In the United States, high school attendance and drop-out are important policy concerns receiving extensive coverage in the research literature. Traditionally, the focus in this work is on the summary of dropout rates and mean attendance rates in specific schools, regions or socio-economic groups. However, the question how stable those attendance…

Analytics derived from the student learning environment provide new insights into the collegiate experience; they can be used as a supplement to or, to some extent, in place of traditional surveys. To serve this purpose, however, greater attention must be paid to conceptual frameworks and to advancing institutional systems, activating new…

This chapter describes an open learning analytics system focused on learning process measures and designed to engage instructors and students in an evidence-informed decision-making process to improve learning.

Constructively engaging with learning analytics enables institutions of higher education to support students in more personalized, empowering ways, but to do so requires sustained levels of collaboration not commonly found within colleges and universities. Themes that emerge from the chapters of this volume provide useful principles for leveraging…

This article develops a perspective on big data in education, drawing on a broadly liberal conception of education's primary purpose. We focus especially on the rise of so-called learning analytics and the associated rise of digitization, which we evaluate according to the liberal view that education should seek to cultivate individuality and…

In this book, educators learn what they need to know about the action research cycle and get practical help for working through each step of the cycle--from choosing a topic and generating research questions to analyzing data and reporting results and conclusions. In a clear, concise, user-friendly approach, the author helps readers through the…

Our research explores the experiences of participants in a program for graduate students interested in pursuing faculty careers in higher education (Students Pursuing Faculty Careers). The methodologies used to collect data for this case study included individual semistructured interviews, an asynchronous online focus group, a qualitative Levels…

This guide describes a five-step collaborative process that educators can use with other educators, researchers, and content experts to write or adapt questions and develop surveys for education contexts. This process allows educators to leverage the expertise of individuals within and outside of their organization to ensure a high-quality survey…

In this paper log data on e-book usage is used as part of a learning analytics approach to generate user models which describe university students' characteristics in multiple dimensions. E-book usage is logged and analysed to extract information on how users use e-books for academic purposes. Two cases contributing to user modelling are…

This article addresses methodological issues related to the consequences of researchers' range of insider identities that emerge over the course of completing subsequent stages of qualitative migration research projects. Taking on a temporal approach to the insider status evolving over the course of field entry, data collection, data analysis, and…

Nitrogen- or phosphorus-based fertilizers, used in agriculture, can run off into nearby waterways during periods of heavy rain or high flow and cause harmful blooms (Paerl et al. 2016), low oxygen (Joyce 2000), and decreased biodiversity (Sebens 1994). Studies of the effects wetlands can have on water and habitat quality (Verhoeven and Meuleman…

Currently, the state of California has dedicated much focus to reducing absenteeism in schools through the In School + On Track initiative, which revitalizes efforts made to keep accurate and informative attendance data. Additionally, absenteeism has been integrated into California's Local Control and Accountability Plan to monitor district…

The use of machine learning and data mining techniques across many disciplines has exploded in recent years with the field of educational data mining growing significantly in the past 15 years. In this study, random forest and logistic regression models were used to construct early warning models of student success in introductory calculus-based…

The purpose of this study is to compare decision trees obtained by data mining algorithms used in various areas in recent years according to different criteria. In the study, similar and different aspects of the decision trees obtained by different methods for classifying the students as successful and unsuccessful in terms of science literacy…

Extension professionals are increasingly using geographic information system (GIS) technology to develop and inform programs and services. In this article, we use a mapping exercise to demonstrate how the unit of data can be applied and inadvertently misrepresented in GIS mapping. We contrast the use of counts, percentages, and location quotients…