Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…

Composite scores are an exceptionally important psychometric tool for behavioral science research applications. A prototypical example occurs with self-report data, where researchers routinely use questionnaires with multiple items that tap into different features of a target construct. Item-level missing data are endemic to composite score…

The novel coronavirus disease 2019 (COVID-19) pandemic has created an unprecedented set of obstacles for schools and exacerbated existing structural inequalities in public education. In spring 2020, as schools went to remote learning formats or closed completely, end-of-year assessment programs ground to a halt. As a result, schools began the…

The year 2022 is the 20th anniversary of Joseph Schafer and John Graham's paper titled "Missing data: Our view of the state of the art," currently the most highly cited paper in the history of "Psychological Methods." Much has changed since 2002, as missing data methodologies have continually evolved and improved; the range of…

Clients display considerable variations in functioning across the contexts that encompass their social environments (e.g., home, school/workplace, peer interactions). No single measurement method can fully capture these variations. Yet, assessors must balance the need to accurately capture clients' clinical presentations, and at the same time…

States often turn to a data masking procedure called microsuppression in order to reduce the risk of disclosing student records when sharing data with external researchers. This process removes records deemed to have high risk for disclosure should data be released. However, this process can induce differences between the original data and the…

The Learning Target Rating Scale (LTRS) is a measure designed to evaluate the quality of teacher-developed learning targets for embedded instruction for early learning. In the present study, we examined the measurement dependability of LTRS scores by conducting a generalizability study (G-study). We used a partially nested, three-facet model to…

This study investigates a possible way to analyze chat data from collaborative learning environments using epistemic network analysis and topic modeling. A 300-topic general topic model built from TASA (Touchstone Applied Science Associates) corpus was used in this study. 300 topic scores for each of the 15,670 utterances in our chat data were…

Ho and Reardon (2012) present methods for estimating achievement gaps when test scores are coarsened into a small number of ordered categories, preventing fine-grained distinctions between individual scores. They demonstrate that gaps can nonetheless be estimated with minimal bias across a broad range of simulated and real coarsened data…

Research suggests that the academic achievement of deaf and hard-of-hearing (DHH) students is the result of a complex interplay of many factors. These factors include characteristics of the students (e.g., hearing thresholds, language fluencies, mode of communication, and communication functioning), characteristics of their family environments…

Through comparative case study, we seek to understand the ways in which actors in high schools use and think about performance data. In particular, we compare data use in higher and lower value-added schools. Data use is conceptualized here as having access to a host of available performance data on students, using them to guide instructional…

This is the final external evaluation report prepared by SRI International for the Rural Math Excel Partnership (RMEP) project, an investing in innovation (i3) development project funded by the U.S. Department of Education. Operated by Virginia Advanced Study Strategies, Inc. (VASS), the RMEP project included six rural school districts (LEAs) in…