Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

The Federal STEM Education Strategic plan recognizes the importance of building computational literacy today. This document is aligned to the Computational Literacy Interagency Working Group (IWGCL) objectives to: (1) develop a common operational definition; (2) identify existing research on computational literacy; and (3) identify existing…

Background: Stealth assessment is a learning analytics method, which leverages the collection and analysis of learners' interaction data to make real-time inferences about their learning. Employed in digital learning environments, stealth assessment helps researchers, educators, and teachers evaluate learners' competencies and customize the…

Design-based research (DBR) has proven to be a robust methodology for transforming educational practice through a systematic cycle of analysis, design, development, and real-world implementation. Its distinctive strength lies in fostering close collaboration between researchers and educators within authentic learning contexts, producing design…

This report aims to showcase the value of implementing a Bayesian framework to analyse and report results from international large-scale surveys and provide guidance to users who want to analyse the data using this approach. The motivation for this report stems from the recognition that Bayesian statistical inference is fast becoming a popular…

This study examines modelling with machine learning. In the context of a yearlong data science course, the study explores how upper secondary students apply machine learning with Jupyter Notebooks and document the modelling process as a computational essay incorporating the different steps of the CRISP-DM cycle. The students' work is based on a…

American Educational Research Association (AERA) standards stipulate that researchers show evidence of the internal structure of instruments. Confirmatory factor analysis (CFA) is one structural equation modeling procedure designed to assess construct validity of assessments that has broad applicability for counselors interested in instrument…

With the advent of data systems that allow for frequent or even real-time student data updates, and recognition that high school students often can move from being on-track to graduation to off-track in a matter of weeks, indicator analysis alone may not provide a complete picture to guide school leaders' actions. The authors of this paper suggest…

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…

A new design-based theory has recently been developed to estimate impacts for randomized controlled trials (RCTs) and basic quasi-experimental designs (QEDs) for a wide range of designs used in social policy research (Imbens & Rubin, 2015; Schochet, 2016). These methods use the potential outcomes framework and known features of study designs…

Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies (Imbens and Rubin, 2015; Schochet, 2015, 2016). The estimators are derived using the building blocks of experimental designs with minimal assumptions, and are unbiased and normally distributed in large samples…

Missing data is endemic in much educational research. However, practices such as step-wise regression common in the educational research literature have been shown to be dangerous when significant data are missing, and multiple imputation (MI) is generally recommended by statisticians. In this paper, we provide a review of these advances and their…

With widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data--commonly known as trace data--are readily accessible to researchers. Trace data has been extensively used to calculate time that students spend on different learning activities--typically referred to as time-on-task. These measures…

Missing data are a common occurrence in survey-based research studies in education, and the way missing values are handled can significantly affect the results of analyses based on such data. Despite known problems with performance of some missing data handling methods, such as mean imputation, many researchers in education continue to use those…

A large body of research in the learning sciences has focused on students' commonsense science knowledge--the everyday knowledge of the natural world that is gained outside of formal instruction. Although researchers studying commonsense science have employed a variety of methods, 1-on-1 clinical interviews have played a unique role. The data…