Educational Data Mining: An Advance for Intelligent Systems in Education

Computer-based technologies have transformed the way we live, work, socialize, play, and learn. Today, the use of data collected through these technologies is supporting a second-round of transformation in all of these areas. Over the last decades, the methods of data mining and analytics have transformed field after field. Scientific fields such as physics, biology, and climate science have leveraged these methods to manage and make discoveries in previously unimaginably large datasets. The first journal devoted to data mining and analytics methods in biology, Computers in Biology and Medicine, began publication as long ago as the 1970s. In the mid-1990s and into the first decade of the new millennium, data mining and analytics began to occupy a prominent place in business practices. Now, it seems like one can hardly go to an airport without seeing an advertisement from a consultancy, promising to increase profits through analytics, or an advertisement for a master’s degree in analytics or data science. In the Education field, data mining and analytics also have huge transformational potential: discovering how people learn, predicting learning, and understanding real learning behavior. By achieving these goals, educational data mining can be used to design better and smarter learning technology and to better inform learners and educators. Initial Obstacles and Efforts The development of data mining and analytics in the field of Education was fairly late, compared to other fields. The first articles and workshops on data mining in Education began only a decade ago, the first conference series (th