A technology-based problem-solving test can automatically capture all the actions of students when they complete tasks and save them as process data. Response sequences are the external manifestations of the latent intellectual activities of the students, and it contains rich information about students' abilities and different problem-solving…

Technology and data analysis have evolved into a resource-rich tool for collecting, researching and comparing student achievement levels in the classroom. There are sufficient resources to discover student success through data analysis by routinely collecting extensive data on student behaviour and curriculum structure. Educational Data Mining…

Five years ago, California's education data lagged far behind the systems in most other states. However, state leaders and education advocates undertook a purposeful engagement and design process to build a data system that represents the state's values and meets different stakeholders' needs. This case study on California's P-20W Cradle-to-Career…

Since 2013, DaSy has tracked the status of Part C and Part B 619 state data systems to understand states' technical assistance needs, provide stakeholders with a national picture of what capacities state data systems have, and to track how those capacities are changing over time. Most recently, in spring of 2021, DaSy collected comprehensive…

The emerging field of Data Science has had a large impact on science and society. This has led to over a decade of calls to establish a corresponding field of Data Science Education. There is still a need, however, to more deeply conceptualize what a field of Data Science Education might entail in terms of scope, responsibility, and execution.…

Coding has typically been understood as an engineering practice, where the meaning of code has discrete boundaries as a technology that does precisely what it says. Multidisciplinary code studies reframed this technological perspective by positing code as the latest form of writing, where code's meaning is always partial and dependent on…

Data visualizations have proliferated throughout the COVID-19 pandemic to communicate information about the crisis and influence policy development and individual decision-making. In invoking exponential growth, mathematical modelling, statistical analysis, and the like, these data visualizations invite opportunities for mathematics teaching and…

Grounded within current reform recommendations and built upon Giere's views (1986, 1999) on model-based science, we propose an alternative approach to science education which we refer to as the "Evidence-Explanation (EE) Continuum." The approach addresses conceptual, epistemological, and social domains of knowledge, and places emphasis…

Language research has come to rely heavily on large-scale, web-based datasets. These datasets can present significant methodological challenges, requiring researchers to make a number of decisions about how they are collected, represented, and analyzed. These decisions often concern long-standing challenges in corpus-based language research,…

This article presents autoethnographic short stories that describe an early childhood education and care (ECEC) centre director's work for one year in a municipality in Finland. The purpose of this article is to provide a glimpse into what it is like to enter into an ECEC director position and live everyday ECEC life with economic data that are…

Enrollment of American Indian and Alaska Native (AI/AN) students in postsecondary education in the United States has been increasing over the past three decades (Chee, Shorty, and Robinson Kurpius 2019). The Tribal College Movement began more than 40 years ago with the establishment of the first tribally-controlled community college in 1968.…

Education is considered a key element in the formation of human capital, associated with the sustainable development of a country's economic growth. The study has investigated the relationship between education and Pakistan's economic growth in the short as well as long run. For measurement, thirty years of data spanning from 1987 to 2016 was used…

Machine learning (ML) models are fundamentally shaped by data, and building inclusive ML systems requires significant considerations around how to design representative datasets. Yet, few novice-oriented ML modeling tools are designed to foster hands-on learning of dataset design practices, including how to design for data diversity and inspect…

The purpose of this quantitative study was to provide school district leaders and policymakers information of the impact grade configuration had on academic performance using math and ELA ILEARN scores over a three-year period. The study included data from 585 schools that were classified into four groups: Elementary Setting, Intermediate Setting,…

Data Envelopment Analysis (DEA) is a widely adopted non-parametric technique for evaluating R&D performance. However, traditional DEA models often struggle to provide reliable solutions in the presence of data uncertainty. To address this limitation, this study develops a novel robust super-efficiency DEA approach to evaluate R&D…