Should students be smart, curious, or both? Fluid intelligence, openness, and interest co-shape the acquisition of reading and math competence

Crystallized Intelligence, Fluid Intelligence, and Need for Cognition: Their Longitudinal Relations in Adolescence

Investment theory and related theoretical approaches suggest a dynamic interplay between crystallized intelligence, fluid intelligence, and investment traits like need for cognition. Although cross-sectional studies have found positive correlations between these constructs, longitudinal research testing all of their relations over time is scarce. In our pre-registered longitudinal study, we examined whether initial levels of crystallized intelligence, fluid intelligence, and need for cognition predicted changes in each other. We analyzed data from 341 German students in grades 7-9 who were assessed twice, one year apart. Using multi-process latent change score models, we found that changes in fluid intelligence were positively predicted by prior need for cognition, and changes in need for cognition were positively predicted by prior fluid intelligence. Changes in crystallized intelligence were not significantly predicted by prior Gf, prior NFC, or their interaction, contrary to theoretical assumptions. This pattern of results was largely replicated in a model including all constructs simultaneously. Our findings support the notion that intelligence and investment traits, particularly need for cognition, positively interact during cognitive development, but this interplay was unexpectedly limited to Gf.

Does using artificial intelligence assistance accelerate skill decay and hinder skill development without performers' awareness?

Artificial intelligence in the workplace is becoming increasingly common. These tools are sometimes used to aid users in performing their task, for example, when an artificial intelligence tool assists a radiologist in their search for abnormalities in radiographic images. The use of artificial intelligence brings a wealth of benefits, such as increasing the efficiency and efficacy of performance. However, little research has been conducted to determine how the use of artificial intelligence assistants might affect the user's cognitive skills. In this theoretical perspective, we discuss how artificial intelligence assistants might accelerate skill decay among experts and hinder skill acquisition among learners. Further, we discuss how AI assistants might also prevent experts and learners from recognizing these deleterious effects. We then discuss the types of questions: use-inspired basic cognitive researchers, applied researchers, and computer science researchers should seek to answer. We conclude that multidisciplinary research from use-inspired basic cognitive research, domain-specific applied research, and technical research (e.g., human factors research, computer science research) is needed to (a) understand these potential consequences, (b) design artificial intelligence systems to mitigate these impacts, and (c) develop training and use protocols to prevent negative impacts on users' cognitive skills. Only by answering these questions from multidisciplinary perspectives can we harness the benefits of artificial intelligence in the workplace while preventing negative impacts on users' cognitive skills.

The interplay between investment traits and cognitive abilities: Investigating reciprocal effects in elementary school age

Based on investment theories and guided by Mussel's (2013) intellect model, the present study investigated reciprocal relations over 1 year (2021-2022) between investment traits (need for cognition, achievement motives, epistemic curiosity) and fluid and crystallized cognitive abilities in 565 German elementary school children (298 girls; Mage = 8.40, SD = 0.59; 59.5% with immigration background). Children's fluid and crystallized abilities increased over time, whereas fear of failure and curiosity decreased. Investment traits barely predicted change in cognitive abilities. However, mathematical ability predicted change in most investment traits (.14 ≤ |β| ≤ .20), even after accounting for control variables. Results largely contradict investment theories but support the role of crystallized abilities for the development of investment traits in elementary school age.

Personality, intelligence, and academic achievement: Charting their developmental interplay

OBJECTIVE

Although intelligence and personality traits have long been recognized as key predictors of students' academic achievement, little is known about their longitudinal and reciprocal associations. Here, we charted the developmental interplay of intelligence, personality (Big Five) and academic achievement in 3880 German secondary school students, who were assessed four times between the ages 11 and 14 years (i.e., in grades 5, 6, 7, and 8).

METHOD

We fitted random intercept cross-lagged panel models (RI-CLPs) to investigate reciprocal within-person associations between (a) academic achievement and intelligence, (b) academic achievement and personality, as well as (c) intelligence and personality.

RESULTS

The results revealed negative within-person associations between Conscientiousness and Extraversion assessed at the first wave of measurement and intelligence assessed at the second wave. None of the reciprocal personality-achievement associations attained statistical significance. Academic achievement and intelligence showed reciprocal within-person relations, with the strongest coefficients found for achievement longitudinally predicting intelligence.

CONCLUSIONS

Our work contributes to developmental theorizing on interrelations between personality, intelligence, and academic achievement, as well as to within-person conceptualizations in personality research.

Different cognitive mechanisms used for solving open and closed math problems

Problem-solving skills are very important in our daily life. Almost all problem-solving studies have addressed the cognitive correlates of solving closed problems, but only limited studies have investigated the cognitive mechanisms of solving open problems. The current study aimed to systematically examine differences between the cognitive mechanisms used for solving open and closed problems. In total, the abilities of 142 high school students to solve open and closed problems were assessed, as were a series of general cognitive abilities as controlled variates. Analogical reasoning uniquely contributed to solving both open and closed math problems, after controlling for age, gender, and inductive reasoning. Reactive cognitive flexibility (measured using the Wisconsin card sorting test) and spatial working memory uniquely correlated only with solving open and closed math problems, respectively. These findings suggest that the cognitive processes used to solve open and closed math problems differ. Open and closed math problems appear to require more reactive cognitive flexibility for generation and more memory for retrieval, respectively.

What Is Mathematical Giftedness? Associations with Intelligence, Openness, and Need for Cognition

It is common practice in the educational system to foster high mathematical abilities in schools as well as in specific promotional programs. Still, little is known about the construct of mathematical giftedness itself. In line with intellectual investment theories, our study investigates the relationship between fluid intelligence (figural and numerical), openness, and the need for cognition with mathematical abilities. The current study is based on a sample (N = 115) of seventh graders participating in the application process for a promotion program. The results of our regression analyses show a positive link between fluid intelligence and mathematical abilities. However, neither the association with openness nor the need for cognition reached significance, emphasizing the importance of cognitive abilities for mathematical giftedness. Limitations and further directions are discussed.

Factors influencing secondary school students' reading literacy: An analysis based on XGBoost and SHAP methods

This paper constructs a predictive model of student reading literacy based on data from students who participated in the Program for International Student Assessment (PISA 2018) from four provinces/municipalities of China, i.e., Beijing, Shanghai, Jiangsu and Zhejiang. We calculated the contribution of influencing factors in the model by using eXtreme Gradient Boosting (XGBoost) algorithm and sHapley additive exPlanations (SHAP) values, and get the following findings: (1) Factors that have the greatest impact on students' reading literacy are from individual and family levels, with school-level factors taking a relative back seat. (2) The most important influencing factors at individual level are reading metacognition and reading interest. (3) The most important factors at family level are ESCS (index of economic, social and cultural status) and language environment, and dialect is negative for reading literacy, whereas proficiency in both a dialect and Mandarin plays a positive role. (4) At the school level, the most important factors are time dedicated to learning and class discipline, and we found that there is an optimal value for learning time, which suggests that reasonable learning time is beneficial, but overextended learning time may make academic performance worse instead of improving it.

Number sense: the mediating effect between nonverbal intelligence and children's mathematical performance

The study explored the mediating effect of number sense between nonverbal intelligence and children's mathematical performance. The sample consisted of 131 pupils in Shaoxing City of China from grades 1, 3, and 5. The students completed measures of nonverbal intelligence, number sense, basic arithmetic ability, mathematical performance, rapid automatized naming, and working memory. Results show that although all variables significantly relate with each other (all p < .01), only nonverbal intelligence, number sense, and basic arithmetic ability significantly affect children's mathematical performance (all p < .01). According to multiple-mediation model, nonverbal intelligence significantly predicts children's mathematical performance through number sense and basic arithmetic ability. These findings suggest that domain-specific mathematical skills play a prominent role in children's mathematical performance in primary school, rather than domain-general cognitive functions. Educators should pay attention to develop children's number sense in order to improve children's mathematical ability.

Interest-Ability Profiles: An Integrative Approach to Knowledge Acquisition

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.

Being Snoopy and Smart

Abstract. Curiosity is a basic driver for learning and development. It has been conceptualized as a desire for new information and knowledge that motivates people to explore their physical and social environment. This raises the question of whether curiosity facilitates the acquisition of knowledge. The present study ( N = 100) assessed epistemic curiosity and general knowledge as well as fluid intelligence (i.e., reasoning ability, processing speed, memory) in a student sample. The results indicate that epistemic curiosity is moderately related to knowledge ( r = .24) and reasoning ability ( r = .30). None of the fluid intelligence measures did moderate the relationship between curiosity and knowledge (interaction terms β < |.08|). Rather, reasoning ability mediated the relationship between epistemic curiosity and general knowledge (indirect effect: β = .10, p < .05). The findings suggest that epistemic curiosity facilitates the acquisition of knowledge by promoting reasoning. One might speculate that epistemically curious individuals enrich their environment, which in turn enhances their cognitive ability.

Fluid Intelligence and Competence Development in Secondary Schooling: No Evidence for a Moderating Role of Conscientiousness

Fluid intelligence and conscientiousness are important predictors of students’ academic performance and competence gains. Although their individual contributions have been widely acknowledged, less is known about their potential interplay. Do students profit disproportionately from being both smart and conscientious? We addressed this question using longitudinal data from two large student samples of the German National Educational Panel Study. In the first sample, we analyzed reading and mathematics competencies of 3778 fourth graders (Mage = 9.29, 51% female) and gains therein until grade 7. In the second sample, we analyzed the same competencies in 4942 seventh graders (Mage = 12.49, 49% female) and gains therein until grade 9. The results of (moderated) latent change score models supported fluid intelligence as the most consistent predictor of competence levels and gains, whereas conscientiousness predicted initial competence levels in mathematics and reading as well as gains in mathematics (but not reading) only in the older sample. There was no evidence for interaction effects between fluid intelligence and conscientiousness. We found only one statistically significant synergistic interaction in the older sample for gains in reading competence, which disappeared when including covariates. Although our findings point to largely independent effects of fluid intelligence and conscientiousness on competence gains, we delineate avenues for future research to illuminate their potential interplay.

The Role of Intelligence and Self-Concept for Teachers’ Competence

Research on intelligence and competence has developed widely independent of each other. The present paper aims at relating these traditions and at integrating the dominant models to fill gaps in the respective theories. We test the structural models derived from this integration in a series of confirmatory factor analyses and a latent moderated structural equations approach using teachers as an example. The data reveal that both fluid intelligence (gf) and domain-specific knowledge affect teachers’ ability to solve the domain-specific items. Teachers’ academic self-concept related to mathematics explains individual differences beyond gf. An interaction effect between gf and self-concept exists for teachers’ pedagogical content and general pedagogical knowledge, but not for their mathematics knowledge. This finding indicates that a positive self-concept cannot compensate for a lack of gf, but it supports the acquisition of domain-specific knowledge in case of high gf, probably because it facilitates overcoming challenges.

Antecedents of Interest and the Investment of Fluid Intelligence in the Formation of Crystalized Intelligence

Most of the studies of the effects of fluid intelligence and non-cognitive characteristics on crystalized intelligence examined additive effects. The results of the few studies that examined interactive effects are inconsistent. Some find a positive (facilitating) interaction and some find a negative (compensatory) interaction. We improve on these previous studies by examining non-cognitive characteristics that were not studied before and by using a very large representative sample (n = 11,266). We find a positive/facilitating interaction. We discuss the implication of these results to theories about the joint effect of fluid intelligence and non-cognitive characteristics on crystalized intelligence.