Advances in the integration of smart technology with interdisciplinary methods has created a new genre, approachable modeling and smart methods -- AM-Smart for short. AM-Smart platforms address a major challenge for applied and public sector analysts, educators and those trained in traditional methods: accessing the latest advances in…

This report is based on the discussion that emerged from a convening of a panel of 22 experts in artificial intelligence (AI) and in learning. It introduces three layers that can frame the meaning of AI for educators. First, AI can be seen as "computational intelligence" and capability can be brought to bear on educational challenges as…

The COVID-19 pandemic has resulted in unprecedented amounts of information communicated to the public relating to STEM. The pandemic can be seen as a 'wicked problem' defined by high complexity, uncertainty and contested social values requiring a transdisciplinary approach formulating social policy. This article argues that a 'Critical STEM…

Interactive problem solving environments, such as intelligent tutoring systems and educational video games, produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled the student-tutor interactions using complex network…

The Revised Hierarchical Model (RHM) of bilingual language processing dominates current thinking on bilingual language processing. Recently, basic tenets of the model have been called into question. First, there is little evidence for separate lexicons. Second, there is little evidence for language selective access. Third, the inclusion of…

Generalized structured component analysis (GSCA) is a component-based approach to structural equation modeling. In practice, researchers may often be interested in examining the interaction effects of latent variables. However, GSCA has been geared only for the specification and testing of the main effects of variables. Thus, an extension of GSCA…

In social and business sciences, the importance of the analysis of interaction effects between manifest as well as latent variables steadily increases. Researchers using partial least squares (PLS) to analyze interaction effects between latent variables need an overview of the available approaches as well as their suitability. This article…

This paper describes the results of a pedagogical experience carried out at the University of Comahue, Argentina, with an interactive text (IT) concerning Homogeneous Chemical Reactors Analysis. The IT was built on the frame of the "Mathematica" software with the aim of providing students with a robust computational tool. Students'…

The effects of misspecifying intercept-covariate interactions in a 4 time-point latent growth model were the focus of this investigation. The investigation was motivated by school growth studies in which students' entry-level skills may affect their rate of growth. We studied the latent interaction of intercept and a covariate in predicting growth…

This paper presents an updated WWC (What Works Clearinghouse) Review of the Article "Culture and the Interaction of Student Ethnicity with Reward Structure in Group Learning". The study examined the effects of different reward systems used in group learning situations on the math skills of African-American and White students. The…

"Culture and the Interaction of Student Ethnicity with Reward Structure in Group Learning" examined the effects of different reward systems used in group learning situations on the math skills of African-American and white students. The study analyzed data on 75 African-American and 57 white fourth- and fifth-grade students from urban…

The tendency to underestimate egocentric distances in immersive virtual environments (VEs) is not well understood. However, previous research (A. R. Richardson & D. Waller, 2007) has demonstrated that a brief period of interaction with the VE prior to making distance judgments can effectively eliminate subsequent underestimation. Here the authors…

The analysis of interaction among latent variables has received much attention. This article introduces a Bayesian approach to analyze a general structural equation model that accommodates the general nonlinear terms of latent variables and covariates. This approach produces a Bayesian estimate that has the same statistical optimal properties as a…

In this article, a nonlinear structural equation model is introduced and a quasi-maximum likelihood method for simultaneous estimation and testing of multiple nonlinear effects is developed. The focus of the new methodology lies on efficiency, robustness, and computational practicability. Monte-Carlo studies indicate that the method is highly…

The impact of outliers on Cronbach's coefficient [alpha] has not been documented in the psychometric or statistical literature. This is an important gap because coefficient [alpha] is the most widely used measurement statistic in all of the social, educational, and health sciences. The impact of outliers on coefficient [alpha] is investigated for…