Areal data have been used to good effect in a wide range of sociological research. One of the most persistent problems associated with this type of data, however, is the need to combine data sets with incongruous boundaries. To help address this problem, we introduce a new method for identifying common geographies. We show that identifying common…

In this paper, the authors address learning analytics and the ways academic libraries are beginning to participate in wider institutional learning analytics initiatives. Since there are moral issues associated with learning analytics, the authors consider how data mining practices run counter to ethical principles in the American Library…

Educational Data Mining is an emerging discipline which seeks to develop methods to explore large amounts of data from educational settings, in order to understand students' behavior, interests and results in a better way. In recent years there have been various works related to this specialty and multiple data mining techniques derived from this…

There are quite a few challenges in the development of an automated writing placement model for non-native English learners, among them the fact that exams that encompass the full range of language proficiency exhibited at different stages of learning are hard to design. However, acquisition of appropriate training data that are relevant to the…

The following is an applied database scenario based on a single season in the FIA Formula One (F1) World Championship of auto racing. This scenario builds database understanding and skills through data modeling, data acquisition, creation of a database schema through a database management system, query construction, and report creation. In the…

The School Survey on Crime and Safety (SSOCS) is managed by the National Center for Education Statistics (NCES) within the Institute of Education Sciences of the U.S. Department of Education. SSOCS collects extensive crime and safety data from principals and administrators of public schools in the United States. Data from this collection can be…

This article is a revised version of the keynote presented at LAK '16 in Edinburgh. The article investigates some of the assumptions of learning analytics, notably those related to behaviourism. Building on the work of Ivan Pavlov, Herbert Simon, and James Gibson as ways of "learning as a machine," the article then develops two levels of…

Marketing analytics students who can communicate effectively with decision makers are in high demand. These "analytic unicorns" are hard to find. The Master of Science in Customer Analytics (MSCA) degree program at Xavier University seeks to fill that need. In this paper, we discuss the process of creating the MSCA program. We outline…

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…

This discussion paper explores the possibilities and risks that data linkage presents for the vocational education and training (VET) sector. Along with a broad overview of the nature of data linkage, it highlights possible applications for data linkage in the VET sector and examines the key challenges associated with its use. A number of case…

Currently the challenges in e-Learning are converging the learning content from various sources and managing them within e-learning practices. Data mining learning algorithms can be used and the contents can be converged based on the Metadata of the objects. Ensemble methods use multiple learning algorithms and it can be used to converge the…

In recent years, a wide array of tools have emerged for the purposes of conducting educational data mining (EDM) and/or learning analytics (LA) research. In this article, we hope to highlight some of the most widely used, most accessible, and most powerful tools available for the researcher interested in conducting EDM/LA research. We will…

In this paper, we present a dataset consisting of data generated from 22 previously and currently running randomized controlled experiments inside the ASSISTments online learning platform. This dataset provides data mining opportunities for researchers to analyze ASSISTments data in a convenient format across multiple experiments at the same time.…

This case study describes an experience of using constructivist grounded theory to analyze data. The project investigated how high school students improved their approaches to learning mathematics. Over 4 months, students participated in processes which supported their learning while simultaneously generating data, including interactive writing,…

Temporal analyses are critical to understanding learning processes, yet understudied in education research. Data from different sources are often collected at different grain sizes, which are difficult to integrate. Making sense of data at many levels of analysis, including the most detailed levels, is highly time-consuming. In this paper, we…