Background: As the body of scientific evidence about what works in education grows, so does the need to effectively communicate that evidence to policy-makers and practitioners. Websites and clearinghouses such as the "What Works Clearinghouse" (WWC), "Evidence for ESSA," "Blueprints for Healthy Youth Development,"…

Background: Traditional survey efforts to gather outcome data at scale have significant limitations, including cost, time, and respondent burden. This pilot study explored new and innovative large-scale methods of collecting and validating data from publicly available sources. Taking advantage of emerging data science techniques, we leverage…

Background: The data revolution in education has led to more data collection, more randomized controlled trials (RCTs), and more data collection within RCTs. Often following IES recommendations, researchers studying program effectiveness gather data on how the intervention was implemented. Educational implementation data can be complex, including…

Background/Context: Application Programming Interfaces (APIs) are becoming a core means to collect and disseminate data for education research and policy. Surveys can be costly, slow, and burden respondents, and manually downloading data files is slow and cumbersome when many files are needed. APIs provide a programmatic way to collect data or…

Why we need better reports of teacher professional development interventions for finding out what works where: Worldwide, billions of dollars are invested yearly in the professional development of in-service teachers ($14 billion in the USA alone, as of 2014; Bill & Melinda Gates Foundation, 2014). This makes the question of what effects TPD…

Research Context: In educational research, "context effects" are often of inferential interest to researchers as well as of evaluative interest to policymakers. While student education outcomes likely depend on individual-level influences like individual academic achievement, school contexts may also make a difference. Such questions are…

Introduction: Planned missing designs are relatively new to the field of psychological and developmental research. These designs allow researchers to randomly assign participants to missing data conditions; participants are either randomly selected to receive or not receive particular measures or items during data collection (Little &…

Introduction: The proposed poster will describe the observational data collection methodology and preliminary findings from a large-scale efficacy study examining a corequisite mathematics intervention at the community college level. Specifically, the larger study is conducting a randomized controlled trial of the Carnegie Math Pathways (CMP)…

To date, evaluation research and policy analysis have focused mainly on average program impacts and paid little systematic attention to their variation. Recently, the growing number of multi-site randomized trials that are being planned and conducted make it increasingly feasible to study "cross-site" variation in impacts. Important…

The concept of "implementation fidelity" is broadly used to capture the extent to which an intervention is executed as intended by the designers of the intervention (Century, Rudnick, & Freeman, 2010; Huntley, 2005, McNaught, Tarr, & Sears, 2010, Munter, 2010). Though implementation fidelity instruments are often used to assess…

In this paper, the authors explore the use of learning analytics as a method for easing the cognitive demands on teachers implementing the HALF instructional model. Learning analytics has been defined as "the measurement, collection, analysis and reporting of data about learners and their contexts for the purposes of understanding and…

Educators have long used test scores to make educational decisions, but only within the last decade has the availability of data been systematic (Abelman, Elmore, Even, Kenyon, & Marshall, 1999). In recent years, interest has spiked in data-driven decision making in education (Marsh, Pane, & Hamilton, 2006). With technological advances and…

The authors present work towards automatically assessing data collection behaviors as middle school students engage in inquiry within a physics microworld. In this study, the authors used machine learned models that can detect when students test their articulated hypotheses, design controlled experiments, and engage in planning behaviors using…

In Djibouti, extreme poverty was 41.9% and relative poverty 79.4% according to the poverty profile elaborated by the national statistical office (DISED) in 2012. Malnutrition remains high in Djibouti, and comparable to Sub-Saharan countries, with 29.7% of children under the age of five chronically malnourished, 29.6% underweight, and over 17.8% of…

This paper illustrates how information collected through interviews can develop a richer understanding of the assignment mechanism, which can result in more plausible causal effect estimates from observational studies and provides a roadmap for sensitivity analysis. Focusing on the issue of assignment to algebra in 8th grade, the author shows how…