Although social scientists devote considerable effort to mitigating measurement error during data collection, they often ignore the issue during data analysis. And although many statistical methods have been proposed for reducing measurement error-induced biases, few have been widely used because of implausible assumptions, high levels of model…

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…

Supplemental Instruction (SI) is a voluntary, non-remedial, peer-facilitated, course-specific intervention that has been widely demonstrated to increase student success, yet concerns persist regarding the biasing effects of disproportionate participation by already higher-performing students. With a focus on maintaining access for all students, a…

We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online…

A new lecture supporting system based on real-time learning analytics is proposed. Our target is on-site classrooms where teachers give their lectures, and a lot of students listen to teachers' explanation, conduct exercises etc. We utilize not only an e-Learning system, but also an e-Book system to collect real-time learning activities during the…

Analysis of student-level data to inform policy and promote student success is a core function of executive higher education agencies. Postsecondary data systems have expanded their collection of data elements for use by policymakers, institutional staff and the general public. State coordinating and governing boards use these data systems for…

The Integrated Postsecondary Education Data System (IPEDS) collects institution-level data from postsecondary institutions in the United States (50 states and the District of Columbia) and other U.S. jurisdictions (see appendix A for a list of other U.S. jurisdictions). This "First Look" presents findings from the provisional data for…

As state and local education agencies increasingly focus on serving educators with their data systems, a common challenge has arisen: identifying the critical knowledge, skills, and behaviors needed by teachers and administrators to use data effectively. Many states are creating data literacy and data use training programs for pre- and in-service…

It is an exhilarating and important time for conducting research on learning, with unprecedented quantities of data available. There is a danger, however, in thinking that with enough data, the numbers speak for themselves. In fact, with larger amounts of data, theory plays an ever-more critical role in analysis. In this introduction to the…

The purpose of this chapter is to provide administrators and faculty with an understanding of learning analytics and its relationship to existing roles and functions so better institutional decisions can be made about investments and activities related to these technologies.

This descriptive, multiple case study was designed to convey a clear portrayal of the DIDM practice of six superintendents and to provide a description of what these superintendents employ during their decision making process. The ability of local education leaders to strategically influence the use of data for decision making has a large effect…

This articles argues in favour of a recently introduced approach to statistical inference which focuses on understanding the data generating process. A comprehensive example supports the discussion.

This article is the second of two articles in this special issue that were developed following discussions of the Assessment Working Group at EDUsummIT 2013. The article extends the analysis of assessments of collaborative problem solving (CPS) to examine the significance of the data concerning this complex assessment problem and then for…

The Big Data phenomenon is posing new challenges in our modern society. In addition to requiring information systems to effectively manage high-dimensional and complex data, the privacy and social implications associated with the data collection, data analytics, and service requirements create new important research problems. First, the high…

The challenges of conducting lengthy fieldwork in today's busy academic world have impacted the types of research that are able to be carried out. In particular, traditional educational ethnography has become problematic for research beyond initial doctoral research programs. This article analyzes data collected during a return to the field of a…