Whilst there is plenty of debate on the nature and role of data in social science research, data in schools tend to be understood in terms of numbers and used in limited ways linked primarily to attainment. The 'datafication' of schooling has been strongly critiqued for its powerful impacts on policy and practice, pupils' experience, the…

This is the fourth in a series of statistical articles for mathematics teachers. In this article, the authors discuss topics in General Mathematics in Unit 2 Topic 1 (Univariate data analysis and the statistical investigation process) and topics in Essential Mathematics, Unit 2 Topic 1 (Representing and comparing data).

Data--done right--has the power to put schools on the path to true change. Rely on this research-backed resource to help you kickstart, implement, and sustain data-informed school-wide transformation. There are many ways to use student data, and the author's 10 steps offer practical, clear methods for establishing a data team, collecting relevant…

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…

Supervision models are fundamental to our supervision practices and criticized for lacking empirical support. As a data-driven approach based on research with expert supervisors, Cohesive Model of Supervision unifies existing models' central premises in a meaningful manner and emphasizes the understated areas of supervision practice.

Penciling, a technique used to anonymize images for both human and machine vision, offers an opportunity to reduce technical traceability and retain visual data for online and social media research contexts. Drawing on methods for creating composite narrative and visual accounts to preserve participant anonymity, penciling enables researchers to…

This case study examines employee attrition, its detrimental effects on businesses, and the potential of data analytics to address this challenge. By employing Latent Dirichlet Allocation (LDA), a sophisticated NLP technique, we delve into the underlying reasons for employee departures. Additionally, we explore using RapidMiner to develop…

Binary logistic regression is one of the most widely used statistical tools. The method uses odds, log odds, and odds ratios, which are difficult to understand and interpret. Understanding of logistic regression tends to fall down in one of three ways: (1) Many students and researchers come to believe that an odds ratio translates directly into…

In this paper, we propose a method for constructing an occupation-based socioeconomic index that can easily incorporate changes in occupational structure. The resulting index is the occupational percentile rank for a given cohort, based on contemporaneous information pertaining to educational composition and the number of workers at the occupation…

Student data is an invaluable asset for driving educational success, yet it comes with significant responsibility. As states explore ways to enhance data privacy protections, they must strike a balance between safeguarding sensitive information and leveraging data for student success. This brief examines the best practices in student data privacy…

This paper discusses the "how" of conducting participatory research that engages youth as participants and, more importantly, as co-researchers. In collaboration with four community co-researchers, this arts-based inquiry engaged 14 young Black people ranging in age from seven to fifteen years around their definitions of joy. Using a…

Higher education leaders face growing pressure to demonstrate the return on investment (ROI) of not only their institution but also each academic program offering. With increasing accountability and limited time for meaningful reflection on student learning and development, now is the time to rethink how a quasi-annual academic program review…

Background and Context: Data science and statistics are used across a broad spectrum of professions, experience levels and programming languages. The popular scientific computing languages, such as Matlab, Python and R, were organized without using empirical methods to show evidence for or against their design choices, resulting in them feeling…

This case study is based on original research adopting a textographic research approach. Textography combines both textual analysis and ethnography to investigate the texts, context, and practices of a specific discourse community. Textography can include ethnographic methods including but not limited to observations, documentary evidence, and/or…

Many large-scale assessments model proficiency with a latent regression on contextual variables. Item-response data are used to estimate the parameters of the latent variable model and are used in conjunction with the contextual data to generate plausible values of individuals' proficiency attributes. These models typically incorporate numerous…