Students' talent and potential cannot be served until they are recognized by schools or caregivers. While the field of gifted education has had success in identifying talent among many students with talents in reading and mathematics, those with spatial talents are often overlooked. This article reviews how we might identify spatial talent using…

Summative assessments provide data to evaluate the effectiveness of schools, teachers, and educational policies, contributing to a robust accountability system worldwide. However, educators and scholars argue that summative assessments do not effectively promote ongoing learning, enhance teaching practices, or align with the skills required in the…

PREPARE, implemented by High Point University, was a Teacher Quality Partnership grant offering a Master of Education for elementary education, secondary mathematics, and special education (in grant years 2-5). The residency model included a living wage stipend to support time spent earning the accelerated master's degree. The PREPARE impact…

Causal-formative indicators are often used in social science research. To achieve identification in causal-formative indicator modeling, constraints need to be applied. A conventional method is to constrain the weight of a formative indicator to be 1. The selection of which indicator to have the fixed weight, however, may influence statistical…

Platform-enabled research services will control, manage, and measure learner experiences within that platform. In this paper, we consider the need for research services that examine learner experiences "outside" the platform. For example, we describe an effort to conduct an experiment on peer assessment in a college writing course, where…

Regression discontinuity (RD) designs are increasingly used for causal evaluations. For example, if a student's need for a literacy intervention is determined by a low score on a past performance indicator and that intervention is provided to all students who fall below a cutoff on that indicator, an RD study can determine the intervention's main…

Lottery-based identification strategies offer potential for generating the next generation of evidence on U.S. early education programs. The authors' collaborative network of five research teams applying this design in early education settings and methods experts has identified six challenges that need to be carefully considered in this next…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit with panel data. Two challenges arise with higher frequency data (e.g., monthly versus yearly): (1) achieving excellent pre-treatment fit is typically more challenging; and (2) overfitting to noise is more likely. Aggregating data…

Assessing students' answers and in particular natural language answers is a crucial challenge in the field of education. Advances in transformer-based models such as Large Language Models (LLMs), have led to significant progress in various natural language tasks. Nevertheless, amidst the growing trend of evaluating LLMs across diverse tasks,…

Replication provides a confrontation of psychological theory, not only in experimental research, but also in model-based research. Goodness-of-fit (GOF) of the original model to the replication data is routinely provided as meaningful evidence of replication. We demonstrate, however, that GOF obscures important differences between the original and…

Teachers play a critical role in deciding what curricula are used in their classrooms. We examine the factors that teachers describe influencing their sustainment or discontinuation of a literacy curriculum, "Zoology One," following their participation in a randomized controlled trial (RCT) examining the curriculum's efficacy. This study…

Accurate item parameters and standard errors (SEs) are crucial for many multidimensional item response theory (MIRT) applications. A recent study proposed the Gaussian Variational Expectation Maximization (GVEM) algorithm to improve computational efficiency and estimation accuracy (Cho et al., 2021). However, the SE estimation procedure has yet to…

The education sector has been quick to recognize the power of predictive analytics to enhance student success rates. However, there are challenges to widespread adoption, including the lack of accessibility and the potential perpetuation of inequalities. These challenges present in different stages of modeling, including data preparation, model…

This paper introduces REFLECTSUMM, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of REFLECTSUMM is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, with potential implications in the opinion summarization…

Dynamic structural equation modeling (DSEM) is a useful technique for analyzing intensive longitudinal data. A challenge of applying DSEM is the missing data problem. The impact of missing data on DSEM, especially on widely applied DSEM such as the two-level vector autoregressive (VAR) cross-lagged models, however, is understudied. To fill the…