This paper presents a game-design workshop built around a digital art installation featuring video games displayed over a real-world skyscraper to stimulate students' interest in computer science and a study testing its short-term effects on improving middle school students' computational thinking (CT) skills and attitudes towards computing.…

Student attendance is both a critical input and intermediate output of the education production function. However, the malleable classroom-level determinants of student attendance are poorly understood. We estimate the causal effect of class size, class composition, and observable teacher qualifications on student attendance by leveraging the…

There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…

Despite the importance of retirement savings, many individuals retire with lack of adequate retirement savings. While calculating retirement savings needs was found to enhance retirement savings, little is known about what underlies this enhancement. Applying the theory of planned behavior (TPB), we developed a model in which psychological factors…

Research Findings: The aim of this study was to investigate U.S. preschool teachers' math teaching knowledge in a specific content domain: counting and numbers. One hundred in-service and pre-service teachers participated in the study; they completed a questionnaire that is composed of learning scenarios and scenario-based math teaching questions.…

The notion of algorithm may be perceived in different levels of abstraction. In the lower levels it is an operational set of instructions. In higher levels it may be viewed as an object with properties, solving a problem with characteristics. Novices mostly relate to the lower levels. Yet, higher levels are very relevant for them as well. We…

This study examined the effectiveness of STEAM (Science, Technology, Engineering, Art, Mathematics) integrated approach via Scratch on five subconstructs of computational thinking (CT) among 29 male and 30 female students. A quasi-experimental design was employed in the research. The participants demonstrated the application of CT in designing…

Background and Context: While assessment of computational thinking concepts, practices, and perspectives is at the forefront of K-12 CS education, supporting student "communication about computation" has received relatively little attention. Objective: To examine the usability of process-based portfolios for capturing students'…

The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…

This article explains the process behind estimating a National Education Cost Model (NECM) and generating from that model projections of per-pupil costs to achieve 2016 national average outcomes (reading and math grades 3 to 8) across all districts in the United States, from 2019-20 to 2020-21. This article is a follow-up to a preliminary report…

Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…

Educational data mining focuses on exploring increasingly large-scale data from educational settings, such as Learning Management Systems (LMS), and developing computational methods to understand students' behaviors and learning settings better. There has been a multitude of research dedicated to studying the student learning process, leading to…

By the time they reach early adulthood, English speakers are familiar with the meaning of thousands of words. In the last decades, computational simulations known as distributional semantic models (DSMs) have demonstrated that it is possible to induce word meaning representations solely from word co-occurrence statistics extracted from a large…

Operational validities are important to personnel selection research because they estimate how well a predictor in practical use correlates with a criterion construct, if the criterion measure were purged of measurement error variance. Because range restriction on a predictor or predictor composite creates incidental range restriction on the…

In order to investigate causality in situations where random assignment is not possible, propensity scores can be used in regression adjustment, stratification, inverse-probability treatment weighting, or matching. The basic concepts behind propensity scores have been extensively described. When data are longitudinal or missing, the estimation and…