The emerging field of Data Science has had a large impact on science and society. This has led to over a decade of calls to establish a corresponding field of Data Science Education. There is still a need, however, to more deeply conceptualize what a field of Data Science Education might entail in terms of scope, responsibility, and execution.…

We present a model for sharing quantitative data in the field of physics education research and use it to present a newly available dataset as an example. This model is in line with calls from across physics and science more generally to democratize data and results through open access. The model includes suggestions for data collection, creation…

When the COVID-19 pandemic drove schools online in March 2020, state education leaders were left without access to data needed to understand how best to support students. The pandemic revealed the strengths and limitations of state education data systems while inspiring new strategies for collecting, reporting and using data. In 2021, DataSmith…

The Education Insights Center produced a series of reports culminating in recommendations for the structure and governance of a preschool through higher education and into the workforce (known as a P20W data system). This brief follows up on that series, with a focus on data quality; the brief was informed by the author's experience using…

There is an urgent need to develop an evidence-based framework for learning analytics whereby stakeholders can manage, evaluate, and make decisions about which types of interventions work well and under which conditions. In this article, we will work towards developing a foundation of an Analytics4Action Evaluation Framework (A4AEF) that is…

Data-informed instructional methods offer tremendous promise for increasing the effectiveness of teaching, learning, and schooling. Yet-to-be-developed data science approaches have the potential to dramatically advance instruction for every student and to enhance learning for people of all ages. Next steps that emerged from a recent National…

Learning technologies are now commonplace in education, and generate large volumes of educational data. Scholars have argued that analytics can and should be employed to optimize learning and learning environments. This article explores what is really meant by "analytics", describes the current best-known examples of institutional…

This paper details the anticipated impact of synthetic "big" data on learning analytics (LA) infrastructures, with a particular focus on data governance, the acceleration of service development, and the benchmarking of predictive models. By reviewing two cases, one at the sector-wide level (the Jisc learning analytics architecture) and…

This article introduces the special issue from the 2015 Learning Analytics and Knowledge conference. We describe the current state of the field and identify some of the trends in recent research. As the field continues to expand, there seem to be at least three directions of vigorous growth: (1) the inclusion of multimodal data (gesture,…

Open data sharing promises to accelerate the pace of discovery in the developmental and learning sciences, but significant technical, policy, and cultural barriers have limited its adoption. As a result, most research on learning and development remains shrouded in a culture of isolation. Data sharing is the rare exception (Gilmore, 2016). Many…

According to researchers at the University of Southern California (Washington Post, 2011), the world's storage capacity for digital data increased from 0.2 billion gigabytes in 1986 to 276 billion gigabytes by 2007 (at the same time analogue storage capacity increased from 2.6 to 18.9 billion gigabytes). This huge growth is often seen in…

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…

Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…

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 societal sector perspective looks to a broad array of actors and agencies responsible for creating the community contexts that affect youth learning and development. We demonstrate the efficacy of this perspective by describing the Youth Data Archive, which allows community partners to define issues affecting youth that transcend specific…