Journal of Intelligence最新文献

Emotional Intelligence (EI) in teaching is associated with various educational outcomes and processes. However, it has typically been measured through self-reports and general EI assessments, lacking a specific performance test with greater ecological validity in relation to the demands of the professional educational context. This study describes the development and validation results of the Video-Test of Emotional Intelligence for Teachers (ViTIED), a new performance-based measure to assess the EI of secondary education teachers based on ability EI model and the situational judgment test paradigm. The test comprises 12 video scenes designed to elicit intra- and interpersonal processes, as well as both positive and negative emotions. A total of 163 Spanish teachers (36% male, 64% female; mean age = 40.32 years) completed the ViTIED, along with personality, perceived EI, and burnout assessments. Test scores provide initial evidence of adequate reliability, as well as content, convergent, and divergent validity. Continued validation of this measure will benefit evaluation and intervention processes with teachers, as well as research on the impact of teachers' EI on the teaching-learning processes and the well-being of the educational community.

Mental rotation is an important aspect of spatial ability. While the importance of measuring mental rotation has been explored, disputes still exist within the literature surrounding sources of item difficulty in mental rotation tests (MRTs). Furthermore, gender differences in MRT performance are often seen but not fully understood. In the current study, we analyzed sources of item difficulty in a set of spatial ability test items using the Linear Logistic Test Model (LLTM). We found that items with more cubes, color differences, and higher rotational complexity tend to be more difficult, whereas items that contain occlusion, a mirrored structure, and a homogenous configuration type tend to be easier. Next, using Differential Component Functioning (DCF) analysis, we analyzed gender differences across these different item characteristics, finding that the number of cubes and color characteristics made questions more difficult for males when compared to females. The results and implications of this study are discussed in further detail.

Curricula in school often do not prepare students adequately for the kinds of critical and creative thinking that they will need in their careers and lives. Part of the problem is that the characteristics of real-world problems differ greatly from the characteristics of many curricular activities, and so what the students learn in school about critical and creative thinking may fail when generalized to everyday problems. We suggest that extracurricular activities, such as in aspects of musical and athletic training, often prepare students better for real-world challenges. We describe the kinds of methods that can be used in curricular instruction to better prepare students for the challenges of the everyday world.

After almost a century of global generational IQ test score gains, the Flynn effect has, in the past decades, been observed to show stagnation and reversals in several countries. Tentative evidence from academic achievement data has suggested that these trajectory changes may be rooted in a decreasing strength of the positive manifold of intelligence due to increasing ability differentiation and specialization in the general population. Here, we provide direct evidence for generational IQ test score and positive manifold strength changes based on IQ test standardization data from 1392 Austrian residents between 2005 and 2018. Our analyses revealed positive Flynn effects across all domains of the IQ test (Cohen's d from 0.21 to 0.91) but a trend toward decreasing strength in the positive manifold of intelligence (R² from .908 to .892), though these changes were not statistically significant. Our results are consistent with the idea that increasingly inconsistent Flynn effect trajectories may be attributed to increasing ability differentiation and specialization in the general population over time.

Technological advances have introduced new methods for assessing psychological constructs, moving beyond traditional paper-pencil tests. Game-related assessments (GRAs) offer several advantages for research and practice, though questions about their construct validity persist. This meta-analysis investigated the relationship between indicators derived from computer-based games and traditional cognitive ability measures, examining whether measurement scope (single vs. multiple indicators) or measurement medium of cognitive ability (computer-based vs. paper-pencil) influences this relationship. We identified 52 eligible samples stemming from 44 papers, including data from over 6100 adult participants. The results from three-stage mixed-effects meta-analyses showed an overall observed correlation of r = 0.30 (p < 0.001; corrected r = 0.45) between GRA indicators and traditional cognitive ability measures with substantial heterogeneity in effect sizes. Stronger relationships were found when cognitive ability was measured by multiple indicators, but no differences emerged based on the measurement medium of cognitive ability. Furthermore, GRAs intended to assess cognitive ability did not show stronger relationships with traditional measures of cognitive ability than GRAs not specifically used to measure cognitive ability. Overall, our findings suggest that GRAs are related to traditional cognitive ability measures. However, the overall effect size raises questions about whether GRAs and traditional measures capture the same aspects of cognitive ability or if GRAs also measure other constructs beyond cognitive ability.

Need for Cognition (NFC) refers to the enjoyment of and the search for intellectual challenges. Although numerous studies suggest associations between NFC and cognitive performance, the processes and factors that may mediate the relationship are not yet well understood. Based on the literature suggesting that self-efficacy (SE) expectancies mediate the relationship between NFC and cognitive performance, we sought to investigate this relationship systematically under controlled laboratory conditions. Additionally, we were interested in whether the visibility of the test subject's performance to others (i.e., the experimenter) would influence these correlations. After an online questionnaire assessing NFC, 204 participants completed a set of highly demanding intelligence tasks in the laboratory. Following the sample tasks and prior to working through the task battery, task-specific SE about solving the tasks was assessed. To examine the role of visibility, participants either worked alone or were observed by the investigator while completing the tasks. We found a moderate positive association between NFC and task-specific SE, as well as a significant small positive association between NFC and task performance. Further analyses indicated that the relationship between NFC and task performance is fully mediated by task-specific SE, without any moderation effects related to the visibility of one's own task performance to others. Our study suggests that the relationship between NFC and cognitive performance is also due to the positive influence of NFC on task-specific SE, which in turn influences cognitive performance.

We posit that curiosity, an epistemic emotion, is an integral part of entrepreneurial education, entrepreneurial activities, and learning, which seek to develop an entrepreneurial mindset, a form of cognitive ability. The purpose of the present investigation was to examine the influence of autonomy and competence satisfaction on epistemic curiosity and the influence of epistemic curiosity on epistemic satisfaction and performance on epistemic activities in entrepreneurial education. Participants completed a battery of questionnaires in three waves of data collection. Results showed a positive relationship between the satisfaction of the need for autonomy and competence in times 1 and 2. The satisfaction of the need for competence at times 1 and 2 then had a positive relationship with epistemic curiosity at times 1 and 2. Curiosity at time 2 had a positive relationship with epistemic satisfaction at time 3. Our results supported the idea that autonomy and competence satisfaction facilitated the experience of epistemic curiosity and epistemic satisfaction. The implications of developing an entrepreneurial mindset were discussed.

Non-intellectual factors in mathematics are key psychological factors that influence students' cognitive activities and, consequently, their learning efficiency. While the assessment of these factors has gained increasing academic attention, research on the effective use of intelligent tools to assess and improve students' non-intellectual factors remains insufficient. This study employed intelligent technology to develop the Intelligent Assessment and Strategy Implementation System for Non-intellectual Factors in Mathematics Learning for Primary and Secondary School Students, which integrates an assessment index system, scales, regional norms, and personalized improvement strategies, enabling it to automatically generate bulk reports on students' non-intellectual factor scores across various dimensions and provide targeted improvement strategies. In order to test its effectiveness, the intelligent system was applied across several provinces, cities, and schools in China. Eleventh-grade students from X Middle School in T City served as a representative case study. The interventions were based on the strategies provided by the system, and the research consistently demonstrated that the "Intelligent Assessment and Strategy Implementation System of Mathematics Non-intellectual Factors for Primary and Secondary School Students" effectively delivers high-precision diagnoses and personalized intervention strategies.

This study examined generative artificial intelligences (GenAIs), as popularized by ChatGPT, in standardized creativity tests. Benchmarking GenAI against human performance, the results showed that ChatGPT demonstrated remarkable fluency in content generation, though the creative output was average. The random nature of AI creativity and the dependency on the richness of the training database require a reassessment of traditional creativity metrics, especially for AI. Our findings highlight the integral role humans play in guiding AI to foster genuine originality, suggesting the need for future research in human-AI co-creation and the development of robust AI creativity measurement mechanisms.

Universities and schools rely heavily on the ability to forecast student performance, as it enables them to develop efficient strategies for enhancing academic results and averting student attrition. The automation of processes and the management of large datasets generated by technology-enhanced learning tools can facilitate the analysis and processing of these data, which provides crucial insights into the knowledge of students and their engagement with academic endeavors. The method under consideration aims to forecast the academic achievement of students through an ensemble of deep neural networks. The proposed method presents a new feature-ranking mechanism based on existing approaches. This mechanism is effective in identifying the most pertinent features and their correlation with the academic performance of students. The proposed method employs an optimization strategy to concurrently configure and train the deep neural networks within our ensemble system. Furthermore, the proposed ensemble model uses weighted voting among its learning components for more accurate prediction. Put simply, the suggested approach enhances the accuracy of academic performance predictions for students not only by employing weighted ensemble techniques, but also by optimizing the parameters of deep learning models. These experimental outcomes provide evidence that the proposed method outperformed the alternative approaches, accurately predicting student performance with a root-mean-square error (RMSE) value of 1.66, a Mean Absolute Percentage Error (MAPE) value of 9.75, and an R-squared value of 0.7430. These results show a significant improvement compared to the null model (RMSE = 4.05, MAPE = 24.89, and R-squared = 0.2897) and prove the efficiency of the techniques employed in the proposed method.