Students cannot experience the full potential benefits of an intervention unless they are receiving the intervention. This is the second installment in a three-part series on intervention fidelity designed to highlight the importance of ensuring classroom supports are implemented as intended. This article provides guidance related to measuring and…

The Maine Department of Education (MDOE) wanted to better understand if their current educator workforce data collection could help them quantify supply and demand for educators in the state. They also wanted to understand if local school administrative units collected data that could inform future efforts to understand educator vacancies to…

One of the most significant issues in education, as defined by the U.S. Department of Education Office of Accountability (2018), is disproportionality in exclusionary discipline. Disproportionality is defined as the over- and under-representation of racial/ethnic minorities in relation to their overall enrollment (Ahram et al., 2011). Currently,…

It may seem obvious, but learning should never be implied or assumed. Learning must be explicit, evaluated and monitored; the impact of teaching on student learning should be visible. But how can we be sure? Armed with years of research that includes more than 2,100 meta-analyses, and 130,000 studies that include more than 300 million…

A national poll from the Data Quality Campaign (DQC), conducted by The Harris Poll, surveyed early childhood administrators--educational or child care professionals in program director or general manager roles serving children from birth through age four--to find out how they are collecting, using, and reporting data. Early childhood…

In order to better grasp the needs of library users and provide them with more accurate knowledge services, combining the characteristics of university libraries, this article applies library small data to personalized recommendation and proposes a small data fusion algorithm model for library personalized recommendation. This model combines the…

Each year, state legislators introduce hundreds of bills that generate new data collections, analyses, and resources, playing a crucial role in how people access and use data. Notably, in 2023 legislators introduced and enacted bills governing cross-agency data systems--the most important step that states must take to make robust access to data…

Data reflects a series of decisions made by people--and those decisions affect the story that data tells, what it captures, and how it can and should be used to inform decision-making. Because of this, mistrust in data is often the result of incomplete information and a lack of context. This resource breaks down what it means to build trust in…

Evaluation data helps inform decision-makers about the time, human capital, and funding required for professional learning to be effective. Evaluation data also guides program improvement and sets leaders' expectations for ongoing monitoring and accountability. The complexities of the educational systems in which professional learning happens mean…

Government agencies collect vast amounts of administrative data in their day-to-day activities, primarily for program operations. But the information is less often used as a research tool or fully harnessed for its evidence-building potential. This brief is the fourth in a series of publications from MDRC about the Temporary Assistance for Needy…

The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…

Managing and analysing large qualitative datasets pose a particular challenge for researchers seeking a consistent and rigorous approach to qualitative data analysis. This paper describes and demonstrates the development and adoption of a matrix tool to guide the qualitative data analysis of a large sample (N = 122) of interview data. The paper…

As a result of the growing commercial marketplace for teachers' digital data, a new organization that includes educational data brokers has evolved. Educational data brokerage is relatively intangible due to the ease of de-identified data being collected and sold via educational technology. There is an urgent need to expose how the brokerage of…

The present study used quantitative and qualitative measures to examine Iranian applied linguists' (mis-) conceptions of ethical issues in research. For this purpose, one hundred and twelve applied linguists completed a research ethics questionnaire constructed and validated by the researchers. In the follow-up qualitative phase, 15 applied…

The underrepresentation and underperformance of low-income, first-generation, gender minoritized, Black, Latine, and Indigenous students in Science, Technology, Engineering, and Mathematics (STEM) occurs for a variety of reasons, including, that students in these groups experience opportunity gaps in STEM classes. A critical approach to disrupting…