In latent growth curve modeling (LGCM), overall fit indices have garnered increased disputation for model selection, and model fit evaluation based on the mean structure has becoming popularity. The present study developed a versatile fit index, named Weighted Root Mean Squared Errors (WRMSE), based on individual case residuals (ICRs) with the aim…

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…

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…

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…

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…

Despite numerous studies about language learning strategies (LLSs), many learners still misunderstand their effectiveness, thinking they require too much effort for minimal gain. Additionally, students have varied and conflicting preferences for LLSs, and factors like cultural background influence their choices, indicating a need for more research…

Minority-serving institutions (MSIs) are unique in their ability to support the educational advancement of students of color. Approximately one in five postsecondary institutions are eligible for funding under an MSI designation, yet more than half of all undergraduate students of color are enrolled in such colleges and universities. However,…

Accumulating evidence suggests that there is a spontaneous preference for numerical, compared to non-numerical (e.g., cumulative surface area), information. However, given a paucity of research on the perception of non-numerical magnitudes, it is unclear whether this preference reflects a specific bias towards number, or a general bias towards the…

Research on the accuracy of Brain Fingerprinting (BFP) has produced mixed outcomes: some report 99.9% and others report lower. Furthermore, no studies have measured the susceptibility of BFP to countermeasures. In Experiment-1, we report the accurate classification of 15 of the 16 subjects, tested on their own real-life autobiographical incidents;…

The special education eligibility category that has come to be most commonly associated with Attention-Deficit Hyperactivity Disorder (ADHD) in recent years is Other Health Impairment (OHI). However, the eligibility criteria for the OHI disability category have been criticized for being especially vague, given that the disability category…

Studies on the quality of nature of science (NOS) representations in school science textbooks report them being mostly of implicit manner and not fully adequate. However, the often underlying NOS framework of the consensus list in these studies is criticized as undifferentiated and inadequate. The family resemblance approach (FRA) to NOS shows…