The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

The rapid development of education informatization has accumulated a large amount of data for learning analytics, and adopting educational data mining to find new patterns of data, develop new algorithms and models, and apply known predictive models to the teaching system to improve learning is the challenge and vision of the education field in…

Purpose: Drawing from the equitable education fund (EEF) launching 6Qs innovation in the teacher school quality program (TSQP) for small and medium schools, this research aims to analyze the effect size of the ordinary national educational test (O-NET) scores between TSQP schools that implement 6Qs innovation and non-TSQP schools and explain the…

Multidimensional item response theory (MIRT) models have generated increasing interest in the psychometrics literature. Efficient approaches for estimating MIRT models with dichotomous responses have been developed, but constructing an equally efficient and robust algorithm for polytomous models has received limited attention. To address this gap,…

In this work we introduce the system for adaptive practice of foundations of mathematics. Adaptivity of the system is primarily provided by selection of suitable tasks, which uses information from a domain model and a student model. The domain model does not use prerequisites but works with splitting skills to more concrete sub-skills. The student…

Knowledge tracing is a fundamental area of educational data modeling that aims at gaining a better understanding of the learning occurring in tutoring systems. Knowledge tracing models fit various parameters on observed student performance and are evaluated through several goodness of fit metrics. Fitted parameter values are of crucial interest in…

Due to poor student success rates in developmental mathematics, many institutions have implemented various forms of redesign into their developmental math curricula. Since the goal of redesign is to increase student success, it is salient to explore all aspects of the redesign process. Many studies have focused on the positive outcomes of redesign…

The purpose of this study is to evaluate the implementation and impacts of the Building Assets, Reducing Risks (BARR) model in its first year of implementation in 66 schools across the U.S. and to document scale-up progress during the Investing in Innovation (i3) grant period (2017-2021). The impact evaluation included 21,529 9th grade students…

This three-article dissertation considers the pedagogical practices for developing statistically literate students and teaching data-driven decision-making with the goal of preparing students for civic engagement and improving student achievement. The first article discusses a critical review of the literature on data-driven decision-making…

Data mining has been successfully used by financial and retail companies since the mid-1960's to create predictive models and reveal unexpected relationships. However, it remains underutilized as a tool in educational research. Large-scale standardized assessment programs such as the Trends in International Mathematics and Science Study (TIMSS)…

This study compared the direct, indirect, and total effects of information, communication, and technology (ICT) variables on math achievement for second-generation immigrant, first-generation immigrant, and nonimmigrant students. A path model was used to analyze U.S. nationally representative data from the Program for International Student…

Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…

Does data use make a difference in student achievement? Despite the field's optimism on this matter, relatively few studies have attempted to quantify the effects of data use. These studies have often used the presence of a data use intervention (e.g., a data system or data coaching) as a proxy for use, as opposed to tracking teachers' direct…

There are relatively few studies in Australia and South-East Asian region that combine investigating models of math growth trajectories with predictors such as reasoning ability and reading comprehension skills. Math achievement is one of the major components of overall academic achievement and it is important to determine what factors (especially…