Using secondary data has many advantages, but there are also many limitations, including the lack of relevant information. This article draws on a previous study that used secondary data to investigate substance use in young, elite athletes. Three types of missing data appeared: missing data, lack of information about the data collection process,…

The U.S. Department of Education has required educational collection and reporting. For postsecondary institutions, this requirement has evolved from the Higher Education General Information Survey (HEGIS), which was used from the 1960s to the 1980s, to the Integrated postsecondary Education Data System (IPEDS) (Aliyeva, Cody, & Low, 2018).…

This article aims to present a first approximation of the conceptual field of measures of central tendency (MCT), grounded in the theory of conceptual fields. We propose six situations according to type of variable, data presentation (raw or grouped) and amount of data. We revisit specific situations for the mean and exemplify several…

Data collection and analyzation practices for English language development services are scarcely found in research, but needed in the subgroup of minority students commonly known as English language learners (Wiseman & Bell, 2021). Wiseman and Bell (2021) identified ELLs as one of the most under-documented student subgroups in the American…

The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center,…

With teacher shortages, high staff turnover, and an influx of new and underprepared teachers, highly capable data-informed teaching teams are needed now more than ever. "Instructional Innovation+" provides educators with a systematic action research approach to achieve instructional innovation and guide teaching teams to success through…

This paper offers a creative methodology for co-creating and analysing data when conducting research with children, families and practitioners in the early years. Instead of relying heavily on either adult observation or language when, for example, interviewing children, we propose the method of choreographed visual montage. We show the novelty…

In this paper, we report findings from a multiple case study that examined how instructors used shared data when teaching qualitative data analysis. More specifically, we explored both instructor and student experiences in two graduate-level qualitative methods courses located at U.S. universities. Drawing upon thematic analysis and the theory of…

This article details an exploratory data analysis project using the Common Online Data Analysis Platform (CODAP) based on the "Guidelines for Assessment and Instruction in Statistics Education" (GAISE) four-part statistical problem-solving model. The project goal was to answer what similarities and differences exist within the school…

States often lack timely, specific information about where teachers are needed the most. This information gap is compounded by the way public schools typically pay teachers--based on experience and academic credentials rather than supply and demand conditions--which sends weak signals to potential teachers about which positions are most in-demand…

Purpose: While designing personally meaningful activities with data technologies can support the development of data literacies, this paper aims to focuses on the overlooked aspect of how learners navigate tensions between personal experiences and data trends. Design/methodology/approach: The authors report on an analysis of three student cases…

Everyone who uses student information has a responsibility to maintain students' privacy and the security of their data. Ensuring student data privacy is about so much more than complying with the Family Educational Rights and Privacy Act (FERPA). While privacy must be top of mind when thinking about collecting and using personally identifiable…

This article characterizes and reflects on the possible uses of early warning systems (hereafter, EWS) in the region as effective tools to support educational pathways, whenever they identify risks of dropout, difficulties for the achievement of substantive learning, and the possibility of organizing specific actions. This article was developed in…

In contexts where people lack prior knowledge and risk awareness--such as the COVID-19 pandemic--even truthful visualizations of data can seem surprising. This can lead people to mistrust the veracity of the data and to discount it, leading to poor risk decisions. In this work, we illustrate how narrative visualizations can achieve a balance…

Missing data are common with large scale assessments (LSAs). A typical approach to handling missing data with LSAs is the use of listwise deletion, despite decades of research showing that approach can be a suboptimal strategy resulting in biased estimates. In order to help researchers account for missing data, we provide a tutorial using R and…