The proliferation of sports science and technological innovation within performance settings has precipitated the generation of increasing volumes of data to aid athletes. Copious data production has also perpetuated the privileging of scientific information, and a 'thirst' for 'more data' as an unproblematic 'truth'. Of significance is not merely…

Digital data are transforming higher education (HE) to be more student-focused and metrics-centred. In the UK, capturing detailed data about students has become a government priority, with an emphasis on using student data to measure, compare and assess university performance. The purpose of this paper is to examine the governmental and commercial…

To successfully reduce student attrition, it is imperative to understand what the underlying determinants of attrition are and which students are at risk of dropping out. We develop an early detection system (EDS) using administrative student data from a state and private university to predict student dropout as a basis for a targeted…

This systematic review is built on the seminal work by the New London Group in 1996. Few endeavours have synthesized findings of empirical studies pertaining to the effects and challenges of multiliteracies practices in various schooling and geographical contexts. Through a five-point Likert scale and a deductive and inductive thematic analysis,…

A core feature of Positive Behavioral Interventions and Supports (PBIS) is the collection, summary, and use of data for iterative decision-making. The initial design of support and the adaptations that make behavior support match cultural, organizational, and personal needs require that a support team have functional information to guide…

Accurate, timely data on student outcomes and post-graduate earnings is a critical piece of any state effort to close equity gaps in college access and success, boost attainment statewide, and strategically align education and workforce goals. Unfortunately, in the absence of a federal student-level data network, states and other key stakeholders…

Evaluation capacity building (ECB) is an essential element for generating credible and actionable evidence on Extension programs. This paper offers a discussion of ECB efforts in Cooperative Extension and how such efforts enable Extension professionals to collect and use credible and actionable evidence on the quality and impacts of programs.…

In this chapter, we walk the reader through a set of scenarios that administrators might face when using different types of data on campus. We also provide guiding questions to help institutional research professionals explore how to think about these scenarios with ethics in mind.

Meta-analysis and structural equation modeling (SEM) are 2 of the most prominent statistical techniques employed in the behavioral, medical, and social sciences. They each have their own well-established research communities, terminologies, statistical models, software packages, and journals ("Research Synthesis Methods" and…

Most recent research on teacher evaluation examines evaluation's measurement properties and accountability uses. Less research studies how evaluation data can improve teaching and student learning. In other contexts, researchers have examined how teachers use data to improve their practice. From general research on teachers' data use, we apply the…

In order to demonstrate the value of higher education and evaluate the effectiveness of various policies and practices, researchers are increasingly expected to merge data from the Integrated Postsecondary Education Data System (IPEDS) with a range of other federal and private-sector data sources. In this article, I detail a number of the most…

Online platforms offer new opportunities to study human behavior. However, while social scientists are often interested in using behavioral trace data--data created by a user over the course of their everyday life--to draw inferences about users, many online platforms only allow data to be sampled based on user activities (leading to data sets…

In this ITEMS module, we provide a didactic overview of the specification, estimation, evaluation, and interpretation steps for diagnostic measurement/classification models (DCMs), which are a promising psychometric modeling approach. These models can provide detailed skill- or attribute-specific feedback to respondents along multiple latent…

There is clear scientific evidence linking climate change to human activity. Despite this, we still find numerous public figures claiming there is no climate change, or that climate change data is "fake news." Societal polarization around climate change (Worland 2017; Pernett 2017; McCright and Dunlap 2011) can provide students with…

When practitioners use modern measurement models to evaluate rating quality, they commonly examine rater fit statistics that summarize how well each rater's ratings fit the expectations of the measurement model. Essentially, this approach involves examining the unexpected ratings that each misfitting rater assigned (i.e., carrying out analyses of…