Colleges are important providers of vocational education and training and in some countries they are the major provider. Although the international literature on colleges has grown considerably in the past two decades, it still consists primarily of qualitative descriptions of college sectors in different countries. Quantitative studies of…

The current study tested changes in modern/contemporary art valuation among students ages 6-15. Participants rated abstract paintings and conceptual works (and two control categories--traditional Western figurative paintings and everyday objects) on the dimensions of liking and art classification. As we hypothesized, modern/contemporary art was…

Background: In the past few years there has been a growing interest in the employment of verbal productions as digital biomarkers, namely objective, quantifiable behavioural data that can be collected and measured by means of digital devices, allowing for a low-cost pathology detection, classification and monitoring. Numerous research papers have…

Linguistic categories can impact visual perception. For instance, learning that two objects have different names can enhance their discriminability. Previous studies have identified a typical pattern of categorical perception, characterized by faster discrimination of stimuli from different categories, a neural mismatch response during early…

In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…

Latent class analysis (LCA) is a widely used technique for detecting unobserved population heterogeneity in cross-sectional data. Despite its popularity, the performance of LCA is not well understood. In this study, we evaluate the performance of LCA with binary data by examining classification accuracy, parameter estimation accuracy, and coverage…

To support and better understand how to scale effectively, in 2020, the Millions Learning project at the Center for Universal Education (CUE) at Brookings joined the Global Partnership for Education's (GPE) Knowledge and Innovation Exchange (KIX), a joint partnership between GPE and the International Development Research Centre (IDRC), to…

In many large-scale testing programs, examinees are frequently categorized into different performance levels. These classifications are then used to make high-stakes decisions about examinees in contexts such as in licensure, certification, and educational assessments. Numerous approaches to estimating the consistency and accuracy of this…

This dissertation examined classification outcome differences among four popular individual supervised machine learning (ISML) models (logistic regression, decision tree, support vector machine, and multilayer perceptron) when predicting minor class membership within imbalanced datasets. The study context and the theoretical population sampled…

Manual exploratory behaviors during object interaction that form the basis of tool use behavior, are mostly qualitatively characterized in terms of their frequency and duration of occurrence. To fully understand their functional and clinical significance, quantitative movement characterization is needed alongside their qualitative analysis.…

There is a need to continue to amplify the value of occupational therapy for individuals with disabilities who are transitioning from secondary education to adult settings, such as vocational and post-secondary educational environments. Literature evidences a lack of practitioner knowledge of assessments and evaluations within the scope of…

A decision consistency (DC) index is an estimate of the consistency of a classification decision on an exam. More specifically, DC estimates the percentage of examinees that would have the same classification decision on an exam if they were to retake the same or a parallel form of the exam again without memory of taking the exam the first time.…

Words influence cognition well before infants know their meanings. For example, three-month-olds are more likely to form visually based categories when exemplars are paired with spoken words than with sine-wave tones, a likely precursor to learning symbolic relations between words and their referents. However, it is unclear why words have these…

In rule-based (RB) category-learning tasks, the optimal strategy is a simple explicit rule, whereas in information-integration (II) tasks, the optimal strategy is impossible to describe verbally. This study investigates the effects of two different category properties on learning difficulty in category learning tasks--namely, linear separability…

Background: A body of literature has arisen analyzing and legitimating the emerging field of engineering education research (EER). Using concepts from the sociology of knowledge, EER can be described as a region because it has relationships both to other academic fields and to its field of practice. Of interest is the strength of boundaries…