scholarly journals Theory of Mind Measurements and Mechanisms: An Investigation of Construct Validity and Cognitive Processes in Theory of Mind Tasks

2021 ◽  
Author(s):  
◽  
Ester Navarro Garcia
Keyword(s):  
Individual Differences ◽  
Theory Of Mind ◽  
Construct Validity ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Metalinguistic Awareness ◽  
Latent Factors ◽  
Confirmatory Factor Analyses ◽  
Crystallized Intelligence ◽  
Important Challenge

Understanding the perspectives of others is a critical skill. Theory of mind (ToM) is an essential ability for social competence and communication, and it is necessary for understanding behaviors that differ from our own (Premack and Woodruff, 1978). Although all individuals possess a ToM to varying degrees, bilinguals are especially adept to perspective-taking. Research has reported that bilinguals outperform monolinguals in ToM tasks (e.g., Goetz, 2003; Rubio-Fernandez & Glucksberg, 2012). However, the mechanisms underlying this effect are unclear. Studying individual differences in ToM performance between bilinguals and monolinguals can help explain these mechanisms. Yet this promising area of research faces an important challenge: the lack of psychometric research on ToM measurement. Recent research suggests that tests that measure the ToM construct might not be as reliable as previously thought (Warnell & Redcay, 2019). This hinders the interpretation of experimental and correlational findings and puts into question the validity of the ToM construct. This dissertation addresses these two questions empirically to improve our understanding of what constitutes ToM. Study 1 examines the structure of ToM, crystallized intelligence (Gc), and fluid intelligence (Gf) to understand (a) whether ToM constitutes a construct separate from other cognitive abilities and (b) to explore whether tasks of ToM present adequate construct validity. For this, three confirmatory factor analyses (CFAs) were conducted. The results demonstrated that a model with three latent factors (ToM, Gf and Gc) did not adequately fit the data and was not significantly different from a model with only two latent factors (ToM-Gf and Gc). In addition, an exploratory factor analysis (EFA) showed that two of the ToM tasks loaded onto a Gf factor whereas one of the tasks loaded onto a third factor by itself. Finally, an exploratory network analysis (NMA) was conducted to observe relationships among the tasks. The results showed that the ToM tasks were no more related to each other than to some tasks of Gf and Gc, and that ToM tasks did not form a consistent cluster. Overall, the results of Study 1 suggest that ToM tasks are likely not measuring a monolithic ToM construct. Study 2 examines individual differences in metalinguistic awareness, executive function, and bilingualism as predictors of ToM. The results showed that all variables significantly predicted ToM, but bilingualism was not a significant moderator of ToM. Overall, the findings suggest that in this sample there was no difference in the processes used to predict ToM based on being bilingual or monolingual. Implications for measurement and individual differences in ToM are discussed.

scholarly journals Are We Measuring Theory of Mind Correctly? A Psychometric Study of Theory of Mind and Intelligence

2021 ◽  
Author(s):  
Ester Navarro
Keyword(s):  
Factor Analysis ◽  
Network Analysis ◽  
Theory Of Mind ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Factor Analyses ◽  
Latent Factors ◽  
Confirmatory Factor Analyses ◽  
Crystallized Intelligence ◽  
Confirmatory Factor

Theory of mind (ToM) is an essential ability for social competence and communication, and it is necessary for understanding behaviors that differ from our own (Premack and Woodruff, 1978). However, recent research suggests that tasks designed to measure the ToM construct might not be as reliable or valid as previously thought (Warnell & Redcay, 2019). This hinders the interpretation of experimental and correlational findings and puts into question the validity of the ToM construct. The study examines the structure of ToM, crystallized intelligence (Gc), and fluid intelligence (Gf) to understand (a) whether ToM constitutes a construct separate from other cognitive abilities and (b) to explore whether tasks of ToM present adequate construct validity. For this, three confirmatory factor analyses (CFAs) were conducted. The results demonstrated that a model with three latent factors (ToM, Gf and Gc) did not adequately fit the data and was not significantly different from a model with only two latent factors (ToM-Gf and Gc). In addition, an exploratory factor analysis (EFA) showed that two of the ToM tasks loaded onto a Gf factor whereas one of the tasks loaded onto a third factor by itself. Finally, an exploratory network analysis (NMA) was conducted to observe relationships among the tasks. The results showed that the ToM tasks were no more related to each other than to some tasks of Gf and Gc, and that ToM tasks did not form a consistent cluster. Overall, the results suggest that ToM tasks are likely not measuring a monolithic ToM construct.

scholarly journals Training Working Memory for Two Years – No Evidence of Latent Transfer to Intelligence

2021 ◽  
Author(s):  
Luc Watrin ◽  
Oliver Wilhelm ◽  
Gizem Hülür
Keyword(s):  
Working Memory ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Convincing Evidence ◽  
Memory Training ◽  
Control Group ◽  
Training Effects ◽  
Latent Factors ◽  
Crystallized Intelligence ◽  
9Th Grade

Working memory (WM) training has been proposed as a promising intervention to enhance cognitive abilities, but convincing evidence for transfer to untrained abilities is lacking. Prevalent limitations of WM training studies include the narrow assessment of both WM and cognitive abilities, the analysis of manifest variables subject to measurement error, and training dosages too low to likely cause changes in the cognitive system. To address these limitations, we conducted a two-year longitudinal study to investigate the effects of working memory training on latent factors of working memory capacity, fluid intelligence and crystallized intelligence. 112 students initially attending 9th grade practiced a heterogenous set of validated WM tasks on a bi-weekly basis. A control group of 113 students initially attending 9th grade participated in the pretest and posttest. Broad and prototypical measures of fluid and crystallized intelligence served as measures of nearer and farer transfer. We found substantial and reliable training effects on the practiced WM tasks, as well as on a latent WM factor constituted by them. However, no transfer of training effects to latent factors of fluid or crystallized intelligence were observed. These results question the utility and validity of WM training as means of improving cognitive abilities.

Investment Traits and Intelligence in Adulthood

2013 ◽  
Vol 34 (2) ◽  
pp. 82-89 ◽  
Author(s):  
Sophie von Stumm
Keyword(s):  
Individual Differences ◽  
Personality Traits ◽  
Fluid Intelligence ◽  
Need For Cognition ◽  
Openness To Experience ◽  
Intelligence Tests ◽  
Crystallized Intelligence ◽  
New Knowledge ◽  
The Relationship ◽  
Over Time

Intelligence-as-knowledge in adulthood is influenced by individual differences in intelligence-as-process (i.e., fluid intelligence) and in personality traits that determine when, where, and how people invest their intelligence over time. Here, the relationship between two investment traits (i.e., Openness to Experience and Need for Cognition), intelligence-as-process and intelligence-as-knowledge, as assessed by a battery of crystallized intelligence tests and a new knowledge measure, was examined. The results showed that (1) both investment traits were positively associated with intelligence-as-knowledge; (2) this effect was stronger for Openness to Experience than for Need for Cognition; and (3) associations between investment and intelligence-as-knowledge reduced when adjusting for intelligence-as-process but remained mostly significant.

scholarly journals Decision-Making Competence: More Than Intelligence?

2020 ◽  
Vol 29 (2) ◽  
pp. 186-192 ◽  
Author(s):  
Wändi Bruine de Bruin ◽  
Andrew M. Parker ◽  
Baruch Fischhoff
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Individual Differences ◽  
Fluid Intelligence ◽  
Psychological Research ◽  
Future Research ◽  
Experimental Conditions ◽  
Crystallized Intelligence ◽  
Age Related ◽  
Development And Validation

Decision-making competence refers to the ability to make better decisions, as defined by decision-making principles posited by models of rational choice. Historically, psychological research on decision-making has examined how well people follow these principles under carefully manipulated experimental conditions. When individual differences received attention, researchers often assumed that individuals with higher fluid intelligence would perform better. Here, we describe the development and validation of individual-differences measures of decision-making competence. Emerging findings suggest that decision-making competence may tap not only into fluid intelligence but also into motivation, emotion regulation, and experience (or crystallized intelligence). Although fluid intelligence tends to decline with age, older adults may be able to maintain decision-making competence by leveraging age-related improvements in these other skills. We discuss implications for interventions and future research.

Use of Fluid and Crystallized Intelligence Theory to Enhance Prediction of Learning Foreign Language Grammar

2015 ◽  
Vol 7 (6) ◽  
pp. 69
Author(s):  
Mohammad Davoudi ◽  
Narges Amel Sadeghi
Keyword(s):  
Foreign Language ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Language Teachers ◽  
Adult Intelligence Scale ◽  
Wechsler Adult Intelligence Scale ◽  
Crystallized Intelligence ◽  
Intelligence Theory ◽  
Wechsler Adult Intelligence ◽  
Raven's Advanced Progressive Matrices

<p>The aim of this study was to examine if there is any relationship between the two types of intelligences in Cattell'sGF- GC theory and learning foreign language grammar among Iranian learners. To this end, 85 university students took part in this study. First, the participants were asked to take the Raven's Advanced Progressive Matrices (APM), then the researcher asked them to take part in Wechsler Adult Intelligence Scale (WAIS) separately, and the interview for each participant was recorded. The researcher used the students' grammar scores which were obtained from their professors as the measure of their level of grammatical knowledge. The result of the study showed that there are significant correlations between the two types of intelligences (fluid and crystallized intelligences) and foreign language grammar. Moreover, the result from path analysis showed that between the two intelligences in the GF-GC theory, fluid intelligence is a better cognitive predicator of learning foreign language grammar. Bearing the finding of this study in mind, language teachers should provide an environment in which students can develop their cognitive abilities such as abstract reasoning and critical thinking.</p>

scholarly journals The Enriching Interplay between Openness and Interest: A Theoretical Elaboration of the OFCI Model and a First Empirical Test

2018 ◽  
Vol 6 (3) ◽  
pp. 35 ◽  
Author(s):  
Matthias Ziegler ◽  
Titus Schroeter ◽  
Oliver Lüdtke ◽  
Lena Roemer
Keyword(s):  
Longitudinal Data ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Empirical Test ◽  
Current Paper ◽  
Theoretical Development ◽  
Specific Interest ◽  
Crystallized Intelligence ◽  
Micro Level

The Openness-Fluid-Crystallized-Intelligence (OFCI) model posits long-term relations between Openness and cognitive abilities and has been successfully tested with longitudinal data. However, research on the developmental interplay between cognitive abilities and personality exists only sparsely. The current paper focuses on a theoretical development of the OFCI model which suggests micro-level mechanisms underlying the long-term development. Specifically, within-situation relations between Openness, interests, situational perception, cognitive abilities, and emotions are proposed to explain longitudinal relations between Openness and cognitive abilities. Using experience sampling, selected parts of this elaboration were empirically scrutinized in a first test of the proposed ideas. Openness and specific interest both varied substantially across situations and covaried systematically. In interaction with an indicator of fluid intelligence, this covariation was related to an indicator of crystallized intelligence. The paper contributes to theorizing the intertwined development of personality and cognitive abilities, and highlights the importance of within-situation research for explaining long-term development.

scholarly journals Differential and Experimental Approaches to Studying Intelligence in Humans and Non-Human Animals

2020 ◽  
Author(s):  
Alexander P. Burgoyne ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Randall W Engle
Keyword(s):  
Individual Differences ◽  
Cognitive Performance ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Relevant Information ◽  
Attention Control ◽  
Cognitive Tasks ◽  
General Factor ◽  
Albino Rat ◽  
General Ability

Why do some individuals learn more quickly than others, or perform better in complex cognitive tasks? In this article, we describe how differential and experimental research methods can be used to study intelligence in humans and non-human animals. More than one hundred years ago, Spearman (1904) discovered a general factor underpinning performance across cognitive domains in humans. Shortly thereafter, Thorndike (1935) discovered positive correlations between cognitive performance measures in the albino rat. Today, research continues to shed light on the underpinnings of the positive manifold observed among ability measures. In this review, we focus on the relationship between cognitive performance and attention control: the domain-general ability to maintain focus on task-relevant information while preventing attentional capture by task-irrelevant thoughts and events. Recent work from our lab has revealed that individual differences in attention control can largely explain the positive associations between broad cognitive abilities such as working memory capacity and fluid intelligence. In research on mice, attention control has been closely linked to a general ability factor reflecting route learning and problem solving. Taken together, both lines of research suggest that individual differences in attention control underpin performance in a variety of complex cognitive tasks, helping to explain why measures of cognitive ability correlate positively. Efforts to find confirmatory and disconfirmatory evidence across species stands to improve not only our understanding of attention control, but cognition in general.

scholarly journals Quest for I (Intelligence) in AI (Artificial Intelligence): A Non-Elusive Attempt

2021 ◽  
Author(s):  
Kumar S. Ray
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Philosophical Argument ◽  
Robust Learning ◽  
Crystallized Intelligence ◽  
Theory Of Intelligence ◽  
Alan Turing ◽  
Meta Learning ◽  
Evaluation Approaches

This chapter essentially makes a non-elusive attempt in quest of ‘I’ (Intelligence) in ‘AI’ (Artificial Intelligence). In the year 1950, Alan Turing proposed “the imitation game” which was a gaming problem to make a very fundamental question — “can a machine think?”. The said article of Turing did not provide any tool to measure intelligence but produced a philosophical argument on the issue of intelligence. In 1950, Claude Shannon published a landmark paper on computer chess and rang the bell of the computer era. Over the past decades, there have been huge attempts to define and measure intelligence across the fields of cognitive psychology and AI. We critically appreciate these definitions and evaluation approaches in quest of intelligence, which can mimic the cognitive abilities of human intelligence. We arrive at the Cattell-Horn-Carroll (C–H–C) concept, which is a three-stratum theory for intelligence. The C–H–C theory of intelligence can be crudely approximated by deep meta-learning approach to integrate the representation power of deep learning into meta-learning. Thus we can combine crystallized intelligence with fluid intelligence, as they complement each other for robust learning, reasoning, and problem-solving in a generalized setup which can be a benchmark for flexible AI and eventually general AI. In far-reaching future to search for human-like intelligence in general AI, we may explore neuromorphic computing which is essentially based on biological neurons.

scholarly journals Individual differences in working memory capacity, attention control, fluid intelligence, and pupillary measures of arousal

2021 ◽  
Author(s):  
Matthew Kyle Robison ◽  
Gene Arnold Brewer
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Memory Capacity ◽  
Attention Control ◽  
Future Research ◽  
Control Fluid ◽  
Thought Probes

The present study examined individual differences in three cognitive abilities: attention control (AC), working memory capacity (WMC), and fluid intelligence (gF) as they relate the tendency to experience task-unrelated thoughts (TUTs) and the regulation of arousal. Cognitive abilities were measured with a battery of nine laboratory tasks, TUTs were measured via thought probes inserted into two tasks, and arousal regulation was measured via pupillometry. Recent theorizing (Robison &amp; Unsworth, 2017a) suggests that one reason why some people experience relatively frequent TUTs and relatively poor cognitive performance - especially AC and WMC - is that they exhibit dysregulated arousal. Here, we examined how arousal regulation might predict both AC and WMC, but also higher-order cognitive abilities like gF. Further, we examine direct and indirect associations with these abilities via a mediating influence of TUT. Participants who reported more TUTs also tended to exhibit poorer AC, lower WMC, and lower gF. Arousal dysregulation correlated with more TUTs and lower AC. However there was no direct correlation between arousal regulation and WMC, nor between arousal regulation and gF. Rather, the associations between arousal regulation, WMC, and gF were indirect via TUT. We discuss the implications of the results in light of the arousal regulation theory of individual differences and directions for future research.

What Influences Successful Communication? An Examination of Cognitive Load and Individual Differences

2019 ◽  
Author(s):  
Ester Navarro ◽  
Brooke N Macnamara ◽  
Sam Glucksberg ◽  
Andrew R. A. Conway
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Cognitive Load ◽  
Cognitive Abilities ◽  
Fluid Intelligence ◽  
Working Memory Capacity ◽  
Cognitive Resources ◽  
Audience Design ◽  
Low Load ◽  
Communication Errors

The underlying cognitive mechanisms explaining why speakers sometimes make communication errors are not well understood. Some scholars have theorized that audience design engages automatic processes when a listener is present; others argue that it relies on effortful resources, regardless of listener presence. We hypothesized that (a) working memory is engaged during communicative audience design and (b) the extent to which working memory is engaged relies on individual differences in cognitive abilities and concurrent amount of resources available. In Experiment 1, participants completed a referential task under high, low, or no cognitive load with a present listener, whose perspective differed from the speaker’s. Speakers made few referential errors under no and low load, but errors increased when cognitive load was highest. In Experiment 2, the listener was absent. Speakers made few referential errors under no and low load, but errors increased when cognitive load was highest, suggesting that audience design is still effortful under high cognitive load, regardless of the presence of a listener. Experiment 3 tested whether cognitive abilities predicted communication performance. Participants with higher fluid intelligence and working memory capacity made fewer communication errors. Our findings suggest that communication relies on available cognitive resources, and therefore errors occur as a function of factors like cognitive load, and individual differences.

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