Value-Added Models (VAMs) are both common and controversial in education policy and accountability research. While the sensitivity of VAMs to model specification and covariate selection is well documented, the extent to which test scoring methods (e.g., mean scores vs. IRT-based scores) may affect VA estimates is less studied. We examine the…

As a key motivational factor that determines future teaching success with Computational Thinking (CT), in this cross-sectional survey study, we investigated if and how preservice teachers' (n = 76) self-efficacy for CT teaching, their usage of CT tools, and their motivation (utility value) were (inter)related. Through a series of regression…

The number of years to estimate value-added measures (VAM) has received insufficient attention. Researchers often use as many years as available, to increase precision and decrease transitory sorting bias. However, this decision has little theoretical or empirical backing. We develop a theoretical framework and evaluate data from thousands of…

This paper proposes a new methodology for estimating teacher value-added. Rather than imposing a normality assumption on unobserved teacher quality (as in the standard empirical Bayes approach), our nonparametric estimator permits the underlying distribution to be estimated directly and in a computationally feasible way. The resulting estimates…

Inappropriate treatment of missing data may introduce bias into the value-added estimation. We consider a commonly used value-added model (VAM), which includes the past student test score as a covariate. We formulate a joint model of student achievement and missing data, in which the probability of observing a test score depends on observing the…

Many education policy strategy documents at the European Union level, as well as national strategies of various countries, recommend including computational thinking as a fundamental skill in curricula. The professional development of teachers should be supported to disseminate computational thinking in K12 education. Teachers' value beliefs about…

When the COVID-19 pandemic hit the U.S. last spring, schools nationwide shut their doors and states cancelled annual standardized tests. Now federal and state policymakers are debating whether to cancel testing again in 2021. One factor they should consider is whether a two-year gap in testing will make it impossible to measure student-level…

We evaluate the feasibility of estimating test-score growth with a gap year in testing data, informing the scenario when state testing resumes after the 2020 COVID-19-induced test stoppage. Our research design is to simulate a gap year in testing using pre-COVID-19 data--when a true test gap did not occur--which facilitates comparisons of…

At least sixteen US states have taken steps toward holding teacher preparation programs (TPPs) accountable for teacher value-added to student test scores. Yet it is unclear whether teacher quality differences between TPPs are large enough to make an accountability system worthwhile. Several statistical practices can make differences between TPPs…

As a result of COVID-19, various forms of education and teaching are moving online. However, the notion of an online STEM camp is still in its beginnings, and there is little relevant research and experience in this context. At the beginning of April 2021, the research team launched an online STEM charity camp with the theme of "Shen Nong…

Developing computational thinking (CT) skills at an early age can help develop literacy, science, and mathematics skills; however, CT instruction in grades K-2 remains limited. This study examined the perceptions of 45 K-2 teachers from 30 school districts before and after a CT professional development (PD) experience. The PD included two online…

Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for…

By aggregating residual gain scores (the differences between each student's current score and a predicted score based on prior performance) for a school or a teacher, value-added models (VAMs) can be used to generate estimates of school or teacher effects. It is known that random errors in the prior scores will introduce bias into predictions of…

Contemporary teacher evaluation systems are built upon multiple measures including, primarily, teacher-level value-added and observational estimates. While researchers have conducted examinations of these systems and indicators, researchers have not investigated how using these systems might distort the validity of the inferences being drawn,…

Contribution: Knowledge of students' Habits of Mind in a signal processing course, and a method for education research. The method identifies factors that may influence students' performance, but are not evident when analyzing agglomerated data; it is an alternative to the traditional case study method as it derives the cases after applying a…