Are differences in peoples cognitive abilities related more to individual differences or to whether they are male or female?

Access through your institution

Volume 32, May 2014, Pages 69-79

https://doi.org/10.1016/j.lindif.2014.03.017Get rights and content

Over the past 100 years both psychologists and the general public have been fascinated with the idea of gender differences in cognitive abilities (Hyde & McKinley, 1997). The most popular belief is that males possess greater quantitative and visuospatial abilities than females while females possess greater verbal ability than males (Maccoby & Jacklin, 1974). Summaries of meta-analyses however, suggest that gender differences in cognitive abilities may be much more specific in adult populations than is popularly believed (Hyde and McKinley, 1997, Spelke, 2005; see Hyde, 2005 and Halpern et al., 2007 for a discussion of this point). In the domain of quantitative and visuospatial abilities, for example, although males tend to perform better than females on measures of mathematical problem solving, mental rotation, and spatial perception (e.g., Halpern, 2000, Halpern et al., 2007), few, if any, gender differences exist on measures of mathematical computation (i.e., arithmetic), mathematical concepts, and other measures of visuospatial abilities (Halpern et al., 2007, Hyde and McKinley, 1997, Linn and Petersen, 1985). Similarly, in the domain of verbal abilities, although females tend to perform better than males on measures of spelling (Kimura, 1999), word fluency (Halpern, 2000, Kimura, 1999), and language production (Halpern, 2000, Hyde and McKinley, 1997), few if any gender differences exist on measures of vocabulary (Halpern et al., 2007). Indeed, although there is a female advantage on measures of reading comprehension ability when the target population is children or adolescents (Logan and Johnston, 2010, Lynna and Mikk, 2009, Mullis et al., 2003, Mullis et al., 2007) few, if any, gender differences exist when the target population is adults (Hyde and Linn, 1988, Hyde and McKinley, 1997).

Nevertheless there are at least two reasons why there is a need to further examine gender differences in reading comprehension, especially when gender differences in the cognitive components of reading are being considered and the target population is adults. First from a practical perspective, determining whether there are gender differences in specific cognitive components such as those cognitive components tapped by measures of reading comprehension might provide insight as to why males achieve higher scores than females on standardized tests designed for admissions to colleges, universities, and graduate programs whereas females achieve higher grades (i.e., GPAs) than males in school (Halpern et al., 2007, Mau and Lynn, 2001; also see Halpern, 2004). Second, from a theoretical perspective, researchers argue that gender differences should be understood in terms of cognitive processes rather than the classification or type of task (e.g., verbal, quantitative, visuospatial) (see Halpern, 2004 for a discussion of the cognitive-processes approach for examining gender differences in cognitive abilities).

Therefore, one goal of the present study was to determine whether gender differences exist in the specific cognitive components that are typically tapped by measures of adult reading comprehension. For example, are there gender differences in the specific cognitive components that are used to learn explicit and implicit text-based information (i.e., text memory, text inferencing)?; are there gender differences in the specific cognitive components that connect text-based information with information from prior knowledge (i.e., knowledge integration)?; or are there gender differences in the specific cognitive components that decode and identify words (i.e., lower-level word decoding)? The specific cognitive components examined in the present study were higher-level processes, which are used for learning and integrating text (e.g., text memory, text inferencing, knowledge integration, and knowledge access), lower-level processes, which are used for decoding words, and epistemic belief of learning, which is knowledge about learning. This taxonomy of high-low cognitive processes has been adopted in order to delineate the differences between processes that are used to remember, retrieve, and connect ideas of a text (i.e., higher-level processes) and processes that are used to decode words (i.e., lower-level processes). These cognitive components were selected because of their importance for constructing an integrated and coherent representation of a text (e.g., Daneman and Hannon, 2001, Kintsch, 1988, Kintsch, 1998). Additionally, research suggests that measures of higher- and lower-level cognitive processes account for as much as 55% of the variance in reading comprehension performance in an adult population (Hannon, 2012a, Hannon and Daneman, 2001a, Hannon and Daneman, 2006, Hannon and Daneman, 2009).

A second goal of the present study was to determine whether gender differences exist in the powers of the specific cognitive components to predict measures of adult reading comprehension ability. That is, does text memory predict reading comprehension performance to the same extent for males and females?; does text inferencing predict reading comprehension performance to the same extent for males and females?; does knowledge integration predict reading comprehension performance to the same extent for males and females?; and do lower-level word decoding processes predict reading comprehension performance to the same extent for males and females? Below I briefly review developmental research examining gender differences in reading comprehension performance and its cognitive components. Next I relate this developmental literature to the adult literature that has examined gender differences in verbal abilities. In the final section, I describe the present study.

National and international assessments consistently observe a gender difference in reading comprehension ability in children (Department for Children, Schools and Families (DCSF), 2008a, Department for Children, Schools and Families (DCSF), 2008b, Department for Children, Schools and Families (DCSF), 2008c; Mullis et al., 2003, Mullis et al., 2007). Indeed, international studies examining reading comprehension in 10-year old children have observed a gender difference favoring girls in 35 of 40 participating countries (Mullis et al., 2003, Mullis et al., 2007). This gender difference exists regardless of the type of writing system, alphabetic or ideographic orthography (Ming Chui and McBride-Chang, 2006, Mullis et al., 2003, Mullis et al., 2007), and it extends well into adolescence (e.g., Ming Chui & McBride-Chang, 2006). Given the importance of reading skill in academics and employment, this “gender gap” potentially has a profound impact on males (Clinton et al., 2012, Riordan, 1999, Wood, 2003).

Reading comprehension, however, is a complex construct that is composed of a number of cognitive component processes (Cain et al., 2004, Graesser et al., 1994, Hannon, 2012a, Hannon and Daneman, 2001a, Hannon and Daneman, 2006, Hannon and Daneman, 2009, Hannon and Frias, 2012, McNamara and Magliano, 2009).1 Indeed, research suggests that reading comprehension is composed of: (i) lower-level processes that identify and decode words (Cunningham, Stanovich, & Wilson, 1990), (ii) higher-level processes that extract explicit information from text (Hannon, 2012a), connect text-based ideas (i.e., text-based inferences: Hannon & Daneman, 2001a), establish text coherence by connecting or bridging text-based ideas with prior knowledge (Singer & Ritchot, 1996), and embellish the text using prior knowledge (e.g., thematic and predictive inferences: Hannon and Daneman, 1998, Long et al., 1994), as well as (iii) knowledge about learning (i.e., epistemic belief of learning: Daneman & Hannon, 2001). Consequently, any one or a combination of these components might be a major source of the gender difference in reading comprehension ability.

Because of this complexity, a few developmental researchers have begun to examine gender differences in the specific cognitive that are typically tapped by measures of global reading comprehension ability. One surprising finding is that, for children, gender differences in the specific cognitive components are limited to only a small subset of components rather than all of the cognitive components that are part and parcel of reading comprehension. For example, using a think aloud protocol Clinton et al. (2012) examined gender differences in the frequency that grade 4 children generated four cognitive components of reading comprehension, namely re-instatement inferences (i.e., re-instatement of a previous fact to explain a current fact), connective inferences (i.e., inferences that connect concurrent sentences), knowledge-based inferences (i.e., inferences requiring explanations/predictions based on prior knowledge), and text-based memory statements (i.e., paraphrases or repetition of the text). Although Clinton et al. observed that females generated more re-instatement inferences than their male counterparts, they also observed no gender differences in the generation of connective inferences, knowledge-based inferences, or text-based memory statements.

In a subsequent study, Seipel, Clinton, and Carlson (2012) extended the findings of Clinton et al. (2012) by examining whether a gender difference existed in connective inferences that were either semantically- or episodically-based. Although Seipel et al. observed that females generated more episodic connective inferences than their male counterparts, there was no gender difference in semantic connective inferences. Therefore, the combined results of Clinton et al.'s and Seipel et al.'s studies suggest that, for grade 4 children, gender differences in the specific cognitive components of reading comprehension are limited to re-instatement inferences and episodically-based connective inferences.

With respect to adults, to date no study has examined gender differences in the specific cognitive components that are tapped by measures of reading comprehension ability. Thus, from this viewpoint, it is unclear whether gender differences in the specific cognitive components of reading comprehension do or do not exist. Moreover, in the broader context of verbal abilities, the evidence for gender differences is equivocal. On the one hand research suggests that gender differences in an adult population are minimal to non-existent on measures of reading comprehension and vocabulary (e.g., Halpern et al., 2007, Hyde, 2005, Hyde and McKinley, 1997). For the present study, this lack of a relationship between gender and vocabulary is particularly relevant because vocabulary knowledge is highly predictive of adult reading comprehension ability (e.g., Daneman, 1991, Sternberg and Powell, 1983). And because the shared variance between vocabulary knowledge and reading comprehension ability is largely a consequence of specific cognitive components that are common to both constructs (e.g., Hannon and Daneman, 2001a, Hannon and Daneman, 2006, Sternberg and Powell, 1983), it is possible that the present study will reveal no gender differences in the specific component processes that are tapped by measures of adult reading comprehension ability.

However other research suggests that there are gender differences in some of the important measures of verbal abilities. For instance, females perform better than males on measures of spelling (e.g., Kimura, 1999), word fluency (e.g., Halpern, 2000, Kimura, 1999), language production (e.g., Halpern, 2000, Hyde and McKinley, 1997), perceptual speed (e.g., Halpern, 2000), and episodic memory (e.g., Guillem and Mograss, 2005, Halpern, 2000). On the other hand, males perform better than females on measures of verbal analogies (e.g., Lim, 1994), deductive reasoning, and analytic reasoning (e.g., Colom, Contreras, Arend, Leal, & Santacreu, 2004). These latter findings are particularly relevant to the present study because other research suggests that measures of the higher-level cognitive components of text inferencing and knowledge integration are predictive of performance on measures of verbal analogies, deductive reasoning, and analytic reasoning (e.g., Hannon & Daneman, 2001a). Thus, it is possible that the present study will reveal male advantages on the higher-level cognitive components of text inferencing and knowledge integration.

In summary, a few developmental studies have revealed gender differences in re-instatement inferences, a type of inference that is tapped by measures of children's reading comprehension ability, and episodic connective inferences, inferences that connect concurrent sentences in a text. However to date, no study has examined gender differences in the specific cognitive components that are tapped by measures of adult reading comprehension ability. Nevertheless, given that there is some evidence of both female and male advantages on some measures of verbal abilities, it is quite possible that there are also gender differences on some of the specific cognitive components tapped by measures of adult reading comprehension ability. Therefore one goal of the present study was to determine whether gender differences exist in some of the specific cognitive components that are typically tapped by measures of reading comprehension in adults. A second, novel goal was to examine whether gender differences exist in the powers of the specific cognitive components to predict performance on measures of adult reading comprehension ability.

In order to achieve these goals, participants completed a number of measures. To assess higher-level processes, participants completed Hannon and Daneman's cognitive component task (e.g., Hannon, 2012a, Hannon, 2012b, Hannon and Daneman, 2001a, Hannon and Daneman, 2006, Hannon and Daneman, 2009). The cognitive component task provides estimates of a reader's ability to access prior knowledge from long-term memory and to integrate this prior knowledge with new text-based information, to learn new text-based information, and to make text-based inferences. The cognitive component task was selected over other measures because its multi-component nature saves time by eliminating the need to administer multiple measures (Hannon & NcNaughton-Cassill, 2011), it has a high degree of reliability (Hannon, 2012a), and it is highly predictive of reading comprehension ability (Hannon, 2012a, Hannon and Daneman, 2001a, Hannon and Daneman, 2006, Hannon and Daneman, 2009, Hannon and NcNaughton-Cassill, 2011).

Participants also completed five measures of lower-level word processes. These measures included Bell and Perfetti's (1994) word and pseudoword decoding task as well as their phonological and orthographic lexical decision tasks. In addition, participants completed a measure of epistemic belief of learning, which has been shown to be predictive of reading comprehension ability (Daneman & Hannon, 2001). Finally, participants completed two measures of quantitative abilities, namely math word problems and arithmetic, and two measures of visuospatial abilities, namely spatial rotation and spatial construction. These measures were administered for two reasons. First, because previous research shows a male advantage on measures of math word problems and spatial rotation (Halpern, 2000, Halpern et al., 2007) but no gender differences on measures of arithmetic and spatial construction (Halpern, 2000, Hyde and McKinley, 1997), these four measures provide evidence of the normality/typicality of the present study's participants. Second, because the measurers of arithmetic and spatial construction should reveal no gender differences, these two measures should serve as evidence of discriminant validity if gender differences in the cognitive components of reading comprehension should be observed.

One hundred and forty Introductory to Psychology students participated in this study for course credit. All students were pre-screened to ensure that they were free of any known learning disability and that they were monolingual, native English speakers who spoke few words in another language. Monolingual English speakers were used because many of the measures used in the present study were designed for only English speakers. Seventy participants were male and 70 participants were female. The

The Results section includes five subsections. Section 3.1 reports the results of the data screening while Section 3.2 reports the validation of the sample of participants as well as a factor analysis of the two measures of reading comprehension ability. Section 3.3 reports the descriptive statistics as well as replications of previous findings that predict specific relationships among the predictors. Section 3.4 reports the analysis examining gender differences in global verbal abilities and

In the domain of verbal abilities, studies suggest a female advantage on measures of spelling, word fluency, and language production (Halpern, 2000) and a male advantage on measures of verbal reasoning (e.g., Colom et al., 2004). Few if any gender differences, however, exist on measures of vocabulary and adult reading comprehension ability (Halpern et al., 2007). Furthermore, little is known about gender differences in the specific cognitive components that predict adult reading comprehension

D.S. McNamara et al.
T.K. Lim
B. Hannon et al.
B. Hannon
F. Guillem et al.
A. Baddeley et al.
L.C. Bell et al.
J.I. Brown et al.
K. Cain et al.
V. Clinton et al.

J. Cohen

R. Colom et al.

A.E. Cunningham et al.

M. Daneman

M. Daneman et al.

Department for Children, Schools and Families (DCSF)

A. Gallagher et al.

A.C. Graesser et al.

R. Griffin et al.

D.F. Halpern

D.F. Halpern et al.

B. Hannon

B. Hannon et al.

Children with ADHD exhibit narrative comprehension difficulties relative to typically developing peers. One unexplored comprehension area for this population is the generation of explanatory predictive inferences. Plausible explanatory predictive inferences allow for smooth integration of new information, and are targeted in many comprehension interventions. The current study examined three questions: (1) Is there a difference between children with ADHD and typically developing children in the creation of explanatory predictive inferences during a predictive prompt task? (2) Does the group difference in the generation of these inferences mediate group differences in recall measures? (3) Does the act of making predictions during story presentation improve recall relative to a control condition? Seven- to 11-year-old children with and without ADHD listened to two audio-taped stories, and made predictions at several pauses during one of the stories (predictive prompt task). The recording of the other story was paused without asking for predictions in the control task. Children recalled the story following the task. During the predictive prompt task, children with ADHD generated fewer plausible explanatory predictive inferences than typically developing peers and this group difference mediated a group difference in the recall of highly important events. Further, children in both diagnostic groups included more plausible explanatory backwards inferences during recall following the predictive prompt task than following the control task. Given the importance of explanatory inferences in constructing coherent story representations, these findings are encouraging for educators using predictive tasks but indicate that children with ADHD may need further instruction on generating appropriate predictive inferences.
This study aimed to investigate undergraduates' cardiac activity during an episode of complex learning from text. Specifically, we examined (a) heart rate (HR) and (b) heart rate variability (HRV) as psychophysiological measures while students read a science text and were tested on it. Reading goals were also taken into account: Students were asked to read for themselves to know more on a topic, or to read to perform well to gain course credit. Undergraduates (N = 50) were randomly assigned to one of the two reading goal conditions. Their HR and HRV were registered at baseline, while reading the text, during the testing phase, and while recovering from the task. Findings confirmed that in the condition with the reading goal focused on good performance, the students comprehended the text better than the students who read for themselves. Two mixed-effects models examined HR and HRV trends during the four phases of the learning episode. Findings showed a general trend in which students’ HRV was greater in the reading phase compared to baseline. HR decreased during reading and increased during the testing phase. This pattern indicates a deep cognitive effort of students while reading that gave way to higher psychophysiological arousal in the testing phase. Moreover, a series of linear regression models revealed that being under aroused and in a state of receptive calm during the reading phase allowed greater performance. Educational implications are drawn.
This study compared two views that differ about the composition of the SAT: one view that proposes both general intelligence and non-general intelligence factors predict SAT, SAT-V, and SAT-M performance and a second view that proposes that just a general intelligence factor or “g” predicts SAT, SAT-V, and SAT-M performance. The results suggested that structural equation models (i.e., SEMs) that included multiple factors (i.e., general intelligence, metacognitive awareness, and performance avoidance-test anxiety) as predictors were significantly better at explaining the SAT and SAT-M data than were SEMs that included: (i) just a general intelligence factor as a predictor or (ii) just metacognitive + social-personality factors as predictors (i.e., metacognitive awareness, performance avoidance-test anxiety). Moreover, this multiple factor SEM was also suitable for explaining the SAT-V data. However for the SAT-V, the results also suggested that a SEM that included just a general intelligence factor as a predictor was better at explaining the SAT-V data than was a SEM that included multiple factors as predictors (i.e., general intelligence, metacognitive awareness, and performance avoidance-test anxiety) or a SEM that included just metacognitive and social-personality factors as predictors (i.e., metacognitive awareness, performance avoidance-test anxiety).
In the present study we focus on the component processes of reading comprehension in adolescents. To accomplish this we applied the component processes task (CPT, Hannon & Daneman, 2001) in two connected studies to assess higher-level reading comprehension processes and the cognitive-components-resource (CC-R, Hannon, 2012) model to structure the pattern of relationships between word-level and higher-level processes, working memory, and reading comprehension. Our results indicate that the component processes of reading comprehension can be differentiated in German speaking adolescents and that approaches such as the CC-R are suitable for modeling individual differences in their comprehension processes. The pattern of relationships between processes and cognitive resources was found to be comparable between girls and boys as well as L1 and L2 German speakers, although mean differences were found in both comparisons.
Recent research suggests that relational integration is a strong predictor of measures of complex cognitive abilities (e.g., Oberauer, Süβ, Wilhem, & Whittmann, 2008). In this paper we argue that there are at least two types of relational integration and that forming new relational structures by integrating relevant prior knowledge with new information is the fundamental relational integration process that underlies skill at performing many complex cognitive tasks. We describe a simple way to measure individual differences in this knowledge integration process and we show that our knowledge integration measure accounts for an impressive proportion of the variance on a battery of cognitive tests that assessed general fluid intelligence and specific abilities (verbal, quantitative, spatial). Knowledge integration also had better predictive power than two popular measures of the combined storage and processing capacity of working memory (reading span and operation span), as well as another relational integration measure that did not require accessing and integrating prior knowledge.

View all citing articles on Scopus

This study explores the (a) text-learning strategies and (b) schematizing skills of pre-adolescents with varying achievement levels by means of the analysis of think-aloud protocols, traces, and pen movements. Twenty fifth- and sixth-grade students from two elementary schools participated. Results show the use and combination of various text-learning strategies during learning from text, mostly applied at a surface level. Notwithstanding the large variation in students' individual strategy repertoires, four main text-learning approaches could be distinguished. No achievement level differences in text-learning strategy use were found. As to students' schematizing skills, analyses illustrate the great difficulty students experience with spatially and hierarchically representing text information. Students paid limited attention in the construction process to assisting metacognitive processes. Surprisingly, low achievers spent significantly more time on these metacognitive processes. This multi-method assessment of text-learning strategies in general and schematizing skills in particular provide fruitful avenues for future intervention research.
Over 300 adults completed a questionnaire that asked them to estimate their “overall” intelligence, as well as their scores on the 10 broad abilities specified by the Cattell–Horn–Carroll (CHC) theory of cognitive abilities. They also completed a short measure of the Big Five, as well as six questions on their beliefs about intelligence and intelligence testing. There were, as predicted, sex differences on the self-estimate of overall intelligence as well as seven of the ten CHC abilities. The abilities factored into two dimensions. A regression showed that respondents think only five of the ten abilities are related to overall IQ (g). There were replicated sex differences in beliefs about intelligence testing. Implications and limitations of these results are considered.
Learning processes are often associated with intelligence and induction but rarely empirically examined in relation to fluid intelligence (Gf) tasks. This study examined whether learning of Raven’s Distribution of Two (D2) rule occurs, and whether this learning contributes to individual differences. Learning sets with different numbers of D2 rule items were presented to 284 participants in three exposure conditions and then tested for transfer. Results suggest learning about a specific rule is not necessary for induction to take place. However, evidence that rule learning contributes to individual differences in Raven’s performance was observed, with those higher in Gf benefitting most from more exposure. This Gf advantage was only evident when actualized learning opportunity (successful solution) was taken into account, as opposed to potential learning opportunity (mere exposure). Mere item exposure appears insufficient for rule learning unless the individual solves items correctly and thus receives actualized learning opportunity.
Our aim is to examine whether mentored students' Perceived Competence in Learning (PCL) moderates school performance outcomes in school-based mentoring (SBM) programs delivered by teachers. A three-stage longitudinal study was conducted in order to compare mentored (n = 157) and non-mentored students (n = 160) enrolled in formal basic education (5th to 8th grades). Multivariate Analyses of Covariance (MANCOVA) revealed that mentoring was moderately effective in improving mentees' Portuguese grades and Grade Point Average (GPA) and reducing the number of unexcused absences compared to equivalent non-mentored students. The study also demonstrated that the mentees' PCL had a significant moderating effect on improvement in their Math grades. The different patterns of change in PCL during SBM also contributed to a variation in school performance outcomes. These results suggest that SBM delivered by experienced educators may enhance PCL as well as school performance in formal learning contexts.
Research concerning different standards in performance goals – the achievement goal of demonstrating ability – has found little difference in cognition and behavior between normative (social-comparative) oriented and outcome-oriented standards. The present study tested differences in affect between performance goals with these different standards. Ninety-nine participants were randomly assigned into five goal conditions: (a) mastery; (b) normative-performance-approach; (c) outcome-approach; (d) normative-performance-avoidance; and, (e) outcome-avoidance. Multi-level analyses of physiological, observed, and self-report measures of affect indicated that pursuing the demonstration of ability along a social-comparative normative standard involved more intense and negative affect than did such pursuit along a non-social-comparative standard. This was found both in goals of approach and of avoidance valence.
The purpose of this study was to examine if students' Big Five personality traits (i.e., neuroticism, extraversion, openness, agreeableness, conscientiousness) and their motives for communicating with an instructor (i.e., relational, functional, participatory, excuse-making, sycophancy) were significant predictors of instructional dissent (i.e., expressive, rhetorical, vengeful) in the college classroom. Student participants (N = 240) completed a questionnaire using self-reports of their own personality traits, motives, and frequency of communicating instructional dissent in reference to a target course. Results of hierarchical regression analyses revealed that (a) expressive dissent was predicted by students' neuroticism, extraversion, and agreeableness, (b) rhetorical dissent was predicted by students' extraversion and agreeableness, and (c) vengeful dissent was predicted by students' openness, agreeableness, and conscientiousness. After controlling for the Big 5 traits, (d) the excuse-making, sycophancy, and functional motives predicted additional variance in instructional dissent.