In this meta-study, we analyzed 2442 effect sizes from 131 meta-analyses in intelligence research, published from 1984 to 2014, to estimate the average effect size, median power, and evidence for bias. We found that the average effect size in intelligence research was a Pearson's correlation of 0.26, and the median sample size was 60. Furthermore,…

The purpose of this study is to identify the determinant role of emotional intelligence sub-dimensions (evaluation of others' emotions, evaluation of one's own emotions, regulation of emotions, social skills, use of emotions) in determining the self-efficacy levels of athletes. In addition, emotional intelligence, and self-efficacy levels of the…

Children's math learning (N = 217; M[subscript age] = 4.87 years; 63% European American, 96% college-educated families) from an intelligent character game was examined via social meaningfulness (parasocial relationships [PSRs]) and social contingency (parasocial interactions, e.g., math talk). In three studies (data collected in the DC area:…

Artificial Intelligence (AI) is attracting a great deal of attention and it is important to investigate the public perceptions of AI and their impact on the perceived credibility of research evidence. In the literature, there is evidence that people overweight research evidence when framed in neuroscience findings. In this paper, we present the…

Designing intelligent services for workplace learning presents a special challenge for researchers and developers of learning technology. One of the reasons is that considering learning as a situated and social practice is nowhere so important than in the case where learning is tightly integrated with workplace practices. The current paper…

In Aristotelian virtue theories, "phronesis" is foundational to being good, but to date accounts of how this particularly important virtue can emerge are sketchy. This article plumbs recent thinking in Aristotelian virtue ethics and developmental theorizing to explore how far its emergence can be understood developmentally, i.e., in…

This study developed and evaluated machine learning algorithms to predict children's physical activity category from raw accelerometer data collected at the hip. Fifty participants (mean age = 13.9 ± 3.0 y) completed 12 activity trials that were categorized into 5 categories: sedentary (SED), light household activities and games (LHHAG),…

In two studies, we intend to investigate whether spirituality can explain the relationship between intrinsic religious orientation (IRO) and emotional intelligence (EI). Seventy-three worshipping houses-going adults, aged 18-56, had participated in the study. Data was collected by employing Intrinsic Scale of Religious Orientation Scale,…

The goal of knowledge tracing is to track the state of a student's knowledge as it evolves over time. This plays a fundamental role in understanding the learning process and is a key task in the development of an intelligent tutoring system. In this paper we propose a novel approach to knowledge tracing that combines techniques from matrix…

Supervised machine learning has become one of the most important methods for developing educational and intelligent tutoring software; it is the backbone of many educational data mining methods for estimating knowledge, emotion, and other aspects of learning. Hence, in order to ensure optimal utilization of computing resources and effective…

Social robot in service is radically changing the ways of performing tasks and it becomes a distinct and valuable nascent. To achieve persist autonomy, robotic systems implement a closed-loop consisting of at least planning, reasoning and acting phases. From the continual loop perspective, this paper presents the ROSPlan framework, as a task…

Mathematical cognition requires coordinated activity across multiple brain regions, leading to the emergence of resting-state functional connectivity as a method for studying the neural basis of differences in mathematical achievement. Hyper-connectivity of the intraparietal sulcus (IPS), a key locus of mathematical and numerical processing, has…

Background: Though pedagogical artificial agents are expected to play a crucial role in the years to come, earlier studies provide inconsistent results regarding their effect on learning. This might be because their potential for exhibiting subtle nonverbal behaviours we know from human teachers has been untapped. What is more, there is little…

Prior research suggests that Black children are at risk for delays in diagnosis of autism, but factors that influence diagnostic timing across races remain unclear. This study analyzed data from Black and White children who received a first-time autism diagnosis at a specialty clinic. Black youth were under-represented in the group who received a…

Attrition in longitudinal studies is a major threat to the representativeness of the data and the generalizability of the findings. Typical approaches to address systematic nonresponse are either expensive and unsatisfactory (e.g., oversampling) or rely on the unrealistic assumption of data missing at random (e.g., multiple imputation). Thus,…