Artificial intelligence (AI) transforms the ethical and moral subjectivity of teachers, positioning them to navigate the complex convergence of technological advancement, intellectual autonomy, and teacher identity. The purpose of this paper is to offer a conceptual model for how teachers' identities are constituted through AI prompt engineering.…

Effective communication skills are essential for success in both academic and professional contexts. This concept paper presents a novel framework designed to operationally define and support the development of assessments of communication skills with a specific emphasis on K-12 settings. Through discussions on important considerations for the…

Structural equation modeling (SEM) is a statistical method widely used in educational research to investigate relationships between variables. SEM models are typically constructed based on theoretical foundations and assessed through fit indices. However, a well-fitting SEM model alone is not sufficient to verify the causal inferences underlying…

The following study shows how reparameterizations and constraints of the general linear model can serve to parse quantitative and qualitative aspects of predictors. We demonstrate three different approaches. The study uses data from the High School Longitudinal Study of 2009 on mathematics course-taking and achievement as an example. Results show…

The paper describes the research of causal relationships between the factors of technological, organizational, environmental, and personal contexts and their influence on the development of learning intentions in potential students. Its purpose was to develop a mechanism for designing a public online educational resource platform based on the…

This study used a meta-analytic structural equation modeling approach to build extended versions of the simple view of reading (SVR) model in second and foreign language (SFL) learning contexts (i.e., SVR-SFL). Based on the correlation coefficients derived from primary studies, we replicated and integrated two previous extended meta-analytic SVR…

Diagnostic classification models (DCMs) are psychometric models that provide probabilistic classifications of examinees on a set of discrete latent attributes. When analyzing or constructing assessments scored by DCMs, understanding how each item influences attribute classifications can clarify the meaning of the measured constructs, facilitate…

The North Carolina Division of Child Development and Early Education (DCDEE) partnered with the American Institutes for Research® (AIR®) to develop three alternative market models for setting child care subsidy rates in the state. Child care subsidy rates are currently based on the market rate, or what providers charge for their services. The…

Self-determination, as a vital topic for individuals with disabilities, has received a narrow investigation in Saudi Arabia and the Middle Eastern communities. Therefore, it is imperative to examine evidence-based practices to furnish insight into the efficacy of self-determination models not only through theoretical research methods but also via…

This dissertation consists of three chapters that contribute to the fields of macroeconomics, economic development, and entrepreneurship. In the first chapter, "Entrepreneurship Selection and Performance in the U.S. and Across Countries: The Role of Human Capital," I seek to establish a set of stylized facts related to entrepreneurship…

Students often see college courses as the presentation of disconnected facts, especially in the life sciences. Student-created Structure Mechanism/Relationship Function (SMRF) models were analyzed to understand students' abilities to make connections between genotype, phenotype, and evolution. Students were divided into two sections; one section…

Learning analytics (LA), like much of machine learning, assumes the training and test datasets come from the same distribution. Therefore, LA models built on past observations are (implicitly) expected to work well for future observations. However, this assumption does not always hold in practice because the dataset may drift. Recently,…

Suppose "X" and "Y" are binary exposure and outcome variables, and we have full knowledge of the distribution of "Y," given application of "X." We are interested in assessing whether an outcome in some case is due to the exposure. This "probability of causation" is of interest in comparative…

Teaching leadership in today's world requires a combination of introducing theory and best practices, as well as allowing moments that are happening in real-time, both current events and interactions from the "laboratory" of the classroom, to affect the teaching agenda. Instructors can lean into the model of Intentional Emergence (IE) to…

We present a model of endogenous schooling and earnings to isolate the causal effect of parents' education on children's education and earnings outcomes. The model suggests that parents' education is positively related to children's earnings, but its relationship with children's education is ambiguous. Identification is achieved by comparing the…