With increased focus on data literacy and data science education in K-12, little is known about what makes a data set preferable for use by classroom teachers. Given that educational designers often privilege authenticity, the purpose of this study is to examine how teachers use features of data sets to determine their suitability for authentic…

To support and better understand how to scale effectively, in 2020, the Millions Learning project at the Center for Universal Education (CUE) at Brookings joined the Global Partnership for Education's (GPE) Knowledge and Innovation Exchange (KIX), a joint partnership between GPE and the International Development Research Centre (IDRC), to…

This study conducted a systematic literature review of articles on learning analytics published between 2004 and January 2024. A total of 1,064 articles, identified using the keyword "learning analytic*" in the Scopus database, were analyzed. The study integrated systematic literature review and bibliometric analysis approaches to…

Purpose: As one of the buzzwords in the present age with considerable impacts in tertiary institutions, social media use in online teaching, learning and information dissemination have been extensively discussed in extant literature. This paper aims to explore the existing campus sustainability appraisal (CSA) tools to identify the length at which…

With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

This paper adds an algorithmic epistemology perspective to previous works that examine the datafication of subjective social and emotional characteristics, perceptions, and behaviours. The paper employs a comparative epistemological approach to explore two behavioural educational platforms: RedCritter Teacher and Panorama Education. We unpack…

Purpose: The goal of this study is to explore how content creators engage in critical data literacies on TikTok, a social media site that encourages the creation and dissemination of user-created, short-form videos. Critical data literacies encompass the ability to reason with, critique, control, and repurpose data for creative uses. Existing work…

This paper describes the role of data and task context in young children's interpretation of and reasoning about data tables. A design-based descriptive study was conducted with fourteen 5-year-old children in their first year of formal schooling. A picture storybook provided the data context for a data modelling activity that focused on…

Adaptive teachers use student data to guide instruction. Learn about using an anecdotal record form to support adaptive teaching. In this article, the authors describe how teachers can use learning trajectories to make adaptive decisions to meet the needs of their students. They provide an example using the U .S. Math Recovery Council's learning…

In the context of digital transformation processes in schools, the introduction of technology is often discussed in terms of the individualization and optimization of teaching, learning and school management. However, it is often neglected that technologies are preconfigured and provide socio-material offers that invite certain actions and thus…

Early Warning Systems (EWS) are research-based analytics that use statistical models to assess dropout risk. School leaders use this analytic to consolidate data about a student and provide actionable data to craft an intervention. Little is currently known about the processes involved in school implementation or data use. By analyzing Montana EWS…

Educator labor markets vary considerably across the country and can change quickly during recessions. We use data from the Quality Workforce Indicators (QWI) on educators in Elementary and Secondary Schools from 2000-01 to 2022-23. We demonstrate how to transform the quarter-level data in the QWI to construct valid educator labor market measures.…

High-volume, high-quality and diverse datasets are crucial for advancing research in the education field. However, such datasets often contain sensitive information that poses significant privacy challenges. Traditional anonymisation techniques fail to meet the privacy standards required by regulations like GDPR, prompting the need for more robust…

The Center for Data Insights at MDRC has partnered with organizations to develop and execute a variety of data projects, some with long-standing partners that have participated in MDRC's long-term evaluations; others with newer partners that are just beginning to use data for program improvement. Important lessons about the essential ingredients…

Learners' satisfaction with Massive Open Online Courses (MOOCs) has been evaluated through quantitative approaches focusing on survey-based methods in several studies. User-Generated Content (UGC) has been an effective approach to assess users' interactions with e-learning systems. Other than survey-based methods, the UGC generated from MOOCs…