SEERNet digital learning platforms (DLPs) are developing new infrastructure to support research in authentic contexts where student learning is happening. In order to contextualize this work within the larger field, we trace historical precedents along four main categories: data repositories, data collection services, research design interfaces,…

Systems for learning and producing knowledge, such as career and technical education (CTE), often reproduce inequities unless an equity-focused lens is used when designing, implementing, and evaluating programs. This framework presents guidance for conducting CTE research with an intentional focus on equity. Developed by the CTE Research Network's…

For the last one decade, research in self-regulated learning (SRL) and educational psychology has proliferated. Researchers and educators have focused on how to support leaners grow their SRL skills on both face-to-face and e-learning environments. In addition, recent studies and meta-analysis have greatly contributed to the domain knowledge on…

This dissertation is composed of projects on three aspects of gathering and learning from data in the social sciences: drawing representative samples, taking valid measurement, and making warranted inductive inferences. Chapter one studies the challenge of drawing representative human samples. It is well documented that most samples used by…

This AERA Open special topic concerns the large emerging research area of education data science (EDS). In a narrow sense, EDS applies statistics and computational techniques to educational phenomena and questions. In a broader sense, it is an umbrella for a fleet of new computational techniques being used to identify new forms of data, measures,…

For the past two decades, educational intervention research has rallied around the common goal of determining "what works in education" to inform education practice and policy (U.S. Department of Education, 2017). To study individual, contextual, and implementation processes and their interaction with educational interventions requires…

Across all sciences, the quality of measurements is important. Survey measurements are only appropriate for use when researchers have validity evidence within their particular context. Yet, this step is frequently skipped or is not reported in educational research. This article briefly reviews the aspects of validity that researchers should…

The arc of quantitative educational research should not be etched in stone but should adapt and change over time. In this article, I argue that it is time for a reshaping by offering my personal view of the past, present and future of our field. Educational research--and research in the social and life sciences--is at a crossroads. There are many…

This paper argues that methods used for the classification and measurement of online education are not neutral and objective, but involved in the creation of the educational realities they claim to measure. In particular, the paper draws on material semiotics to examine cluster analysis as a 'performative device' that, to a significant extent,…

This article describes issues in measuring school contexts with an eye toward understanding students' experiences and outcomes. I begin with an overview of the conceptual underpinnings related to measuring contexts, briefly describe the initiatives at the National Center for Education Statistics to measure school contexts, and identify possible…

Response-to-intervention (RTI) systems posit that Tier 1 consists of high-quality general classroom instruction using evidence-based methods to address the needs of most students. However, data on the extent to which general education teachers provide such instruction are rarely collected. This missing instructional data problem may result in RTI…

In this article, we argue that big data can offer new opportunities and roles for educational researchers. In the traditional model of evidence-gathering and interpretation in education, researchers are independent observers, who pre-emptively create instruments of measurement, and insert these into the educational process in specialized times and…

New high-frequency multimodal data collection technologies and machine learning analysis techniques could offer new insights into learning, especially when students have the opportunity to generate unique, personalized artifacts, such as computer programs, robots, and solutions engineering challenges. To date most of the work on learning analytics…

Background: Schools are an ideal setting in which to involve children in research. Yet for investigators wishing to work in these settings, there are few method papers providing insights into working efficiently in this setting. Objective: The aim of this paper is to describe the five strategies used to increase response rates, data quality and…

This substantially revised text provides a comprehensive, highly accessible, and student friendly introduction to the principles, concepts, and methods currently used in educational research. This text provides a balanced combination of quantitative and qualitative methods and enables students to master skills in reading, understanding,…