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…

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…

The issue of student retention and graduation from postsecondary institutions has grown in stature over the past decade. While the last 40 years of federal and state policies have focused largely on access to college, there is now a very real interest in not only getting students into college but also helping them earn baccalaureate and other…

In this conceptual paper, we map the research terrain on what we term "student-involved data use" (SIDU)--that is, the practice of having students track, chart, and analyze their own data in formal and structured ways. Drawing on peer-reviewed research as well as practitioner-oriented literature, social media, and district websites, we…

In recent years, education data have become both more easily accessible and more important than ever to decisions about K-12 policies and practice. Under the "Every Student Succeeds Act" (ESSA), states are required to publish data on how students, including English Learners (ELs), are performing in areas such as reading, math, and…

Teachers need longitudinal student-level data, such as attendance history, course-taking patterns, grades, and test scores, to tailor instruction to individual students' strengths and weaknesses.This factsheet uses the findings from the Data for Action 2013 analysis to discuss how states can provide teachers with student-level longitudinal data,…

In light of increasing concerns about surveillance, higher education institutions (HEIs) cannot afford a simple paternalistic approach to student data. Very few HEIs have regulatory frameworks in place and/or share information with students regarding the scope of data that may be collected, analyzed, used, and shared. It is clear from literature…

With digitisation and the rise of e-learning have come a range of computational tools and approaches that have allowed educators to better support the learners' experience in schools, colleges and universities. The move away from traditional paper-based course materials, registration, admissions and support services to the mobile, always-on and…

Charlotte-Mecklenburg Schools' (CMS) Parent University is an innovative, collaborative initiative designed to engage parents in their children's education. Working with community partners, Parent University offers unique courses and workshops such as Parenting Awareness, Helping Your Child Learn in the 21st Century, Health and Wellness, and…

Building Assets Reducing Risks (BARR) is a social emotional model that achieves academic outcomes through combining use of real-time student data with proven relationship-building strategies and intensive teacher collaboration to prevent course failure. BARR is a recipient of US Department of Education "Investing in Innovation (i3)"…

Districts expend a considerable amount of time, effort, and resources providing student performance data to teachers to inform instruction, and examining those data for organizational decision-making. Yet rarely, if ever, are these outcome data connected to what goes on in classrooms. In this experimental study, the author reports on the…

Faced with rising demand for information about early childhood programs, states need to find tools and strategies to monitor the progress of and to identify high-quality early childhood programs. In response, REL Mid-Atlantic convened a regional workgroup for state personnel who work with the systems containing early childhood data. The workgroup…

This document is part of a series of guides designed to help school district leaders address one of the toughest challenges in American education: dropout rates of 30 percent nationwide, 50 percent in many big cities, and 60 percent or more in the lowest-performing schools. It includes tools for data analysts to drill down into the data and use…

Schools gather, store and use an increasingly large amount of data. Keeping track of everything from bus routes to building access codes to test scores to sports equipment is done with the help of electronic database programs. Large databases designed for budgeting and student record keeping have long been an integral part of the educational…

Describes the Pittsburgh Public School System's Division of Computer Services established in 1968 to develop computer applications to provide reliable, timely, and accurate information for all phases of the school system. (Author)