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…

With the increasing presence of 'datafied' educational settings across Australia, critical components of teachers' educational practice and work have been quantified. Digital data collected through teachers' labour in and around the classroom links to educational practice and the commercial datafication of teachers' online persona. Often described…

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…

Data increasingly mediates how we understand the world. As such, there is growing interest in designing initiatives to help young people learn about data--not only the techno-mathematical skills necessary to work with data, but also the dispositions needed to participate in data-centric ways of knowing and doing. In this article, we argue that as…

Participatory sensing is a data collection method in which communities of people collect and share data to investigate large-scale processes. These data have many features often associated with the big data paradigm: they are rich and multivariate, include non-numeric data, and are collected as determined by an algorithm rather than by traditional…

The Australian Institute of Health and Welfare developed a national data standards strategy and implementation plan to enhance the comparability, quality and coherence of information across the Australian education and training sectors, including early childhood education, school education, vocational education and training (VET) and higher…

There is much agreement among chemical education researchers that expertise in chemistry depends in part on the ability to coordinate understanding of phenomena on three levels: macroscopic (observable), sub-microscopic (atoms, molecules, and ions) and symbolic (chemical equations, graphs, etc.). We hypothesize this "level-coordination…

Response-to-intervention (RTI) systems posit that Tier 1 consists of high-quality general classroom instruction using evidence-based methods to address the needs of most students. However, data on the extent to which general education teachers provide such instruction are rarely collected. This missing instructional data problem may result in RTI…

Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…

For students to be successful in STEM, they need "statistical literacy," the ability to interpret, evaluate, and communicate statistical information (Gal 2002). The science and engineering practices dimension of the "Next Generation Science Standards" ("NGSS") highlights these skills, emphasizing the importance of…

As the name indicates, the College Readiness Data Catalog Tool focuses on identifying data that can indicate a student's college readiness. While college readiness indicators may also signal career readiness, many states, districts, and other entities, including the U.S. Virgin Islands (USVI), do not systematically collect career readiness…

In this article, we discuss the use of administrative data from schools, colleges and universities, and other public and private agencies and organizations for tracking students through their educational pathways. We focus on existing data collection systems that can be used to study successful postsecondary education transitions, including both…

The purpose of this study was to determine if there was a difference in how high and low performing elementary school districts use and analyze data to differentiate instruction, make changes to district/grade level curriculum, determine professional development needs, determine teacher effectiveness, and determine the use of school district…

Ohio's Butler Tech has been able to improve its student performance results from near the worst in Ohio to among the best in six years. At Butler Tech, performance measures are collected and analyzed on a regular basis at all levels of the institution to serve as constant feedback on how well the school is educating its students. In this article,…

Many school districts are putting data to good use, although much of the data used in administrative decision making ultimately derives from standardized test scores, which raises a host of other related concerns. The author's purpose in this article is not to critique the types or sources of data that administrators use, but to suggest that there…