The role of intelligence and personality traits in explaining school achievement is crucial. However, their mutual impact on academic success remains unclear due to ambiguous results--the synergistic hypothesis versus the compensatory hypothesis. Additionally, there is a lack of research on representative samples, particularly concerning the…

The present study aimed to explore the association between creativity, intelligence, and personality. The study recruited sixty healthy volunteers in the age range of 20-40 years from Bengaluru city (formerly Bangalore), South India, and administered tests for fluid intelligence (Raven's Standard Progressive Matrices), personality (Big Five…

The current study examined whether social competence and autistic traits are related to anxiety and depression in autistic and non-autistic children. Parents of 340 children aged 6 to 12 years old, including 186 autistic and 154 non-autistic children completed the Autism Spectrum Quotient (AQ) to assess their child's autistic traits, the…

This paper examines whether general intelligence (g) factors derived from different test batteries are equivalent. There are three views regarding the equivalency of g-factors: (1) "indicator indifference" claims that test content is irrelevant as long as g loadings are identical and that single tests can be adequate indicators of g; (2)…

Background/purpose: Threshold theory posits that a certain minimum level of intelligence, the "threshold," is essential for creativity to emerge. Beyond this level, the influence of intelligence on creativity diminishes. This study investigates the relationship between creativity and intelligence scores among exceptionally gifted,…

Higher education institutions have consistently strived to provide students with top-notch education. To achieve better outcomes, machine learning (ML) algorithms greatly simplify the prediction process. ML can be utilized by academicians to obtain insight into student data and mine data for forecasting the performance. In this paper, the authors…

This study compared Stepwise Logistic Regression (Stepwise-LR) and three machine learning (ML) methods--Classification and Regression Trees (CART), Random Forest (RF), and Generalized Boosted Modeling (GBM) for estimating propensity scores (PS) applied in causal inference. A simulation study was conducted considering factors of the sample size,…

This study aims to determine whether there is a relationship between linguistic intelligence and computational thinking. The research method employed is quantitative, utilizing a correlational research design. The research sample comprised 73 students from 4 elementary schools in the Laweyan District, Surakarta City. Data collection involved a…

Despite studies showing that individuals with higher levels of emotional intelligence report higher job satisfaction and happiness, relatively few studies have looked at the relationship between higher levels of emotional intelligence and lower levels of teacher burnout, especially among music teachers. With so many music teaching positions going…

The present study aimed to analyse if self-control, self-esteem and self-efficacy are related to the use of artificial intelligence tools. These tools are being incorporated to educational practices, but there is a lack of empirical evidence about the relation between artificial intelligence use by students and their personal and psychological…

The present study explored EFL students' perceptions and experiences in utilising ChatGPT to seek feedback for writing. The present study also examined how levels of metacognitive awareness (MA) influenced these perceptions and experiences. Utilising a mixed-method research design, the study collected data from a total of 40 EFL undergraduates…

In clinical and forensic evaluations, clinical neuropsychologists measure performance validity using standalone and embedded measures. Given the need to capture neuropsychological functioning through a variety of cognitive tests, newer, more sensitive measures should be evaluated for their utility in comparison to already established measures.…

Many individuals with autism experience challenges using language in social contexts (i.e., pragmatic language). Characterizing and understanding pragmatic variability is important to inform intervention strategies and the etiology of communication challenges in autism; however, current manual coding-based methods are often time and labor…

Artificial intelligence (AI) is revolutionizing journalism, necessitating a reevaluation of journalism education. The mixed-method study employs the Unified Theory of Acceptance and Use of Technology (UTAUT) to investigate the factors influencing AI adoption among Egyptian journalism professors from eight universities. Findings indicate that…

Large language models (LLMs) provide cost-effective but possibly inaccurate predictions of human behavior. Despite growing evidence that predicted and observed behavior are often not "interchangeable," there is limited guidance on using LLMs to obtain valid estimates of causal effects and other parameters. We argue that LLM predictions…