Despite the increasing interest in data analytics applications within postgraduate education research, there remains a significant gap in research dedicated to exploring mixed methods research for such investigations. This study undertook to bridge this gap by exploring the application and use of mixed methods research to examine data analytics…

Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…

The traditional system focuses excessively on physical skills and physical fitness assessment, with problems such as single indicator, static approach, subject limitation and inefficient data utilization, making it difficult to assess students in a comprehensive and fair manner. The rise of big data technology has brought about a turnaround, from…

Against the background of a data-driven education system that has detrimental effects on teachers' personal and professional lives, we report on an exploratory project in which seven primary teachers in England shared experiences of literacy teaching through generating 'small' data visualised on postcards. Thematic analysis of their data-sharing…

For any government, difficult choices must be made about how and where to prioritize any school construction. In the absence of data-driven decision-making, these choices typically will be made based on opinions; when that is the case, the most powerful people's opinions tend to dominate. On the other hand, data help us ensure all the children's…

Advances in Information Technology (IT) and computer science have without a doubt had a significant impact on our daily lives. The past few decades have witnessed the advancement of IT enabled processes in generating actionable insights in various fields, encouraging research based applications of modern Data Science methods. Among many other…

Programming skills (PS) are indispensable abilities in the information age, but the current research on PS cultivation mainly focuses on the teaching methods and lacks the analysis of program features to explore the differences in learners' PS and guide programming learning. Therefore, the purpose of this study aims to explore horizontal…

Augmented reality (AR) helps three dimensional, virtual objects to be viewed, interactively, in a real-world setting. AR technology is used in many fields such as medicine, advertisement, military, industry, and increasingly in education. AR has an importantrole in concretizing educational platforms and achieving permanentlearning. This study aims…

Response styles introduce construct-irrelevant variance as a result of respondents systematically responding to Likert-type items regardless of content. Methods to account for response styles through data analysis as well as approaches to mitigating the effects of response styles during data collection have been well-documented. Recent approaches…

This brief examines how state policies and practices continue to evolve in light of the COVID-19 pandemic. It is based on data provided by 45 states plus the District of Columbia as of early May 2022. The brief updates our 2021 report, "Are Students Present and Accounted For? An Examination of State Attendance Policies During the COVID-19…

The National Center for Education Statistics (NCES) sponsors the National Teacher and Principal Survey (NTPS) on behalf of the U.S. Department of Education in order to collect data on public and private elementary and secondary schools in the United States. The NTPS is a large-scale, nationally representative sample survey of K-12 public and…

Systems for learning and producing knowledge, such as career and technical education (CTE), often reproduce inequities unless an equity-focused lens is used when designing, implementing, and evaluating programs. This framework presents guidance for conducting CTE research with an intentional focus on equity. Developed by the CTE Research Network's…

Determining whether a state's young people are on track for a life of opportunity is a difficult task for governors and state leaders. States can be both awash in data and unable to easily access and use that data to inform policy. State longitudinal data systems that meaningfully connect workforce, higher education, K-12, and early childhood…

Higher education leaders have repeatedly called for improved diversity, equity, and inclusion efforts, but many institutions continue to fall short. Data can play an integral role in this work; key among them are data on student demographics, including race/ethnicity. Meeting diversity, equity, and inclusion goals requires a thorough and nuanced…

Statistical data is used in the media and on online platforms, often with an interpretation that serves some commercial or political purpose. Primary preservice teachers must be able to understand statistical data and analyze it critically. Only in this way will they be able to contribute as future teachers to the development of a critical spirit…