J. Intell., Volume 12, Issue 3 (March 2024) – 13 articles

Similar to the field of human intelligence, artificial intelligence (AI) has experienced a long history of advances and controversies regarding its definition, assessment, and application. Starting over 70 years ago, AI set out to achieve a single, general-purpose technology that could overcome many tasks in a similar fashion to humans. However, until recently, implementations were based on narrowly defined tasks, making the systems inapplicable to even slight variations of the same task. With recent advances towards more generality, the contemplation of artificial general intelligence (AGI) akin to human general intelligence (HGI) can no longer be easily dismissed. We follow this line of inquiry and outline some of the key questions and conceptual challenges that must be addressed in order to integrate AGI and HGI and to enable future progress towards a unified field of general intelligence. Full article

The differentiation of personality by the cognitive ability hypothesis proposes that individuals with higher cognitive ability have more variability in their personality structure than those with lower cognitive ability. A large sample of actual job candidates (n = 14,462) who participated in an online proctored test session, providing socio-demographic information and completing cognitive ability, personality, and language proficiency assessments, was used to test this hypothesis. The total sample was divided into three equal groups (low, average, high) using percentiles as the cutoff point to investigate the effects of cognitive ability. An ANCOVA demonstrated the significant effect of cognitive ability on personality traits, controlling for language proficiency. Principal component analyses showed that the personality structure differed between the cognitive ability groups, with the high-cognitive-ability group having an additional personality component. Similarly, analyses across job complexity levels indicated more personality components for high-job-complexity positions. The implications, limitations, and future directions of this study are discussed. Full article

Young children possess the fundamental deductive reasoning skills for solving their upcoming problems in their daily lives. These skills are of great importance for their school readiness and academic development. Therefore, this study aimed to explore the age differences and predictive variables of deductive reasoning skills in young Hungarian children aged 4–8 years old who reside in Hungary and Slovakia. Face-to-face data were collected from 3050 participants. The instrument of deductive reasoning skills assessment was extracted from the school readiness test, DIFER (Diagnostic System for Assessing Development). Utilizing various statistical analyses with R, AMOS, and MPlus8 packages, it was found that there were significant differences in young children’s deductive reasoning skills across countries and age groups. Parents’ education levels had significant positive relationships with children’s deductive reasoning skills development. And the variables of country and age were identified as significant predictors of children’s deductive reasoning skills. And children’s family background variables such as parental education played a significant role in predicting children’s deductive reasoning skills in Hungary. The implications of this study emphasize the importance of educational contexts, parental involvement, cross-cultural exchange, and further research, with the potential to enhance young children’s educational experiences and prospects in Hungary, Slovakia, and beyond. Full article

Item quality is crucial to psychometric analyses for cognitive diagnosis. In cognitive diagnosis models (CDMs), item quality is often quantified in terms of item parameters (e.g., guessing and slipping parameters). Calibrating the item parameters with only item response data, as a common practice, could result in challenges in identifying the cause of low-quality items (e.g., the correct answer is easy to be guessed) or devising an effective plan to improve the item quality. To resolve these challenges, we propose the item explanatory CDMs where the CDM item parameters are explained with item features such that item features can serve as an additional source of information for item parameters. The utility of the proposed models is demonstrated with the Trends in International Mathematics and Science Study (TIMSS)-released items and response data: around 20 item linguistic features were extracted from the item stem with natural language processing techniques, and the item feature engineering process is elaborated in the paper. The proposed models are used to examine the relationships between the guessing/slipping item parameters of the higher-order DINA model and eight of the item features. The findings from a follow-up simulation study are presented, which corroborate the validity of the inferences drawn from the empirical data analysis. Finally, future research directions are discussed. Full article

Women reliably perform worse than men on measures of spatial ability, particularly those involving mental rotation. At the same time, females also report higher levels of spatial anxiety than males. What remains unclear, however, is whether and in what ways gender differences in these cognitive and affective aspects of spatial processing may be interrelated. Here, we tested for robust gender differences across six different datasets in spatial ability and spatial anxiety (N = 1257, 830 females). Further, we tested for bidirectional mediation effects. We identified indirect relations between gender and spatial skills through spatial anxiety, as well as between gender and spatial anxiety through spatial skills. In the gender → spatial anxiety → spatial ability direction, spatial anxiety explained an average of 22.4% of gender differences in spatial ability. In the gender → spatial ability → spatial anxiety direction, spatial ability explained an average of 25.9% of gender differences in spatial anxiety. Broadly, these results support a strong relation between cognitive and affective factors when explaining gender differences in the spatial domain. However, the nature of this relation may be more complex than has been assumed in previous literature. On a practical level, the results of this study caution the development of interventions to address gender differences in spatial processing which focus primarily on either spatial anxiety or spatial ability until such further research can be conducted. Our results also speak to the need for future longitudinal work to determine the precise mechanisms linking cognitive and affective factors in spatial processing. Full article

The study aimed to investigate the allocation of figurative language comprehension (FLC) within the Cattell–Horn–Carroll (CHC) model of cognitive abilities, using three newly developed tests: the Reverse Paraphrase Test (RPT), the Literal Paraphrase Test (LPT), and the Proverb Test (PT). The analysis of a sample of 909 participants revealed that the RPT and LPT measured a unidimensional construct of FLC, while the PT was excluded due to insufficient fit. Combining RPT and LPT items, various models were evaluated, with a bifactor S-1 model showing the best fit, indicating the influence of a general factor (representing FLC) and test-specific method factors. The study explored FLC allocation within the CHC model, supporting its consideration as a distinct factor under the g factor. Examining the nomological network, significant correlations emerged between the Intellectual Curiosity and Aesthetic Sensitivity facets of Openness and FLC, which were comparable in size to the relation with general ability. In conclusion, the study enhances the understanding of FLC within the CHC model, advocating its recognition as a distinct factor. Correlations with Openness facets suggest valuable insights into the interplay between cognitive abilities and personality, necessitating further research for a deeper exploration of this relation. Full article

Metareasoning refers to processes that monitor and control ongoing thinking and reasoning. The “metareasoning framework” that was established in the literature in 2017 has been useful in explaining how monitoring processes during reasoning are sensitive to an individual’s fluctuating feelings of certainty and uncertainty. The framework was developed to capture metareasoning at an individual level. It does not capture metareasoning during collaborative activities. We argue this is significant, given the many domains in which team-based reasoning is critical, including design, innovation, process control, defence and security. Currently, there is no conceptual framework that addresses the nature of collaborative metareasoning in these kinds of domains. We advance a framework of collaborative metareasoning that develops an understanding of how teams respond to the demands and opportunities of the task at hand, as well as to the demands and opportunities afforded by interlocuters who have different perspectives, knowledge, skills and experiences. We point to the importance of a tripartite distinction between “self-monitoring”, “other monitoring” and “joint monitoring”. We also highlight a parallel distinction between “self-focused control”, “other-focused control” and “joint control”. In elaborating upon these distinctions, we discuss the prospects for developing a comprehensive collaborative metareasoning framework with a unique focus on language as a measure of both uncertainty and misalignment. Full article

Just as receptive emotional abilities, productive emotional abilities are essential for social communication. Although individual differences in receptive emotional abilities, such as perceiving and recognizing emotions, are well-investigated, individual differences in productive emotional abilities, such as the ability to express emotions in the face, are largely neglected. Consequently, little is known about how emotion expression abilities fit in a nomological network of related abilities and typical behavior. We developed a multitask battery for measuring the ability to pose emotional expressions scored with facial expression recognition software. With three multivariate studies (n₁ = 237; n₂ = 141; n₃ = 123), we test competing measurement models of emotion posing and relate this construct with other socio-emotional traits and cognitive abilities. We replicate the measurement model that includes a general factor of emotion posing, a nested task-specific factor, and emotion-specific factors. The emotion-posing ability factor is moderately to strongly related to receptive socio-emotional abilities, weakly related to general cognitive abilities, and weakly related to extraversion. This is strong evidence that emotion posing is a cognitive interpersonal ability. This new understanding of abilities in emotion communication opens a gateway for studying individual differences in social interaction. Full article

Language proficiency assessments are pivotal in educational and professional decision-making. With the integration of AI-driven technologies, these assessments can more frequently use item types, such as dictation tasks, producing response features with a mixture of discrete and continuous distributions. This study evaluates novel measurement models tailored to these unique response features. Specifically, we evaluated the performance of the zero-and-one-inflated extensions of the Beta, Simplex, and Samejima’s Continuous item response models and incorporated collateral information into the estimation using latent regression. Our findings highlight that while all models provided highly correlated results regarding item and person parameters, the Beta item response model showcased superior out-of-sample predictive accuracy. However, a significant challenge was the absence of established benchmarks for evaluating model and item fit for these novel item response models. There is a need for further research to establish benchmarks for evaluating the fit of these innovative models to ensure their reliability and validity in real-world applications. Full article

There is little consensus about the underlying parameters of human reasoning. Two major theories have been proposed that suppose very different mechanisms. The mental model theory proposes that people use working memory intensive processes in order to construct limited models of problem parameters. Probabilistic theories propose that reasoning is a process by which people use the sum of their existing knowledge in order to generate an estimate of the probability of a conclusion given problem parameters. Following an initial proposition by Verschueren et al., the dual-strategy model supposes that these different approaches to reasoning are in fact an important individual difference. Specifically, a recently developed diagnostic questionnaire has identified two major categories of reasoners: Counterexample reasoners use a mental model form of processing, while Statistical reasoners use a probabilistic form of processing. In the following, I describe results that show that the Counterexample/Statistical distinction affects information processing across a variety of reasoning and judgment tasks. In addition, strategy use correlates with performance on very different kinds of thinking, such as contingency judgments, processing of negative emotions, or susceptibility to social biases. Although this distinction is related to differences in cognitive ability, it has been found to predict performance over and above these differences. More recent results have shown that it is possible to experimentally modify strategy use. These results suggest that strategy use is an important individual difference that can affect performance in a wide variety of contexts. Full article

Creativity is a universal core higher-order cognitive ability in the 21st century, which reflects a country’s core competitiveness and soft power. Mindfulness, as an important concept in positive psychology, has also received attention for its potential effect on research creativity. Using structural equation modeling and bootstrap methods, this study investigated the relationship between mindfulness and research creativity among 1210 Chinese graduate students. Additionally, we explored the mediating effect of flow experience and creative self-efficacy in this relationship. The research results showed that mindfulness had a direct positive effect on graduate students’ scientific research creativity. The mediating effect of flow experience and creative self-efficacy, as well as the chain mediating effect, were established, with the mediating ratio being 13.1% and 30.0%, respectively, and the indirect effect of chain mediating accounting for 34.1%. Interestingly, the effect mechanism at the gender level was various, with the mediating effect of mindfulness on scientific research creativity being higher among male graduate students. The results of this study revealed the mechanism of mindfulness on graduate students’ scientific research creativity, offering valuable insights for enhancing their creative capabilities in the realm of scientific research. Full article