Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…

Item-level fit analysis not only serves as a complementary check to global fit analysis, it is also essential in scale development because the fit results will guide item revision and/or deletion (Liu & Maydeu-Olivares, 2014). During data collection, missing response data may likely happen due to various reasons. Chi-square-based item fit…

The fit of an item response model is typically conceptualized as whether a given model could have generated the data. We advocate for an alternative view of fit, "predictive fit", based on the model's ability to predict new data. We derive two predictive fit metrics for item response models that assess how well an estimated item response…

Text comprehension is an essential skill in today's information-rich world, and self-explanation practice helps students improve their understanding of complex texts. This study was centered on leveraging open-source Large Language Models (LLMs), specifically FLAN-T5, to automatically assess the comprehension strategies employed by readers while…

The importance of improving teachers' use of culturally responsive practice (CRP) in the classroom setting has been widely recognized. Although quantitative data on teachers' use of CRP has potential to be a helpful decision-making tool in advancing that goal, little is known about the psychometrics of classroom-based CRP measures, their utility…

Processes of classroom emotional transmission have been identified whereby the emotions expressed by an individual are induced in others, with particular attention paid to how this unfolds among teachers and their students. However, there is still much to be clarified about how teachers' and students' emotions transmit in the classroom, including…

Computerized assessments and digital games have become more prevalent in childhood, necessitating a systematic investigation of the effects of gamified executive function assessments on performance and engagement. This study examined the feasibility of incorporating gamification and a machine learning algorithm that adapts task difficulty to…

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…

Academics are not immune to the biases contributing to persistent inequalities in society. We face an urgent need to overhaul and dismantle current evaluation practices that uphold inequities at multiple points along the academic pipeline. Graduate admissions and faculty advancement are two arenas of gatekeeping in which a reimagining and…

The synthetic control method (SCM) is a popular approach for estimating the impact of a treatment on a single unit in panel data settings. The "synthetic control" is a weighted average of control units that balances the treated unit's pre-treatment outcomes and other covariates as closely as possible. A critical feature of the original…

Automated writing evaluation (AWE) tools can facilitate teachers' analysis of and feedback on students' writing. However, increasing evidence indicates that writing instructors experience challenges in implementing AWE tools successfully. For this reason, our development of the Writing Analytics Tool (WAT) has employed a participatory approach…

In this study, we compared the results of 27 special education teachers' evaluations using two different observation instruments, the Framework for Teaching (FFT), and the Explicit Instruction observation protocol of the Recognizing Effective Special Education Teachers (RESET) observation system. Results indicate differences in the rank-ordering…

Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof. Model estimation is complicated by the fact that we typically have multiple interdependent response variables and multiple latent variables (which may also be called random effects or…

Staggered adoption of policies by different units at different times creates promising opportunities for observational causal inference. Estimation remains challenging, however, and common regression methods can give misleading results. A promising alternative is the synthetic control method (SCM), which finds a weighted average of control units…

Mediation analysis plays an important role in understanding causal processes in social and behavioral sciences. While path analysis with composite scores was criticized to yield biased parameter estimates when variables contain measurement errors, recent literature has pointed out that the population values of parameters of latent-variable models…