? Most education studies tend to simply ignore cognitive aptitudes and other student characteristics—in particular the long history of research on this topic—since the focus is on trying to assess the impact of education. Thus, the role of student characteristics has in many ways been underappreciated in even highly sophisticated quantitative education research. Conversely, educational and institutional factors are not as prominent in studies focused on cognitive aptitudes, as these fields focus first on reasoning capacity, and secondarily on other factors. We examine the variance in student outcomes due to student (e.g., cognitive aptitudes) versus institutional characteristics (e.g., teachers, schools). At the level of universities, two contemporary U.S. datasets are used to examine the proportion of variance accounted for in various university rankings and long-run salary by student cognitive characteristics and institutional factors. We find that depending upon the ways the variables are entered into regression models, the findings are somewhat different. We suggest some fruitful paths forward which might integrate the methods and findings showing that teachers and schools matter, along with the broader developmental bounds within which these effects take place. Full article

(This article belongs to the Special Issue Intelligence, Competencies, and Learning)

12 pages, 346 KiB

Open AccessEditor’s ChoiceArticle

On the Relation between the Development of Working Memory Updating and Working Memory Capacity in Preschoolers

by Sabrina Panesi, Alessia Bandettini, Laura Traverso and Sergio Morra

J. Intell. 2022, 10(1), 5; https://doi.org/10.3390/jintelligence10010005 - 21 Jan 2022

Cited by 11 | Viewed by 4222

Abstract

This study aims at investigating the relationship between working memory updating and working memory capacity in preschool children. A sample of 176 preschoolers (36–74 months) was administered a working memory updating task (Magic House) along with three working memory capacity tests that specifically [...] Read more.

This study aims at investigating the relationship between working memory updating and working memory capacity in preschool children. A sample of 176 preschoolers (36–74 months) was administered a working memory updating task (Magic House) along with three working memory capacity tests that specifically measure their core attentional component (M capacity, as defined in the theory of constructive operators): Backward Word Span, Mr. Cucumber, and Direction Following Task. Correlational analyses and cross-classification prediction analyses were performed. Updating and capacity were significantly correlated, although the correlations were not high when age was partialled out. Capacity increased with age, and mediated the relation between age and updating. More importantly, cross-classification prediction analysis revealed that high updating scores with low M capacity, and low updating scores with relatively high M capacity, are possible events; the only combination ruled out was a low updating score with precocious development of M capacity. These facts demonstrate that updating skills in preschoolers depends on M capacity but does not coincide with it. Therefore, in cognitive developmental theories, the constructs of working memory updating and capacity should be distinguished, and on practical grounds, different tests should be used to measure them. Full article

27 pages, 2014 KiB

Open AccessEditor’s ChoiceArticle

Exploring Neural Signal Complexity as a Potential Link between Creative Thinking, Intelligence, and Cognitive Control

by Yadwinder Kaur, Selina Weiss, Changsong Zhou, Rico Fischer and Andrea Hildebrandt

J. Intell. 2021, 9(4), 59; https://doi.org/10.3390/jintelligence9040059 - 30 Nov 2021

Cited by 8 | Viewed by 5620

Abstract

Functional connectivity studies have demonstrated that creative thinking builds upon an interplay of multiple neural networks involving the cognitive control system. Theoretically, cognitive control has generally been discussed as the common basis underlying the positive relationship between creative thinking and intelligence. However, the [...] Read more.

Functional connectivity studies have demonstrated that creative thinking builds upon an interplay of multiple neural networks involving the cognitive control system. Theoretically, cognitive control has generally been discussed as the common basis underlying the positive relationship between creative thinking and intelligence. However, the literature still lacks a detailed investigation of the association patterns between cognitive control, the factors of creative thinking as measured by divergent thinking (DT) tasks, i.e., fluency and originality, and intelligence, both fluid and crystallized. In the present study, we explored these relationships at the behavioral and the neural level, based on N = 77 young adults. We focused on brain-signal complexity (BSC), parameterized by multi-scale entropy (MSE), as measured during a verbal DT and a cognitive control task. We demonstrated that MSE is a sensitive neural indicator of originality as well as inhibition. Then, we explore the relationships between MSE and factor scores indicating DT and intelligence. In a series of across-scalp analyses, we show that the overall MSE measured during a DT task, as well as MSE measured in cognitive control states, are associated with fluency and originality at specific scalp locations, but not with fluid and crystallized intelligence. The present explorative study broadens our understanding of the relationship between creative thinking, intelligence, and cognitive control from the perspective of BSC and has the potential to inspire future BSC-related theories of creative thinking. Full article

(This article belongs to the Special Issue Intelligence and Creativity)

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11 pages, 329 KiB

Open AccessEditor’s ChoicePerspective

Intelligence Can Be Used to Make a More Equitable Society but Only When Properly Defined and Applied

by LaTasha R. Holden and Sara A. Hart

J. Intell. 2021, 9(4), 57; https://doi.org/10.3390/jintelligence9040057 - 25 Nov 2021

Cited by 7 | Viewed by 8266

Abstract

In the US, undeniable evidence shows that socioeconomic inequities explain a high proportion of individual differences in school achievement. Although not all countries show this same effect due to socioeconomic status, it is consistently found that social inequities lead to achievement gaps. These [...] Read more.

In the US, undeniable evidence shows that socioeconomic inequities explain a high proportion of individual differences in school achievement. Although not all countries show this same effect due to socioeconomic status, it is consistently found that social inequities lead to achievement gaps. These achievement gaps then manifest into trajectories that set some individuals on a path of lower incomes, poorer health and higher mortality, lower wellbeing, and other poor adult outcomes. Like James Flynn so handily reminded the scientific literature that achievement gaps are explainable by environmental factors, the inequities we see around the world are based on environments some children are exposed to. In his work, Flynn stated his belief that the suppression of scientific work on intelligence would continue to lead to social inequities. We wish to take this idea and move it forward. We believe that the scientific construct of intelligence plays a key role in helping create a more equitable society through science. We also believe that the poor perception of intelligence, rooted in historical realities, means that it will continue to be misunderstood, feared, and misused, limiting how effective it could be in helping to close gaps in achievement and in creating a more equitable society. Full article

(This article belongs to the Special Issue How Intelligence Can Be a Solution to Consequential World Problems)

23 pages, 846 KiB

Open AccessEditor’s ChoiceArticle

In Search of the Executive Cognitive Processes Proposed by Process-Overlap Theory

by Gidon T. Frischkorn and Claudia C. von Bastian

J. Intell. 2021, 9(3), 43; https://doi.org/10.3390/jintelligence9030043 - 19 Aug 2021

Cited by 9 | Viewed by 5031

Abstract

Process-Overlap Theory (POT) suggests that measures of cognitive abilities sample from sets of independent cognitive processes. These cognitive processes can be separated into domain-general executive processes, sampled by the majority of cognitive ability measures, and domain-specific processes, sampled only by measures within a [...] Read more.

Process-Overlap Theory (POT) suggests that measures of cognitive abilities sample from sets of independent cognitive processes. These cognitive processes can be separated into domain-general executive processes, sampled by the majority of cognitive ability measures, and domain-specific processes, sampled only by measures within a certain domain. According to POT, fluid intelligence measures are related because different tests sample similar domain-general executive cognitive processes to some extent. Re-analyzing data from a study by De Simoni and von Bastian (2018), we assessed domain-general variance from executive processing tasks measuring inhibition, shifting, and efficiency of removal from working memory, as well as examined their relation to a domain-general factor extracted from fluid intelligence measures. The results showed that domain-general factors reflecting general processing speed were moderately and negatively correlated with the domain-general fluid intelligence factor (r = ?.17–?.36). However, domain-general factors isolating variance specific to inhibition, shifting, and removal showed only small and inconsistent correlations with the domain-general fluid intelligence factor (r = .02–?.22). These findings suggest that (1) executive processing tasks sample only few domain-general executive processes also sampled by fluid intelligence measures, as well as (2) that domain-general speed of processing contributes more strongly to individual differences in fluid intelligence than do domain-general executive processes. Full article

(This article belongs to the Special Issue g and Its Underlying Executive Processes)

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21 pages, 3060 KiB

Open AccessEditor’s ChoiceArticle

Bridging Brain and Cognition: A Multilayer Network Analysis of Brain Structural Covariance and General Intelligence in a Developmental Sample of Struggling Learners

by Ivan L. Simpson-Kent, Eiko I. Fried, Danyal Akarca, Silvana Mareva, Edward T. Bullmore, the CALM Team and Rogier A. Kievit

J. Intell. 2021, 9(2), 32; https://doi.org/10.3390/jintelligence9020032 - 15 Jun 2021

Cited by 13 | Viewed by 6751

Abstract

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific [...] Read more.

Network analytic methods that are ubiquitous in other areas, such as systems neuroscience, have recently been used to test network theories in psychology, including intelligence research. The network or mutualism theory of intelligence proposes that the statistical associations among cognitive abilities (e.g., specific abilities such as vocabulary or memory) stem from causal relations among them throughout development. In this study, we used network models (specifically LASSO) of cognitive abilities and brain structural covariance (grey and white matter) to simultaneously model brain–behavior relationships essential for general intelligence in a large (behavioral, N = 805; cortical volume, N = 246; fractional anisotropy, N = 165) developmental (ages 5–18) cohort of struggling learners (CALM). We found that mostly positive, small partial correlations pervade our cognitive, neural, and multilayer networks. Moreover, using community detection (Walktrap algorithm) and calculating node centrality (absolute strength and bridge strength), we found convergent evidence that subsets of both cognitive and neural nodes play an intermediary role ‘between’ brain and behavior. We discuss implications and possible avenues for future studies. Full article

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7 pages, 245 KiB

Open AccessEditor’s ChoiceReview

Critical Thinking: A Model of Intelligence for Solving Real-World Problems

by Diane F. Halpern and Dana S. Dunn

J. Intell. 2021, 9(2), 22; https://doi.org/10.3390/jintelligence9020022 - 7 Apr 2021

Cited by 47 | Viewed by 12251

Abstract

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive [...] Read more.

Most theories of intelligence do not directly address the question of whether people with high intelligence can successfully solve real world problems. A high IQ is correlated with many important outcomes (e.g., academic prominence, reduced crime), but it does not protect against cognitive biases, partisan thinking, reactance, or confirmation bias, among others. There are several newer theories that directly address the question about solving real-world problems. Prominent among them is Sternberg’s adaptive intelligence with “adaptation to the environment” as the central premise, a construct that does not exist on standardized IQ tests. Similarly, some scholars argue that standardized tests of intelligence are not measures of rational thought—the sort of skill/ability that would be needed to address complex real-world problems. Other investigators advocate for critical thinking as a model of intelligence specifically designed for addressing real-world problems. Yes, intelligence (i.e., critical thinking) can be enhanced and used for solving a real-world problem such as COVID-19, which we use as an example of contemporary problems that need a new approach. Full article

(This article belongs to the Special Issue How Intelligence Can Be a Solution to Consequential World Problems)

15 pages, 1207 KiB

Open AccessEditor’s ChoiceArticle

The Relationship between Theory of Mind and Intelligence: A Formative g Approach

by Ester Navarro, Sara Anne Goring and Andrew R. A. Conway

J. Intell. 2021, 9(1), 11; https://doi.org/10.3390/jintelligence9010011 - 19 Feb 2021

Cited by 11 | Viewed by 5019

Abstract

Theory of Mind (ToM) is the ability understand that other people’s mental states may be different from one’s own. Psychometric models have shown that individual differences in ToM can largely be attributed to general intelligence (g) (Coyle et al. 2018). Most [...] Read more.

Theory of Mind (ToM) is the ability understand that other people’s mental states may be different from one’s own. Psychometric models have shown that individual differences in ToM can largely be attributed to general intelligence (g) (Coyle et al. 2018). Most psychometric models specify g as a reflective latent variable, which is interpreted as a general ability that plays a causal role in a broad range of cognitive tasks, including ToM tasks. However, an alternative approach is to specify g as a formative latent variable, that is, an overall index of cognitive ability that does not represent a psychological attribute (Kovacs and Conway 2016). Here we consider a formative g approach to the relationship between ToM and intelligence. First, we conducted an SEM with reflective g to test the hypothesis that ToM is largely accounted for by a general ability. Next, we conducted a model with formative g to determine whether the relationship between ToM and intelligence is influenced by domain-specific tasks. Finally, we conducted a redundancy analysis to examine the contribution of each g variable. Results suggest that the relationship between ToM and intelligence in this study was influenced by language-based tasks, rather than solely a general ability. Full article

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27 pages, 976 KiB

Open AccessEditor’s ChoiceArticle

Intelligence and Creativity: Mapping Constructs on the Space-Time Continuum

by Giovanni Emanuele Corazza and Todd Lubart

J. Intell. 2021, 9(1), 1; https://doi.org/10.3390/jintelligence9010001 - 30 Dec 2020

Cited by 43 | Viewed by 11252

Abstract

This theoretical article proposes a unified framework of analysis for the constructs of intelligence and creativity. General definitions for intelligence and creativity are provided, allowing fair comparisons between the two context-embedded constructs. A novel taxonomy is introduced to classify the contexts in which [...] Read more.

This theoretical article proposes a unified framework of analysis for the constructs of intelligence and creativity. General definitions for intelligence and creativity are provided, allowing fair comparisons between the two context-embedded constructs. A novel taxonomy is introduced to classify the contexts in which intelligent and/or creative behavior can be embedded, in terms of the tightness vs. looseness of the relevant conceptual space S and available time T. These two dimensions are used to form what is identified as the space-time continuum, containing four quadrants: tight space and tight time, loose space and tight time, tight space and loose time, loose space and loose time. The intelligence and creativity constructs can be mapped onto the four quadrants and found to overlap more or less, depending on the context characteristics. Measurement methodologies adapted to the four different quadrants are discussed. The article concludes with a discussion about future research directions based on the proposed theoretical framework, in terms of theories and hypotheses on intelligence and creativity, of eminent personalities and personality traits, as well as its consequences for developmental, educational, and professional environments. Full article

(This article belongs to the Special Issue Intelligence and Creativity)

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24 pages, 1188 KiB

Open AccessEditor’s ChoiceArticle

Effect Sizes, Power, and Biases in Intelligence Research: A Meta-Meta-Analysis

by Michèle B. Nuijten, Marcel A. L. M. van Assen, Hilde E. M. Augusteijn, Elise A. V. Crompvoets and Jelte M. Wicherts

J. Intell. 2020, 8(4), 36; https://doi.org/10.3390/jintelligence8040036 - 2 Oct 2020

Cited by 23 | Viewed by 9415

Abstract

In this meta-study, we analyzed 2442 effect sizes from 131 meta-analyses in intelligence research, published from 1984 to 2014, to estimate the average effect size, median power, and evidence for bias. We found that the average effect size in intelligence research was a [...] Read more.

In this meta-study, we analyzed 2442 effect sizes from 131 meta-analyses in intelligence research, published from 1984 to 2014, to estimate the average effect size, median power, and evidence for bias. We found that the average effect size in intelligence research was a Pearson’s correlation of 0.26, and the median sample size was 60. Furthermore, across primary studies, we found a median power of 11.9% to detect a small effect, 54.5% to detect a medium effect, and 93.9% to detect a large effect. We documented differences in average effect size and median estimated power between different types of intelligence studies (correlational studies, studies of group differences, experiments, toxicology, and behavior genetics). On average, across all meta-analyses (but not in every meta-analysis), we found evidence for small-study effects, potentially indicating publication bias and overestimated effects. We found no differences in small-study effects between different study types. We also found no convincing evidence for the decline effect, US effect, or citation bias across meta-analyses. We concluded that intelligence research does show signs of low power and publication bias, but that these problems seem less severe than in many other scientific fields. Full article

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10 pages, 1158 KiB

Open AccessEditor’s ChoiceCommentary

How to Compare Psychometric Factor and Network Models

by Kees-Jan Kan, Hannelies de Jonge, Han L. J. van der Maas, Stephen Z. Levine and Sacha Epskamp

J. Intell. 2020, 8(4), 35; https://doi.org/10.3390/jintelligence8040035 - 2 Oct 2020

Cited by 59 | Viewed by 12083

Abstract

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to [...] Read more.

In memory of Dr. Dennis John McFarland, who passed away recently, our objective is to continue his efforts to compare psychometric networks and latent variable models statistically. We do so by providing a commentary on his latest work, which he encouraged us to write, shortly before his death. We first discuss the statistical procedure McFarland used, which involved structural equation modeling (SEM) in standard SEM software. Next, we evaluate the penta-factor model of intelligence. We conclude that (1) standard SEM software is not suitable for the comparison of psychometric networks with latent variable models, and (2) the penta-factor model of intelligence is only of limited value, as it is nonidentified. We conclude with a reanalysis of the Wechlser Adult Intelligence Scale data McFarland discussed and illustrate how network and latent variable models can be compared using the recently developed R package Psychonetrics. Of substantive theoretical interest, the results support a network interpretation of general intelligence. A novel empirical finding is that networks of intelligence replicate over standardization samples. Full article

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23 pages, 1499 KiB

Open AccessEditor’s ChoiceArticle

The Worst Performance Rule, or the Not-Best Performance Rule? Latent-Variable Analyses of Working Memory Capacity, Mind-Wandering Propensity, and Reaction Time

by Matthew S. Welhaf, Bridget A. Smeekens, Matt E. Meier, Paul J. Silvia, Thomas R. Kwapil and Michael J. Kane

J. Intell. 2020, 8(2), 25; https://doi.org/10.3390/jintelligence8020025 - 2 Jun 2020

Cited by 9 | Viewed by 5709

Abstract

The worst performance rule (WPR) is a robust empirical finding reflecting that people’s worst task performance shows numerically stronger correlations with cognitive ability than their average or best performance. However, recent meta-analytic work has proposed this be renamed the “not-best performance” rule because [...] Read more.

The worst performance rule (WPR) is a robust empirical finding reflecting that people’s worst task performance shows numerically stronger correlations with cognitive ability than their average or best performance. However, recent meta-analytic work has proposed this be renamed the “not-best performance” rule because mean and worst performance seem to predict cognitive ability to similar degrees, with both predicting ability better than best performance. We re-analyzed data from a previously published latent-variable study to test for worst vs. not-best performance across a variety of reaction time tasks in relation to two cognitive ability constructs: working memory capacity (WMC) and propensity for task-unrelated thought (TUT). Using two methods of assessing worst performance—ranked-binning and ex-Gaussian-modeling approaches—we found evidence for both the worst and not-best performance rules. WMC followed the not-best performance rule (correlating equivalently with mean and longest response times (RTs)) but TUT propensity followed the worst performance rule (correlating more strongly with longest RTs). Additionally, we created a mini-multiverse following different outlier exclusion rules to test the robustness of our findings; our findings remained stable across the different multiverse iterations. We provisionally conclude that the worst performance rule may only arise in relation to cognitive abilities closely linked to (failures of) sustained attention. Full article

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