This study examined the effects of fluid intelligence and trait emotional intelligence (trait EI) on academic performance in primary school-aged intellectually gifted and average children (8-11 years of age). One hundred and four average children and eighty gifted children were administered a Raven's Standard Progressive Matrices and a Trait…

Cultural intelligence is one's ability to adapt when confronted with problems arising in interactions with people or artifacts of diverse cultures. In this study, we conduct an initial construct-validation and assessment of a maximum-performance test of cultural intelligence. We assess the psychometric properties of the test and also correlate the…

The National Association for Kinesiology in Higher Education's (NAHKE) efforts to connect professionals to share our strategies and passions for success within kinesiology are more valuable than ever before and developing emotionally intelligent leaders and administrators is very important. For the 30th Delphine Hanna Commemorative Lecture, the…

Distance education between the student and the teacher through online sessions can make it difficult for a student who does not understand a concept to ask for clarification. Lack of a physical campus or social pressure from peers can demotivate students from completing their assignments. The framework of multi-intelligence English teaching based…

The current study aimed to identify the level of emotional intelligence of outstanding students at the College of Education, Al Ain University (AAU), the United Arab Emirates, and their counterparts at Princess Nourah University (PNU), in the Kingdom of Saudi Arabia. A sample of 77 students was selected from both universities, of whom 41 students…

The main goal of this study is to examine the differences between school-aged children with different chronotypes who are only children or have a sibling in the household, regarding their sleeping habits and performance in intelligence tasks. The main measures used were Chronotype Questionnaire for Children and Raven's Coloured Progressive…

Prediction of student performance in introductory programming courses can assist struggling students and improve their persistence. On the other hand, it is important for the prediction to be transparent for the instructor and students to effectively utilize the results of this prediction. Explainable Machine Learning models can effectively help…

Due to the growing demand for information technology skills, programming education has received increasing attention. Predicting students' programming performance helps teachers realize their teaching effect and students' learning status in time to provide support for students. However, few of the existing researches have taken the code that…

Collaborative problem solving (CPS) enables student groups to complete learning tasks, construct knowledge, and solve problems. Previous research has argued the importance of examining the complexity of CPS, including its multimodality, dynamics, and synergy from the complex adaptive systems perspective. However, there is limited empirical…

This research investigated the relationship between emotional intelligence of university students and their resilience ability during crisis: the pandemic of COVID-19. A large-scale quantitative approach was applied with a national survey in the midst of the fourth wave of COVID-19 outbreak in Vietnam. The research obtained data from 2252 students…

Video data offer important insights into social processes because they enable direct observation of real-life social interaction. Though such data have become abundant and increasingly accessible, they pose challenges to scalability and measurement. Computer vision (CV), i.e., software-based automated analysis of visual material, can help address…

The part of responses that is absent in the nonequivalent groups with anchor test (NEAT) design can be managed to a planned missing scenario. In the context of small sample sizes, we present a machine learning (ML)-based imputation technique called chaining random forests (CRF) to perform equating tasks within the NEAT design. Specifically, seven…

Recent approaches to the detection of cheaters in tests employ detectors from the field of machine learning. Detectors based on supervised learning algorithms achieve high accuracy but require labeled data sets with identified cheaters for training. Labeled data sets are usually not available at an early stage of the assessment period. In this…

Research on bias in artificial intelligence has grown exponentially in recent years, especially around racial bias. Many modern technologies which impact people's lives have been shown to have significant racial biases, including automatic speech recognition (ASR) systems. Emerging studies have found that widely-used ASR systems function much more…

This article analyses and reflects on the ethical aspects of using artificial intelligence (AI) systems in educational contexts. On the one hand, the impact of AI in the field of education is addressed from the perspective of the Sustainable Development Goals (specifically, SDG4) of the UNESCO 2030 Agenda, describing the opportunities for its use…