The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…

The use of information and communication technology-based data systems to support teachers in data-driven decision-making (DDDM) remains limited. Despite the growing number of data systems available, their uptake remains limited, and there is a limited understanding of what data system characteristics increase and factors that influence teacher…

People need access to data to make decisions about post-high school experiences, including postsecondary education. Policymakers need to better understand how financial circumstances relate to college enrollment and completion. And students and their families need information about how much financial aid they may have access to for financing their…

In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…

This study presents a data mining approach to predict academic success of the first-year students. A dataset of 10 academic years for first-year bachelor's degrees from a Portuguese Higher Institution (N = 9652) has been analysed. Features' selection resulted in a characterising set of 68 features, encompassing socio-demographic, social origin,…

The purpose of this study was to examine the amount of attention devoted to data-based decision-making in Curriculum-Based Measurement (CBM) professional development materials. Sixty-nine CBM instructional sources were reviewed, including 45 presentations, 22 manuals, and two books. The content of the presentations and manuals/books was coded into…

Learning Analytics (LA) has had a growing interest by academics, researchers, and administrators motivated by the use of data to identify and intervene with students at risk of underperformance or discontinuation. Typically, faculty leadership and advisors use data sources hosted on different institutional databases to advise their students for…

Data-driven decision making (DDDM) involves using information gathered from and about students to make ongoing decisions about their instruction. Many teachers struggle with implementation of DDDM practices to optimize instruction, underscoring the importance of teacher education vis-à-vis DDDM. The present study secondarily analyzed existing data…

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…

Purpose: Drawing on Coburn and Turner's framework for research on data use, this study looks at how contextual factors support interactions around data. In so doing, the authors contribute to the emerging body of literature on administrators supporting high school students' social-emotional learning (SEL). Design/methodology/approach: This…

Libraries hold large amounts of data, which can contribute to improvements in the quality of library services. Data resources of modern library have the characteristics of big-data, where library can use big-data methods to achieve reform and innovation, including resource transferring, resource utilisation, social identity, thinking innovation.…

This work focuses on simulation, design, development, and evaluation of a visual Learning Analytics (LA) tool -- Real-time Educational AI-powered Classroom Tool (REACT) -- to support educators' data-driven decision-making. The educational institutions face one of the biggest challenges, such as predicting student performance, detecting undesirable…

Objective/Research Question: Community college graduation rates are typically quite low, and developmental mathematics enrollment and coursetaking patterns may constrain academic outcomes. To identify ways in which community college graduation rates may be improved, decision trees were utilized to examine the STEM coursetaking patterns of N =…

Decision-making is key for teaching, with informed decisions promoting students and teachers most effectively. In this study, we explored data-driven decision-making processes of K-12 teachers (N = 302) at times of emergency remote teaching, as experienced during the COVID-19 pandemic outbreak in Israel. Using both quantitative and qualitative…

Data-based instruction (DBI) is a process of collecting and using student progress data to guide decision-making related to intervention intensity and individualization for students with learning disabilities (LD). However, effective DBI requires that teachers have a range of knowledge and skills across multiple domains. Past research has shown…