Drawing on a community-university (CU) partnership between a non-profit organization that serves teen families, a housing organization and a university, this paper discusses the opportunities and challenges that can arise when engaging vulnerable youth in research. Through this paper, we share reflections on promising practices and ethical…

Seamless learning has been recognized as an effective learning approach across various dimensions including formal and informal learning contexts, individual and social learning, and physical world and cyberspace. With the emergence of seamless learning, the majority of the current research focuses on realizing a seamless learning environment at…

The recommendations in this brief create a framework for using data effectively to make instructional decisions. The availability of student-level data for educators has pushed forward the movement to strengthen the role of data to guide instruction and improve student learning. While improvements in technology and assessments, as well as recent…

Over the past decade, chronic absence has gone from being a virtually unknown concept to a national education metric that provides every school in the nation with critical data on how many students are missing so many days of school it jeopardizes their academic success. The inclusion of chronic absence in the Every Student Succeeds Act (ESSA) was…

Accountability seems forever engrained into the K-12 environment, as has been the expectation of delivering quality education to school aged children and adolescents. Yet, repeated failure of this expectation has focused the public's and policy maker's attention on the limitations of major accountability systems. This paper explores applications…

The "Annual Disability Statistics Supplement" is a companion report to the "Annual Disability Statistics Compendium." The "Supplement" presents statistics on the same topics as the "Compendium," with additional categorizations by demographic characteristics including age, gender and race/ethnicity. In…

Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…

A Massive Open Online Course (MOOC) is a course that is offered fully online and is usually open for enrollment by any individual, with no limit on the number of participants. MOOCs are a popular resource for learning worldwide with over 23 million new learners registering for MOOCs in 2017 alone. Coursera, the most popular MOOC platform, has…

Data is a crucial component in educational success. It gives educators the power to address student needs, study what strategies work, and make necessary changes so that every student has the greatest opportunity. Today, educators, parents, and students have access to more data than ever before and have access to more technology tools to…

Many states are building systems and structures to integrate their early care and education data. Combining data from different programs and agencies that serve young children allows policymakers and program decision makers to better answer critical questions about the needs of families in their communities, as well as questions about services and…

We describe a semester-long project for an introductory statistics class that studies the broken windows theory of policing and the related issues of race, policing, and criminal justice. The most impactful feature of the project is the data-collection phase, in which students attend and observe a public arraignment court session. This "Court…

Determining which students are at risk of poorer outcomes -- such as dropping out, failing classes, or decreasing standardized examination scores -- has become an important area of research and practice in both K-12 and higher education. The detectors produced from this type of predictive modeling research are increasingly used in early warning…

Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…

Applying Herzberg's motivation-hygiene theory, we studied the determinants of student satisfaction in using R in a Decision Support Systems course that previously used Excel to teach Data Mining and Business Analytics (DMBA). The course is a degree requirement, and prior programming experience is not a prerequisite. We hypothesized that motivators…

The impact of the COVID-19 pandemic on the higher education sector has been overwhelming, with emergency responses that have affected decision-making processes. Yet, our understanding of higher education instructors' perspectives regarding the process of data-driven decisions, especially in times of emergency, is still limited. We aimed at…