ABSTRACT
Educational Data Mining (EDM) is a non-intrusive method that utilises machine learning techniques, learning algorithms and statistics to analyse student learning in educational settings for the purposes of assessment, evaluation, teaching and research. EDM is aligned closely with learning analytics: both are concerned with the collection, analysis and interpretation of educational data and both extract information from educational data to inform decision-making. Researchers working within a variety of disciplines and fields of study use EDM, including sociology, education, educational psychology, education computing and technology, linguistics and learning sciences. EDM can be used to understand the learning activities of students, how they behave when learning, what they know and their level of engagement. It enables researchers and tutors to produce profiles of students, monitor progression, predict behaviour and future performance identify at-risk students and improve retention rates.
