In the past 15 years, a substantial body of evidence has confirmed that a powerful distributional learning mechanism is present in infants, children, adults and (at least to some degree) in nonhuman animals as well. The present article briefly reviews this literature and then examines some of the fundamental questions that must be addressed for…

In this article, I outline research carried out on in an Ethnomathematics course designed to train Indigenous teachers in Costa Rica, in which the following ethnic groups participated: Ngabes, Bribris, and Cabecares. The challenge is to develop a mathematical education that provides equitable conditions for the different groups within innovative…

In this study, artificial neural networks are suggested as a model that can be "trained" to yield qualitative results out of a huge amount of categorical data. It can be said that this is a new approach applied in educational qualitative data analysis. In this direction, a cascade-forward back-propagation neural network (CFBPN) model was…

The present study employed data simulation techniques to investigate the 1-year stability of alternative classification schemes for identifying children with reading disabilities. Classification schemes investigated include low performance, unexpected low performance, dual-discrepancy, and a rudimentary form of constellation model of reading…

In e-learning systems, the tutors play many roles and carry out several tasks that differ from one system to another. The activity of tutoring is influenced by many factors. One factor among them is the assignment of the appropriate profile to the tutor. For this reason, the authors propose a new approach for modeling and evaluating the function…

We examined how feedback delay and stimulus offset timing affected declarative, rule-based and procedural, information-integration category-learning. We predicted that small feedback delays of several hundred milliseconds would lead to the best information-integration learning based on a highly regarded neurobiological model of learning in the…

Category-specific deficits have rarely been reported in semantic dementia (SD). To our knowledge, only four previous studies have documented category-specific deficits, and these have focused on the living versus non-living things contrast rather than on more fine-grained semantic categories. This study aimed to determine whether a…

President Obama's "Educate to Innovate" initiative emphasizes training in the areas of Science, Technology, Engineering, and Math (STEM). More recently, arts have been added to STEM, resulting in the acronym STEAM: Science and Technology interpreted through Engineering and the Arts, based in the Mathematical elements. However, should the…

The present study is intended to critically examine metadiscourse markers in 24 master thesis abstracts. Twelve of them are written by non-native Iraqi female students and the rest by native American female students. To do so, the researchers have set two aims: examining the types and subtypes of metadiscourse markers in terms of nativity and…

This article describes a predictive model that assesses whether a student will have greater perceived learning in group assignments or in individual work. The model produces correct classifications 87.5% of the time. The research is notable in that it is the first in the education literature to adopt a predictive modeling methodology using data…

Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…

Despite embracing a bio-psycho-social perspective, the World Health Organization's International Classification of Functioning, Disability and Health (ICF) assessment framework has had limited application to date with children who have special educational needs (SEN). This study examines its utility for educational psychologists' work with…

This research examines issues regarding model estimation and robustness in the use of Bayesian Inference Networks (BINs) for measuring Learning Progressions (LPs). It provides background information on LPs and how they might be used in practice. Two simulation studies are performed, along with real data examples. The first study examines the case…

Using a complex simulation study we investigated parameter recovery, classification accuracy, and performance of two item-fit statistics for correct and misspecified diagnostic classification models within a log-linear modeling framework. The basic manipulated test design factors included the number of respondents (1,000 vs. 10,000), attributes (3…

We investigated changes in bias (preference for one response alternative) in signal detection when relative reinforcer frequency for correct responses varied across sessions. In Experiment 1, 4 rats responded in a two-stimulus, two-response identification procedure employing temporal stimuli (short vs. long houselight presentations). Relative…