Preface

Educational Data Mining (EDM) is the process of converting raw data from educational systems to useful information that can be used by educational software developers, students, teachers, parents, and other educational researchers. EDM is also an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and with using those methods to better understand students and the settings in which they learn. Whether educational data are taken from students ' use of interactive learning environments, computer-supported collaborative learning, or administrative data from schools and universities, it often has multiple levels of meaningful hierarchy, which often need to be determined by properties in the data itself, rather than in advance. Issues of time, sequence, and context also play important roles in the study of educational data. The First International Conference on Educational Data Mining (EDM2008) 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 educational software, as well as state databases of student test scores, has created large repositories of data reflecting how students learn. The EDM conference focuses on computational approaches for using those data to address important educational questions. The broad collection of research disciplines ensures cross-fertilization of ideas, with the central questions of educational research serving as a unifying focus. This annual conferenc