A significant amount of research has gone into predicting student performance and many studies have been conducted to predict why students drop out. A variety of data including digital footprints, socio-economic data, financial data, and psychological aspects have been used to predict student performance at the test, course, or program level.…

This Equity Tool, intended to support when critically reading a research study/report, provides a brief introduction to key concepts and issues involved in using largescale research, calling attention to high profile controversies, and providing explicit linkages to desegregation areas (race, sex, nationality, religion). The first part (Table 1)…

Although the body of research about LGBTQ+ students in higher education is growing, little is known about the experiences, success rates, persistence, and graduation rates of sexual minority community college students. Researchers studying this population frequently cite a lack of available data that would assist in exploring the experiences of…

This case study discusses how theory and deductive analysis can be used to better understand work-based learning (WBL). Based in a U.K. teacher education setting, it discusses a project which examined how novice teachers in English Further Education develop their professional knowledge and how their experiences might help understand WBL more…

Purpose: A literature review of 28 data literacy, education articles from 2010 to 2018 was conducted to gain a better understanding of the current state of data literacy research. Design/methodology/approach: A systematic literature review of ERIC, Education Source, and JSTOR was conducted. Articles were included in this literature review if they…

Even with extensive retention research dating from the 1960s, community colleges still struggle to identify the reasons why students do not return to college. Data mining has allowed these retention models to evolve to identify new patterns among student populations and variables. The purpose of this study was to create a predictive model for…

This report aims to provide insight into the realities faced by higher education academic staff at a time of fast-moving change and increasing societal demand. Fluctuating student numbers, new funding and steering mechanisms are among the features of today's European higher education landscape, but not enough is known about how academic staff are…

In 1989, New Zealand started to follow an international trend of reforming education policy according to the neoliberal principles of competition, choice and self-managing schools. Since then, the increasing availability of digital data in schools has corresponded with the development of student achievement measurement tools and benchmarking of…

The concept of precision medicine aims to provide additional context to patient data for healthcare providers. Precision medicine overlays three additional layers of patient data on top of standard patient information: environmental exposure, personal lifestyle and behavior patterns, and information gleaned from their genome. While precision…

California has long been a national and global leader in developing and maintaining quality higher education options, as well as in providing financial aid and consumer protections for Californians who access that education. However, although California's colleges and the state government do collect, receive, and report a great deal of data, these…

This report focuses on a critical concern for the European Training Foundation's (ETF's) partner countries and other countries of the around the world. Skills mismatch is recognised as a major challenge by policy makers, practitioners and social partners, as it is often associated with dynamic social and economic contexts such as restructuring…

Increasing numbers of states have incorporated measures of students' academic growth into their data and accountability policies. Measuring growth is a statistically complicated task and complex growth measures can be easy to misinterpret. This paper reports on a survey of 317 Massachusetts principals' understanding of the Student Growth…

In the last few years, open textbook development has picked up dramatically due both to the expense of commercially published textbooks and the increasing availability of high-quality OER alternatives. While this offers a tremendous benefit in terms of lowering student textbook costs, the question remains, to what extent (if any) do open textbooks…

This paper aims to illustrate how data visualization could be utilized to identify errors prior to modeling, using an example with multi-dimensional item response theory (MIRT). MIRT combines item response theory and factor analysis to identify a psychometric model that investigates two or more latent traits. While it may seem convenient to…

Learning analytics is an emerging field in which sophisticated analytic tools are used to inform and improve learning and teaching. Researchers within a regional university in Australia identified an association between interaction and student success in online courses and subsequently developed a learning analytics system aimed at informing…