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…

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…

Multilayer perceptron neural networks, Gaussian naive Bayes, and logistic regression classifiers were compared when used to make early predictions regarding one-year college student persistence. Two iterations of each model were built, utilizing a grid search process within 10-fold cross-validation in order to tune model parameters for optimal…

Executive functioning abilities have been associated with important behaviors such as adaptive skills and cognitive abilities in children with and without disabilities. Executive functioning has primarily been measured as a strong predictor of later abilities in children with neurodevelopmental disabilities, such as attention-deficit/…

The purpose of this study was to develop a jazz improvisation rubric for the evaluation of collegiate jazz improvisation. To create this measure, research objectives were devised to investigate the aurally-observed performer-controlled components of improvisation, which aurally-observed components should be evaluated in an improvisatory…

Data science is a broad, interdisciplinary field concerned with the extraction of knowledge or insights from data, with the classification of data as a core, fundamental task. One of the most persistent challenges faced when performing classification is the class imbalance problem. Class imbalance refers to when the frequency with which each class…

Value-added models are a class of growth models used in education to assign responsibility for student growth to teachers or schools. For value-added models to be used fairly, sufficient statistical precision is necessary for accurate teacher classification. Previous research indicated precision below practical limits. An alternative approach has…

Virginia Commonwealth University (VCU) is implementing a large scale exploration of digital pedagogies, including connected learning and open education, in an effort to promote digital fluency and integrative thinking among students. The purpose of this study was to develop a classroom assessment toolkit for faculty who wish to document student…

In an educational landscape where teacher evaluation methods are increasingly discussed and scrutinized in research offices, legislatures, and school buildings, the differences in policy and instrumentation among states and school districts can paint a confusing picture of these varying methods and their impacts. To help assess the picture in…

Systems that can detect cognitive decline or harmful levels of stress could assist users in managing their stress and health. However, current assessments are often obtrusive or require specialized equipment, and not suited to continuous monitoring of cognitive status. This research leverages attributes of everyday keyboard interactions to…

Piecewise latent class growth analysis (LCGA) was used to examine growth patterns in reading comprehension and passage reading fluency on easyCBM, a popular formative assessment system. Unlike conventional growth modeling, LCGA takes into account the heterogeneity of growth and may provide reliable predictions for later development. Because…

Distance learning programs are being developed at many institutions of higher learning as a means of maintaining a competitive advantage. The problem is that college administrators have no reliable methods for predicting the likelihood of success or failure of these newly launched programs. There is a lack of information regarding attitudes and…

Due to the inappropriate planning and explosive population growth in urban areas, especially in developing countries, sustainable and disaster-safe urbanization has become the most important challenge for governments. Urbanization presents benefits in different ways but has led simultaneously to changes in land use/land cover (LULC), impacting…

The Internet Age has seen the emergence of richly annotated image data collections numbering in the billions of items. This work makes contributions in three primary areas which aid the management of this data: image representation, efficient retrieval, and annotation based on content and metadata. The contributions are as follows. First,…

The use of early literacy screening measures helps determine which students are at risk for future reading difficulties. However, there has been some recent concern related to the classification validity of screening measures (Hintze, Ryan, & Stoner, 2003; Nelson, 2008). Low classification validity results in the identification of a large number…