The Standards Assessment Inventory (SAI) has provided relevant, educator-level data helping systems of all kinds -- states, districts, schools, provinces, and organizations -- gather and track data about the professional learning their educators experience. An online, confidential, valid, and reliable instrument administered to school-based…

Evaluation is a critical component of continuous improvement in education. Robust evaluations enable engaged parties to determine program and intervention impact on key outcomes, identify areas for improvement, and guide future actions. Additionally, as educational systems increasingly focus on data-driven decisionmaking, evaluation becomes even…

Despite increasing calls to build equitable data infrastructures, the education field has yet to have a shared guideline around equitable education data management and stewardship. To address this gap, we propose one framework from the data governance literature: the FAIR (Findable, Accessible, Interoperable, Reusable) data management principles…

Assessment data play a crucial role in facilitating informed decision-making. In the context of student affairs professionals aiming to empirically demonstrate the significance of connection, belonging, and wellness within a holistic campus learning environment, the need for formative data is becoming increasingly valuable. The article outlines…

Enhancing special educators' data literacy is critical to informing instructional decision-making, especially for students with learning disabilities. One tool special educators commonly use is curriculum-based measurement (CBM). These data are displayed on time-series graphs, and student responsiveness is evaluated. Graph construction varies and…

This paper examines ways in which the ethics of data-driven technologies might be (re)politicised, particularly where educational institutions are involved. The recent proliferation of principles, guidelines, and frameworks for ethical 'AI' (artificial intelligence) have emerged from a plethora of organisations in recent years, and seem poised to…

For the last decade or more, circulation numbers of physical materials have declined in academic libraries across the United States. In the spring of 2020, the COVID-19 pandemic drastically altered society and daily life, not to mention library functions. In particular, fears of contagion via physical surfaces and transmission by contact led many…

Background: There is growing recognition in the education sector of the critical role empirical data plays in aiding strategic decision-making and supporting personalised learning. The call for increased and more nuanced data-driven decision-making has been primarily addressed by the institutional use of student learning dashboards and learner…

Data-informed decision-making is no longer an optional or occasional practice, as higher education professionals now routinely respond to calls for accountability by providing data to show how their work impacts students. Institutions are operating with a culture that, at a minimum, includes the use of descriptive and diagnostic analyses to assess…

Purpose: Research shows data-informed leadership matters for school improvement and student achievement, but less is known about what motivates leaders' data use toward such outcomes, particularly in the Catholic school context. Design/methodology/approach: This qualitative interview study uses interview (n = 23) data from a sample of Catholic…

The Data Culture Framework is a high-level guide designed for institutional leaders who want to create and sustain an effective data culture on campus. The Framework offers a set of practices designed to help institutions of higher education create and maintain an effective data-informed community among institutional leaders, faculty, and staff.

In 2024, state legislators introduced hundreds of bills that would affect data collection, access, and use across early education, K-12, postsecondary, and the workforce. As in 2023, legislators continued to introduce and enact legislation governing cross-agency data systems. These policies are the most important step toward making statewide…

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…

This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…

In the recent Australian 2021 census, the socio-technical construct of algorithmically driven decision-making processes made LGBTQI+ data as a category of diversity, inclusion and belonging an absent presence. In this paper, we position the notion of 'data justice' in relation to the entrenchment of inequalities and exclusion of LGBTQI+ lives and…