The authors used a clustering technique to analyze business course choices made by students who completed an individualized degree in a large, urban, public university. They looked for patterns to answer the research question, "What can we learn from students' choices to inform the curricular redesign process in business programs?" The…

Thanks to extraordinary and exponential improvements in data storage and computing capacities, it is now possible to collect, manage, and analyze data in magnitudes and in manners that would have been inconceivable just a short time ago. As the world has developed this remarkable capacity to store and analyze data, so have the world's governments…

Nowadays, Massive Open Online Courses (MOOCs) have obtained a rapid development and drawn much attention from the areas of learning analytics and artificial intelligence. There are lots of unstructured data being generated in online reviews area. The learning behavioral data become more and more diverse, and they prompt the emergence of big data…

This timely book presents a data-driven approach to preventing and responding to school violence. As school violence receives increasing attention across the nation, the application of scientific knowledge is critical. For maximum effectiveness, transdisciplinary teams should use school data, logic models, and theories of change to design,…

Data collected from online learning and tutoring systems for individual students showed strong autocorrelation or dependence because of content connection, knowledge-based dependency, or persistence of learning behavior. When the response data show little dependence or negative autocorrelations for individual students, it is suspected that…

This chapter describes the background and process for collecting postgraduation outcomes data at a 4-year not-for-profit private college. The strategies, analyses, and reporting of this data-collection effort are highlighted with the use of a case study.

In this study, we examined how in-service middle-level mathematics teachers used statistics in their own classroom research. Using an embedded single-case design, we analyzed a purposefully selected sample of nine teachers' classroom research papers, identifying several themes within each phase of the statistical problem solving process to…

The recommendations in this brief create a framework for using data effectively to make instructional decisions. The availability of student-level data for educators has pushed forward the movement to strengthen the role of data to guide instruction and improve student learning. While improvements in technology and assessments, as well as recent…

State education data systems help policymakers use data to evaluate the impact of their efforts to improve education. By disaggregating the data -- that is, breaking it out by different student subgroups -- policymakers can ensure that their efforts address the needs of students who have been traditionally underserved in educational settings. Yet…

This chapter details the process the University of Michigan developed to build institutional capacity for learning analytics. A symposium series, faculty task force, fellows program, research grants, and other initiatives are discussed, with lessons learned for future efforts and how other institutions might adapt such efforts to spur cultural…

Background: Data use has been promoted as a panacea for instructional improvement. However, the field lacks a detailed understanding of how teachers actually use assessment data to inform instruction and the factors that shape this process. Purpose: This article provides a review of literature on teachers' use of assessment data to inform…

Personalized learning has become the most notable application of big data in primary and secondary schools in the United States. The combination of big data and adaptive technological platforms is heralded as a revolution that could transform education, overcoming the outdated classroom model, and realizing the progressive vision of…

This report identifies effective strategies to tackle skills imbalances in South Africa. It provides an assessment of practices and policies in the following areas: the collection and use of information on skill needs to foster a better alignment of skills acquisitions with labour market needs; education and training policies targeting skills…

This 2016 document is designed to provide state Part C staff with guidance on using fiscal data to analyze and revise their allocation methodology. Allocation methodology is the process -- including practices, strategies, procedures, and policies -- used by Part C state staff to equitably distribute funds to meet the needs of the system, including…

In this study, we used a paper-pencil questionnaire to investigate whether teachers, administrators, and parents differed in their preferences and accuracy when interpreting visual data displays for decision making. For the data analysis, we used nonparametric tests due to violations of distributional assumptions for using parametric tests. We…