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A General Theoretical Integrative Model of Individual Differences in Interests, Abilities, Personality Traits, and Academic and Occupational Achievement: A Commentary on Four Recent Articles
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This commentary integrates the contents of four recent articles on individual differences (Nye, Su, Rounds, & Drasgow, 2012; Schmidt, 2011; Valla & Ceci, 2011; von Stumm, Hell, & Chamorro-Premuzic, 2011) in a causal theoretical model. In this model, introversion and fluid intelligence cause interest in general learning (intellectual curiosity), which in turn is a major cause of crystallized intelligence. Certain specific interests and fluid intelligence also contribute to crystallized intelligence. Prenatal testosterone hormone conditioning is postulated to cause sex differences in certain specific interests but not in others. Crystallized intelligence, specific interests, and the personality trait of conscientiousness cause adult academic and occupational performance, whereas crystallized intelligence is the main cause of good mental functioning at older ages. Research is presented supporting each link in the model.
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... work satisfaction (see, e.g., Morgan et al., 2001;Nye et al., 2012;Rounds & Su, 2014;. Therefore, understanding gender differences in interests may explain gender differences in occupational entry, especially with respect to science, technology, engineering, and mathematics (STEM) fields (see e.g., Ceci et al., 2014;Halpern, 2014;Lubinski et al., 2014;Schmidt, 2014;Tellhed et al., 2017). ...
... There has been a longstanding history of investigations into factors related to gender differences and similarities (Eagly & Wood, 2013). Differences between men and women can be triggered or modified by socio-environmental conditions such as culture (Eagly & Wood, 2013;Schmidt, 2014). For example, gender role expectations may affect the ways boys and girls are treated (e.g., boys being provided trucks to play with and girls being provided with dolls to play with, boys being encouraged while girls being discouraged to engage in certain activities). ...
... Consistent with prior research (see e.g., Lippa, 1998;Su et al., 2009;Su & Rounds, 2015;Tracey & Caulum, 2015), women showed a stronger preference of working with people rather than things whereas men preferred working with things rather than people. This finding provides support for widespread if not universal crosscultural mechanisms contributing to gender differences, as conceptualized by social role and role congruity theories (Eagly & Karau, 2002;Eagly & Wood, 2013;Schmidt, 2014), such that men and women show stronger interests in gender-stereotypical dimensions due to socialization of gender-specific roles and expectations. Similar to previous findings for the gender difference in interest in people/things as one of the strongest differences observed between men and women (Lippa, 1998;Lubinski, 2000;Su et al., 2009), our results based on 42 nations indicate that it might be one of the most culturally universal as well. ...
Are men and women more similar or different in their interests in careers? This question has propelled decades of research into the association between gender and vocational interests. However, our understanding of this question in an international context remains limited. In this study, we examined gender differences in vocational interests across national and cultural contexts by exploring whether national cultural dimensions would be associated with gender differences in the structure and mean levels of vocational interests in people/things, ideas/data, and prestige. Our findings support similarity in the structure of vocational interests for men and women across 42 countries based on two major models on interests. General trends of gender differences in interests emerge such that in comparison to men, women tend to report a large preference for working with people (versus things; d = 1.04), and smaller preferences for working with ideas (versus data; d = 0.29) and with prestige (d = 0.18). National cultural dimensions appear to moderate gender differences in interests beyond the influences of national gender inequality. Specifically, gender differences in interests in people (versus things) tend to be larger in countries of higher uncertainty avoidance and higher indulgence whereas gender differences in ideas (versus data) tend to be larger in countries of higher indulgence, uncertainty avoidance, and lower power distance. This study highlights how a better conceptualization of the influences of culture can inform vocational psychologists, gender studies researchers, and career counselors’ work with men and women in understanding their vocational interests.
... We also contribute new findings about how gender and socioeconomic status relate to interest-ability profiles. Our study's second major aim is to evaluate the central tenet of intellectual development theories: that individuals are most knowledgeable in areas in which they are most interested and have the greatest ability (Ackerman 1996;Holland 1973;Schmidt 2014). We test this assumption by examining how different interest-ability profiles relate to knowledge scores in 14 areas. ...
... Some attempts have been made to examine interests and abilities jointly. Integrative models of individual differences, such as PPIK (Ackerman 1996) and Schmidt's (2014) theoretical model, have established frameworks for how these traits relate to one another developmentally, leading to the acquisition of knowledge and skills. Other studies have analyzed interests and abilities in relation to outcomes such as school subject preferences (Lavrijsen et al. 2021), college major (Achter et al. 1999), occupational choice (Austin and Hanisch 1990), and professional eminence (Bernstein et al. 2019). ...
Cognitive abilities and interests both play an important role in guiding knowledge acquisition, but most previous studies have examined them separately. The current study used a large and representative dataset to integrate interests and abilities using a person-centered approach that examines how distinct profiles of interests and abilities relate to individual strengths and weaknesses in knowledge. Two key findings emerged. First, eight interest–ability profiles were generated from Latent Profile Analysis (LPA), which replicated and extended the interrelations of interests and abilities found in previous studies using variable-centered approaches. Second, each profile’s strongest knowledge scores corresponded to their strongest abilities and interests, highlighting the importance of interest–ability profiles for guiding the development of knowledge. Importantly, in some domains, the lower ability profiles were actually more knowledgeable than higher ability profiles. Overall, these findings suggest that people learn best when given opportunities to acquire knowledge relevant to both their interests and abilities. We discuss how interest–ability profiles inform integrative theories of psychological development and present implications for education and career development.
... Scientific research has shown that cognitive and non-cognitive psychological dimensions do interact. Indeed, there is a long tradition of theoretical models considering their mutual relationships (Ackerman 1996;Royce and Powell 1983;Schmidt 2014). However, in the special issue published in the Journal of Intelligence addressing, once again, the cognitive ability-personality integration, Colom et al. (2019) wrote "we are afraid that researchers will come back to their usual practice of focusing on a limited set of psychological constructs analyzed in isolation". ...
Cognitive and non-cognitive traits are frequently analyzed in isolation. However, there is an increasing acknowledgment that their interplay should be considered for enhancing our understanding of human psychological differences. Testing both traits in the same sample of individuals is desirable when addressing their relationships. Here, for that purpose, 299 university students from Spain (mean age = 18.5 years., 83% female) completed a cognitive ability battery comprised by nine tests, the NEO-FFI for assessing the big five personality traits, and the SCL-90-R for evaluating a range of subjective psychopathological symptoms. This resulted in 23 cognitive and non-cognitive variables that were submitted to a data reduction providing four factors: (1) neuroticism/p, (2) cognitive ability/g, (3) agreeableness/A, and (4) introversion/I. Summary factor scores revealed a positive correlation between p and I (0.47), along with negative correlations of A with p (−0.26) and with g (−0.24), and a negative correlation between A and I (−0.16). These factors were related to some degree even when the assessment of the cognitive and non-cognitive variables cannot be considered straightforwardly comparable because the former was performance based, whereas the later was based on self-reports. Conceptual and methodological implications are discussed regarding the three-way relationship among cognitive ability, personality, and subjective psychopathological symptoms.
... Intelligence research conducted for well over 100 years has produced a substantial body of evidence for the predictive utility of intelligence tests, be it in terms of predicting success in education (Brown et al. 2021;Richardson et al. 2012;Roth et al. 2015), in vocations (Ree et al. 1994;Schmidt and Hunter 2004;Viswesvaran et al. 2005), in health outcomes (Deary et al. 2021;Der et al. 2009;Gottfredson and Deary 2004), or success in life in general (Deary et al. 2005;Gottfredson 1997;Schmidt 2014). This broad spectrum of evidence represents a core element in the narrative of the success story of intelligence testing. ...
A successful adjustment to dynamic changes in one’s environment requires contingent adaptive behaviour. Such behaviour is underpinned by cognitive flexibility, which conceptually is part of fluid intelligence. We argue, however, that conventional approaches to measuring fluid intelligence are insufficient in capturing cognitive flexibility. We address the discrepancy between conceptualisation and operationalisation by introducing two newly developed tasks that aim at capturing within-person processes of dealing with novelty. In an exploratory proof-of-concept study, the two flexibility tasks were administered to 307 university students, together with a battery of conventional measures of fluid intelligence. Participants also provided information about their Grade Point Averages obtained in high school and in their first year at university. We tested (1) whether an experimental manipulation of a requirement for cognitive inhibition resulted in systematic differences in difficulty, (2) whether these complexity differences reflect psychometrically differentiable effects, and (3) whether these newly developed flexibility tasks show incremental value in predicting success in the transition from high school to university over conventional operationalisations of fluid intelligence. Our findings support the notion that cognitive flexibility, when conceptualised and operationalised as individual differences in within-person processes of dealing with novelty, more appropriately reflects the dynamics of individuals’ behaviour when attempting to cope with changing demands.
... When examining differences in abilities and knowledge between males and females, it is essential to exercise caution. While there may be slight average variations in certain cognitive domains, individual differences within each gender often outweigh the average differences between genders (Schmidt, 2014). Societal and cultural factors play a significant role in shaping these variations, and it is important to acknowledge and respect diverse gender identities beyond the binary understanding (Mukti, Yuliskurniawati, Noviyanti, Mahanal, & Zubaidah, 2019). ...
The misconception related to astronomy is fretfully rising in society. This study aims to investigate, (i) level of misconception towards astronomy among university students, (ii) significant difference in students’ interest towards astronomy between male and female, (iii) significant difference between science and non-science students’ level of knowledge in astronomy, (iv) significant relationship between students’ faculties and misconception in astronomy, and (v) significant relationship between the educational background of the respondents' parents and their misconceptions towards astronomy. A qualitative approach was implemented using a set of questionnaires for data collection. The respondents were undergraduate students of with different courses and backgrounds from four different faculties: Faculty of Education, Faculty of Pharmacy, Faculty of Art and Design, and Faculty of Business Management. The data were analyzed using Statistical Package for the Social Science (SPSS). Findings showed that there is a significant difference in students’ interest towards astronomy between male and female students, there is a significant different between level of knowledge in astronomy and students’ major course, there is significant difference between students’ faculties and misconception in astronomy, and there is no significant relationship between the educational background of the respondents’ parents and their misconception in astronomy. This study benefits society by clarifying phenomena, distinguishing myth from reality. It aids Science teachers in addressing astronomy misconceptions and helps educators curb their spread.
... Kanfer et al., 2010;Keller, 2012;Sackett & Walmsley, 2014), vocational interests (e.g. Nye et al., 2012Nye et al., , 2017Schmidt, 2014;Van Iddekinge, Roth, et al., 2011), and specific knowledge and skills that are important for specific jobs or settings (e.g. Mumford et al., 2008;Neubert et al., 2015). ...
Based on the theory of person-environment fit, non-cognitive predictors of job performance were studied in a group of information and communication technology (ICT) specialists. From various potential job and training performance predictors seven psychological attrib-utes (personality, vocational interests, grit, growth mindset, self-efficacy, goal orientation and resistance to change) were chosen and tested as predictors of job performance ratings, as provided by either the supervisor or the study participant. The results indicate that grit, vocational interests, and resistance to change predict job performance in this group of ICT specialists. This study adds to the scientific literature of grit and vocational interests as non-cognitive predictors of job performance. Implications for practice include the recom-mendation of using grit and vocational interests in personnel management processes such as personnel selection or placement
We examined whether a machine-learning-based automated scoring system can mimic the human similarity task performance. We trained a bidirectional encoder representations from transformer-model based on the semantic similarity test (SST), which presented participants with a word pair and asked them to write about how the two concepts were similar. In Experiment 1, based on the fivefold cross validation, we showed the model trained on the combination of the responses (N = 1600) and classification criteria (which is the rubric of the SST; N = 616) scored the correct labels with 83% accuracy. In Experiment 2, using the test data obtained from different participants in different timing from Experiment 1, we showed the models trained on the responses alone and the combination of responses and classification criteria scored the correct labels in 80% accuracy. In addition, human–model scoring showed inter-rater reliability of 0.63, which was almost the same as that of human–human scoring (0.67 to 0.72). These results suggest that the machine learning model can reach human-level performance in scoring the Japanese version of the SST.
In this revised and updated edition of Hunt's classic textbook, Human Intelligence, two research experts explain how key scientific studies have revealed exciting information about what intelligence is, where it comes from, why there are individual differences, and what the prospects are for enhancing it. The topics are chosen based on the weight of evidence, allowing readers to evaluate what ideas and theories the data support. Topics include IQ testing, mental processes, brain imaging, genetics, population differences, sex, aging, and likely prospects for enhancing intelligence based on current scientific evidence. Readers will confront ethical issues raised by research data and learn how scientists pursue answers to basic and socially relevant questions about why intelligence is important in everyday life. Many of the answers will be surprising and stimulate readers to think constructively about their own views.
Changes in intellectual ability over the adult years are complex and important to understand because they can inform social policies. There are 97 million people in the European Union at least sixty-five years old. Three out of 10 live alone, and only 9 out of 100 between sixty-five and seventy-five are economically active. In the United States, the number of people sixty-five or over is 48 million now, in 2023, and this number will rise to 98 million by 2060. In China, the estimate is 487 million people aged sixty-five or older by 2050. The number for Japan will be a quarter of its total population.
Collecting job analysis ratings for a large number of jobs via surveys, interviews, or focus groups can put a very large burden on organizations. In this study, we describe and evaluate a streamlined, natural language processing-based approach to estimating (a) the importance of various knowledges, skills, abilities, and other characteristics (KSAOs) to jobs, and (b) how descriptive various interests are of work on a job. Specifically, we evaluate whether we can train a machine to accurately estimate KSAO ratings for jobs using job description and task statement text as the sole input. Data for 963 occupations from the U.S. Department of Labor’s Occupational Information Network (O*NET) system and an independent set of 229 occupations from a large organization provided the basis for the evaluation. Our approach produced KSAO predictions that had cross-validated correlations with subject matter expert (SME) ratings of knowledges, skills, abilities, and interests of .74, .80, .75, and .84, respectively (on average, across the 126 KSAOs examined). We found clear evidence for the validity of machine-based predictions based on (a) convergence among machine-based and SME-furnished ratings, (b) conceptually meaningful patterns of prediction model regression coefficients among the KSAOs examined, and (c) conceptual relevance of top predictor models underlying related clusters of KSAOs. We also found that prediction models developed on O*NET data produced meaningful results when applied to an independent set of job descriptions and tasks. Implications of this work, as well as suggested directions for future job analysis research and practice, are discussed.
The authors review the development of the modern paradigm for intelligence assessment and application and consider the differentiation between intelligence-as-maximal performance and intelligence-as-typical performance. They review theories of intelligence, personality, and interest as a means to establish potential overlap. Consideration of intelligence-as-typical performance provides a basis for evaluation of intelligence–personality and intelligence–interest relations. Evaluation of relations among personality constructs, vocational interests, and intellectual abilities provides evidence for communality across the domains of personality of J. L. Holland's (1959) model of vocational interests. The authors provide an extensive meta-analysis of personality–intellectual ability correlations, and a review of interest–intellectual ability associations. They identify 4 trait complexes: social, clerical/conventional, science/math, and intellectual/cultural.
In this article, I present a theory that explains the origin of sex differences in technical aptitudes. The theory takes as proven that there are no sex differences in general mental ability (GMA), and it postulates that sex differences in technical aptitude (TA) stem from differences in experience in technical areas, which is in turn based on sex differences in technical interests. Using a large data set, I tested and found support for four predictions made by this theory: (a) the construct level correlation between technical aptitude and GMA is larger for females than males, (b) the observed and true score variability of technical aptitude is greater among males than females, (c) at every level of GMA females have lower levels of technical aptitude, and (d) technical aptitude measures used as estimates of GMA for decision purposes would result in underestimation of GMA levels for girls and women. Given that GMA carries the weight of prediction of job performance, the support found for this last prediction suggests that, for many jobs, technical aptitude tests may underpredict the job performance of female applicants and employees. Future research should examine this question.
© Association for Psychological Science 2011.
Very narrow tests measuring knowledge of specific information from Project TALENT were combined into two composites on the basis of between-group differences for high-school-age boys and girls. These composites were analyzed to determine what happens when specific, nontrait components of variance are included in measures of general intelligence. The two composites were heavily advantageous to either males or females and were made up of very narrow, mostly nonacademic, information-dependent subtests. Correlations were computed between the sex-advantage composites and general intelligence scores. Very large validities were obtained, indicating that the composites were acting as excellent measures of general intelligence for both sexes. Results are discussed in the framework of multiple determinants of responses and group differences in item and test performance.
Holland's (1985a) typology of persons and environments is outlined, and support for the theory as an explanation of stability and change in careers and work satisfaction is summarized. Studies show that people flourish in their work environment when there is a good fit between their personality type and the characteristics of the environment. Lack of congruence between personality and environment leads to dissatisfaction, unstable career paths, and lowered performance. The results of recent research designed to strengthen the explanatory power of Holland's typology and link it to the Big Five personality factors is described. Speculations about the application of the theory to future careers in a changing economy are offered.
Brain organization theory posits a cascade of physiological and behavioral changes initiated and shaped by prenatal hormones. Recently, this theory has been associated with outcomes including gendered toy preference, 2D/4D digit ratio, personality characteristics, sexual orientation, and cognitive profile (spatial, verbal, and mathematical abilities). We examine the evidence for this claim, focusing on 2D/4D and its putative role as a biomarker for organizational features that influence cognitive abilities/interests predisposing males toward mathematically and spatially intensive careers. Although massive support exists for early brain organization theory overall, there are myriad inconsistencies, alternative explanations, and outright contradictions that must be addressed while still taking the entire theory into account. Like a fractal within the larger theory, the 2D/4D hypothesis mirrors this overall support on a smaller scale while likewise suffering from inconsistencies (positive, negative, and sex-dependent correlations), alternative explanations (2D/4D related to spatial preferences rather than abilities per se), and contradictions (feminine 2D/4D in men associated with higher spatial ability). Using the debate over brain organization theory as the theoretical stage, we focus on 2D/4D evidence as an increasingly important player on this stage, a demonstrative case in point of the evidential complexities of the broader debate, and an increasingly important topic in its own right.
Entwicklung von Gc nach der Schule (S. 143, siehe auch Ackerman, 1996, 234f):
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One must not forget that nine-tenths of generalizations and theorizing about intelligence and intelligence tests are based on observations in school (p. 142)
