This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

This study explores the role of artificial intelligence (AI) in K-12 student assessment practices, focusing on educators' use of AI tools. Through content analysis of active Facebook groups dedicated to AI in education, the authors examined how educators integrate AI into assessment across various grade levels and subjects. Using the Technology…

Purpose: The purpose of this study was to further evaluate an eight-step partner instructional model developed by Kent-Walsh and McNaughton that has been demonstrated to improve implementation quality and fidelity among adults in clinical and educational settings who support the use of augmentative and alternative communication (AAC) for…

The outbreak of the coronavirus disease (COVID-19) has caused unprecedented global socio-economic disruptions. One of the areas negatively impacted is the education system. The country's over reliance on traditional face-to-face teaching has brought about serious challenges to policymakers who have to decide how learning would proceed in the…

Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…

This study compared vertical scaling results for the Rasch model from BILOG-MG and WINSTEPS. The item and ability parameters for the simulated vocabulary tests were scaled across 11 grades; kindergarten through 10th. Data were based on real data and were simulated under normal and skewed distribution assumptions. WINSTEPS and BILOG-MG were each…