The system architecture of big data in massive open online courses (BD-MOOCs System Architecture) is composed of six components. The first component was comprised of big data tools and technologies such as Hadoop, YARN, HDFS, Spark, Hive, Sqoop, and Flume. The second component was educational data science, which is composed of the following four…

Educational institutions are creating a considerable amount of data regarding students, faculty and related organs. This data is an essential asset for academic institutions as it has valuable insights, knowledge and intelligence for the policymakers. Students are the fundamental entities and primary source of data creation in any educational…

Due to the unprecedented growth in available data collected by e-learning platforms, including platforms used by massive open online course (MOOC) providers, important opportunities arise to structurally use these data for decision making and improvement of the educational offering. Student retention is a strategic task that can be supported by…

Sentence comprehension requires both syntactic prediction and working memory processes. Evidence suggests that both are impaired in agrammatic aphasia, and can independently contribute to comprehension breakdowns, but the relationship between them, especially during real-time sentence comprehension remains unclear. Two EEG studies investigated…

Recently, Bayesian diagnostic classification modeling has been becoming popular in health psychology, education, and sociology. Typically information criteria are used for model selection when researchers want to choose the best model among alternative models. In Bayesian estimation, posterior predictive checking is a flexible Bayesian model…

Oftentimes in many fields of the social and natural sciences, data are obtained within a nested structure (e.g., students within schools). To effectively analyze data with such a structure, multilevel models are frequently employed. The present study utilizes a Monte Carlo simulation to compare several novel multilevel classification algorithms…

Cognitive scientists have long used distributional semantic representations of categories. The predominant approach uses distributional representations of category-denoting nouns, such as "city" for the category city. We propose a novel scheme that represents categories as prototypes over representations of names of its members, such as…

Methods for group comparisons using predicted probabilities and marginal effects on probabilities are developed for regression models for binary outcomes. Unlike approaches based on the comparison of regression coefficients across groups, the methods we propose are unaffected by the scalar identification of the coefficients and are expressed in…

The key aim of this special issue is to make developmental theory proposals concrete enough to evaluate with empirical data. With this in mind, I discuss proposals from the "Universal Grammar + statistics" (UG+stats) perspective for learning several morphology and syntax phenomena. I briefly review why UG has traditionally been part of…

What do a short car trip, a pandemic, the wood-wide fungal web, a challenging learning experience, a storm, transport logistics, and the language(s) we speak have in common? All of them are systems, or multiple sets of systems within systems. What happens in any set of circumstances will depend on a mix of initial conditions, complexity dynamics,…

The connection between grit and achievement in a variety of areas is well documented. Nevertheless, the factors that affect domain-specific academic grit and the relationship of these factors to academic achievement still require clarification. The present study aimed to explore the contribution of three main categories of variables: subjective…

The purpose of this quantitative correlational predictive study was to examine if a predictive relationship existed between emotional intelligence and the dimensions of burnout among K-8 teachers in the United States. The trait emotional intelligence theory and the Maslach burnout model provided the foundation for the study. The sample included…

Sequence learning is fundamental to a wide range of cognitive functions. Explaining how sequences--and the relations between the elements they comprise--are learned is a fundamental challenge to cognitive science. However, although hundreds of articles addressing this question are published each year, the actual learning mechanisms involved in the…

Drug repurposing refers to the process of discovering new therapeutic uses for existing medicines. Compared to traditional drug discovery, drug repurposing is attractive for its speed, cost, and reduced risk of failure. However, existing approaches for drug repurposing involve complex, computationally-intensive analytical methods that are not…

Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…