This year saw unprecedented disruptions to schools and to students' lives across the country. With a global pandemic shutting school doors, causing economic instability, and highlighting the impact of systemic racism, policymakers and education leaders are looking to data to help them respond and recover. The Data Quality Campaign's 2020 research…

In an increasingly data-driven world, large volumes of fine-grained data are infiltrating all aspects of our lives. The world of education is no exception to this phenomenon: in classrooms, we are witnessing an increasing amount of information being collected on learners and teachers. Because educational practitioners have so much contextual and…

Our nation spends approximately $650 billion per year on our K-12 education system. To understand how those dollars impact students, we need to examine spending where it reaches them: at the school level. The document, developed by the National Center, describes a national data archive that uses all elements of Interstate Financial Reporting (IFR)…

The research on using event logs and item response time to study test-taking processes is rapidly growing in the field of educational measurement. In this study, we analyzed the keystroke logs collected from 761 middle school students in the United States as they completed a persuasive writing task. Seven variables were extracted from the…

This study presents topic modeling based bibliometric characteristics of the articles related to the flipped classroom. The corpus of the study consists of 2959 articles published in the Scopus database as of the end of 2021. In addition to the bibliometric characteristics of the field, research interests and trends were also revealed with the…

Machine Learning concept learns from experiences, inferences and conceives complex queries. Machine learning techniques can be used to develop the educational framework which understands the inputs from students, parents and with intelligence generates the result. The framework integrates the features of Machine Learning (ML), Explainable AI (XAI)…

The adoption by the African Union of its Convention on Cyber Security and Personal Data Protection in 2014 represented a step forward to protect personal data and to ensure that data remain private and secure. This is especially important for students, who often have no autonomy in the educational technology they use. Students cannot choose why…

This paper is a critical case study tracing the professional history of a self-professed open educator over more than two decades. It frames the narrative of an individual as a window on the broader arc of the field, from early open learning as a means of widening participation, through the rise of the participatory web at scale, to the current…

Hands-on computing education requires a realistic learning environment that enables students to gain and deepen their skills. Available learning environments, including virtual and physical laboratories, provide students with real-world computer systems but rarely adapt the learning environment to individual students of various proficiency and…

Country differences in response styles (RS) may jeopardize cross-country comparability of Likert-type scales. When adjusting for rather than investigating RS is the primary goal, it seems advantageous to impose minimal assumptions on RS structures and leverage information from multiple scales for RS measurement. Using PISA 2015 background…

Background: Digital Information Literacy (DIL) refers to the ability to obtain, understand, evaluate, and use information in digital contexts. To accurately capture various dimensions of DIL, assessment designers have increasingly looked toward complex, interactive simulation-based environments that afford more authentic learner performances.…

The purpose of our study was to systematically compile fatality data in Canada involving minors in school and youth groups engaged in outdoor learning, and then compare these incidents to other available data related to risk of fatalities, fatality rates, patterns, and contributory causes. This mixed methods study involved collecting fatality data…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

Measurement uncertainty is a key topic in the university physics laboratory curriculum. In this study, we investigate students' ability to draw conclusions from measurement data and reasoning about measurement uncertainty in inquiry labs. This investigation centres around a task where students conclude whether measurements from two experiments…

In this paper, a key node mining algorithm of entropy-CRITIC combined weighted GRA-TOPSIS method is proposed, which is based on the network structure features. First, the method obtained multi-dimensional data of students' identities, seating relationships, social relationships, and so on to build a database. Then, the seating similarity among…