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…

We describe the construction and initial demonstration of a new instructional tool called ROXI (Research Opportunity through eXperimental Instruction). The system interfaces a series of electronic sensors to control software via the Arduino platform. The sensors have been designed to enable low-cost data collection in laboratory courses. Data are…

In many evolving systems, inputs can be derived from both human observations and physical sensors. Additionally, many computation and analysis tasks can be performed by either human beings or artificial intelligence (AI) applications. For example, weather prediction, emergency event response, assistive technology for various human sensory and…

Researchers have been making use of ecological momentary assessment (EMA) and other study designs that sample feelings and behaviors in real time and in naturalistic settings to study temporal dynamics and contextual factors of a wide variety of psychological, physiological, and behavioral processes. As EMA designs become more widespread,…

This "What Works Clearinghouse Procedures and Standards Handbook (Version 3.0)" provides a detailed description of the standards and procedures of the What Works Clearinghouse (WWC). The remaining chapters of this Handbook are organized to take the reader through the basic steps that the WWC uses to develop a review protocol, identify…

For the forty-second time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented at the annual AECT Convention in Las Vegas, Nevada. The Proceedings of AECT's Convention are published in two volumes. Volume 1 contains 37 papers dealing…

Education researchers, practitioners, and policymakers alike are committed to identifying interventions that teach students more effectively. Increased emphasis on evaluation and accountability has increased desire for sound evaluations of these interventions; and at the same time, school-level data have become increasingly available. This article…

Hierarchical linear modeling (HIM) is an approach used in data analysis to better understand how program outcomes are affected by the "nested" nature of data collected in many studies. An outcome can be considered variables such as an individual's self-efficacy, social skills, or more targeted outcomes such as demonstrated reading and mathematical…

The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…

The study reported here provides a theoretical and empirical framework for the analysis of employment tax credit policy (a government subsidy or business tax credit to firms who maintain or expand their use of labor). Various programs are examined from the standpoint of structure and implications. The programs are selective employment incentive;…

This document presents the proceedings of the 31st Annual Conference of the Mathematics Education Research Group of Australasia (MERGA). The theme of this conference is "Navigating Currents and Charting Directions." The theme reminds us that, although we are constantly pushed to account for the quality and impact of our research, we…