Strategies are an important component of self-regulated learning frameworks. However, the characterization of strategies in these frameworks is often incomplete: (1) they lack an operational definition of strategies; (2) there is limited understanding of how students develop and apply strategies; and (3) there is a dearth of systematic and…

Physics classes with computation integrated into the curriculum are a fitting setting for investigating computational thinking. In this paper, we present a framework for exploring this topic in introductory physics courses. The framework, which was developed by reviewing relevant literature and acquiring video data from high school classrooms,…

Latent growth models (LGMs) are an application of structural equation modeling and frequently used in developmental and clinical research to analyze change over time in longitudinal outcomes. Maximum likelihood (ML), the most common approach for estimating LGMs, can fail to converge or may produce biased estimates in complex LGMs especially in…

This study compares two missing data procedures in the context of ordinal factor analysis models: pairwise deletion (PD; the default setting in Mplus) and multiple imputation (MI). We examine which procedure demonstrates parameter estimates and model fit indices closer to those of complete data. The performance of PD and MI are compared under a…

Complex systems are made up of many entities, whose interactions emerge into distinct collective patterns. Computational modeling platforms can provide a powerful means to investigate emergent phenomena in complex systems. Some research has been carried out in recent years about promoting students' modeling practices, specifically using…

In undergraduate chemistry curricula that include computational modeling, students may gain first-hand experience in both introductory and advanced applications of this technique. However, although students can be exposed to the predictive power of computational work, its capabilities are often limited to determining the intrinsic properties of…

This study is intended to provide an example of computational modeling (CM) experiment using machine learning algorithms. Specific outcomes modeled in this study are the predicted influences associated with the Science Writing Heuristic (SWH) and associated with the completion of question items for the Cornell Critical Thinking Test. The Student…

As part of its Partnership for Pre-K Improvement (PPI) initiative, the Bill & Melinda Gates Foundation sponsored the RAND Corporation to study the cost of high-quality pre-K programming. The RAND study included three states--Oregon, Tennessee, and Washington--that were partnering with the foundation under PPI. The objective of the study was to…

Modeling an inter-ring torsional profile of a simple2,2'-bithiophenemolecule has been used to illustrate the main concepts associated with basic molecular modeling within an introductory course in a master's degree on computational modeling. The methodology proposed in the activity has been used to guide and train the student along the classical…

The Program for the International Assessment of Adult Competencies (PIAAC) is a multicycle survey of adult skills and competencies sponsored by the Organization for Economic Cooperation and Development (OECD). The survey examines a range of basic skills in the information age and assesses these adult skills consistently across participating…

Observable data in empirical social and behavioral science studies are often categorical (i.e., binary, ordinal, or nominal). When categorical data are outcomes, they fail to maintain the scale and distributional properties of linear regression and factor analysis. Attempting to estimate model parameters for categorical outcome data with the…

In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

This tool is intended to support state and local education agencies in developing a statistical model for estimating student postsecondary success at the school or district level. The tool guides education agency researchers, analysts, and decisionmakers through options to consider when developing their own model. The resulting model generates an…

A web design course has complex and diverse skills, which may attract students with an interest in technology and art fields to learn to program. It makes a need to have a flexible learning framework to develop all students to learn in a programming course. This study was designed to develop students' learning achievement and computational…