Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

Educational institutions and governing practices are increasingly augmented with digital database technologies that function as new kinds of policy instruments. This article surveys and maps the landscape of digital policy instrumentation in education and provides two detailed case studies of new digital data systems. The Learning Curve is a…

The state of Wisconsin has one of the highest four year graduation rates in the nation, but deep disparities among student subgroups remain. To address this the state has created the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades six through nine. The Wisconsin DEWS is in use…

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is…

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

This paper reports on a study to predict students at risk of failing based on data available prior to commencement of first year. The study was conducted over three years, 2010 to 2012, on a student population from a range of academic disciplines, n=1,207. Data was gathered from both student enrollment data and an online, self-reporting,…

Learning Analytics (LA) is a field that aims to optimize learning through the study of dynamical processes occurring in the students' context. It covers the measurement, collection, analysis and reporting of data about students and their contexts. This study aims at surveying existing research on LA to identify approaches, topics, and needs for…

We should dispense with use of the confusing term "null hypothesis" in educational research reports. To explain why the term should be dropped, the nature of, and relationship between, scientific and statistical hypothesis testing is clarified by explication of (a) the scientific reasoning used by Gregor Mendel in testing specific…

The aim of this study was to investigate forces that affect the timing of women's exit from violent relationships with men. Abused women were recruited from posters in the community and battered women's shelters, interviewed, and followed up for 10 years. Data for this study are based on 100 women and were analyzed using event history analysis.…

The development and use of library statistics in the Soviet Union and systems of reporting are discussed in this speech by E.A. Fenelonov, Ministry of Culture of the Russian Soviet Federal Socialist Republic, and are compared with statistical development in the United States by Vernon E. Palmour of King Research, Inc. Fenelonov emphasizes the use…

This report summarizes the techniques used in gathering and maintaining a data file on most of the Army aviator trainees who have been through the Officer/Warrant Officer Rotary Wing Aviator Course and the Warrant Officer Candidate Course during the period 1 July 1968-31 December 1969. Specific regression analyses dealing with the prediction of…

The first of two papers compares two models (the market based model and the prevalence model) for analyzing data from annual state surveys to determine future special education personnel needs and discusses critical issues in data collection. These data are required under the Individuals with Disabilities Education Act which asks states to project…

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…