SUPPORTING TEACHING AND LEARNING THROUGH THE APPLICATION OF EDUCATIONAL DATA MINING TECHNIQUES

As defined by the Educational data mining (EDM) society, EDM is an emerging discipline concerns with developing methods for exploring the unique and large-scale data that come from educational settings. EDM exploits techniques of data mining to analyze data collected from the educational environment. The main goal of EDM is to support students learning by predicting students’ future learning behaviours, Studying the effects of different kinds of pedagogical support that can be provided by learning software, and advancing scientific knowledge about learning through building computational models that integrate models of the student, the domain of content to be learned, and the software’s pedagogy. The new trend in educational institutions today is to provide online systems for students to learn. The new technology that supports learning activities, can at the same time collect data about students during the course of learning. Educational data mining is used to investigate online learning systems used in schools and higher education institutions. It can be used to model the users of these systems, including the student’s knowledge, students’ behaviour, motivation, and the extent of satisfaction of the student with the online learning process. EDM uses different methods to study and analyse data gathered from online learning systems, by classifying the data or discovering relationships between them, and build models of predictions that can support future student’s learning. This paper focuses on the wider applications of educational data mining, particularly areas related to online learning. The paper discusses the importance of EDM for the industrial companies offering online learning systems and the impact of EDM on maximizing the effectiveness and efficiency of learning.