Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide,…

Many schools choose to organise students into classes according to their perceived "ability", despite evidence that the practice is not beneficial for students, overall. Class grouping by "ability" can exacerbate existing social inequalities by segregating students according to pre-existing educational advantage, which has…

Missing data can significantly influence results of epidemiological studies. The National Health and Nutrition Examination Survey (NHANES) is a popular epidemiological dataset. We examined recent practices related to the prevalence and the reporting of the amount of missing data, the underlying mechanisms, and the methods used for handling missing…

Meta-analyses can be used to comprehensively summarize the state of a given literature base, understand development and relations between constructs, and synthesize intervention effects to identify "what works for whom," all of which can directly inform research, practice, and policy. In this tutorial, we first argue that data reporting…

Digitally-based assessments create opportunities for collecting moment to moment information about how students are responding to assessment items. This information, called log or process data, has long been regarded as a vast and valuable source of data about student performance. Despite repeated assurances of its vastness and value, process data…

Learning analytics promise significant benefit to online education providers through improved, better-targeted student services. Much has been written about the potential of analytics and how they might be technically implemented, and various ethical considerations are published highlighting the significant potential risk of gathering,…

Despite increasing calls to build equitable data infrastructures, the education field has yet to have a shared guideline around equitable education data management and stewardship. To address this gap, we propose one framework from the data governance literature: the FAIR (Findable, Accessible, Interoperable, Reusable) data management principles…

In today's data-driven and data-informed educational landscape, leaders face increasing pressure to make decisions and present results based on what appear to be comprehensive statistical analyses. However, the ethical implications of these responsibilities can be complex, particularly when statistical results carry the potential to be…

Data literacy is the ability to collect, manage, evaluate, and apply data, in a critical manner. It is a relatively new field of study, dating only from the 2010s. It includes the skills necessary to discover and access data, manipulate data, evaluate data quality, conduct analysis using data, interpret results of analyses, and understand the…

These Guidelines and accompanying Toolkit aim to generate a diagnosis of the education in emergencies data ecosystem at a given point in time, mainly by evaluating the opportunities for integrating humanitarian EiE data systems with development and national institutional education information systems. They include approaches and tools for the…

This project reviews data collection practices regarding race, ethnicity and ancestry (REA) in post-secondary institutions (PSIs) in Canada, as well as in other relevant sectors (e.g., health, K-12 education, government agencies). The goal of the project was to identify promising practices and to develop recommendations to guide REA data…

Exploratory data analysis (EDA) is an iterative, open-ended data analysis procedure that allows practitioners to examine data without pre-conceived notions to advise improvement processes and make informed decisions. Education is a data-rich field that is primed for a transition into a deeper, more purposeful use of data. This article introduces…

In early childhood education, ensuring that all students, including those with disabilities, can access and engage with learning materials is a pivotal aspect of educational equity and inclusion. Accessible Educational Materials (AEM) and Assistive Technologies (AT) are central to this endeavor, providing essential resources that accommodate…

A key responsibility of state education agencies (SEAs) under the Individuals with Disabilities Education Act (IDEA) is to monitor local education agency (LEA) implementation of the law (34 C.F.R. § 300.600-604). This Fast Five details five principles (plus one!) that we recommend SEAs incorporate as part of their LEA monitoring.

The need for a comprehensive education data governance -- the regulation of who collects what data, how it is used and why -- continues to grow. Technologically, data can be collected by third parties, rendering schools unable to control their use. Legal frameworks partially achieve data governance as businesses continue to exploit existing…