Data mining techniques are used to extract useful knowledge from raw data. The extracted knowledge is valuable and significantly affects the decision maker. Educational data mining (EDM) is a method for extracting useful information that could potentially affect an organization. The increase of technology use in educational systems has led to the storage of large amounts of student data, which makes it important to use EDM to improve teaching and learning processes.

data mining

Implementing a Data Mining Project The data mining projects are implemented with the aim of discovering patterns of relevant and interesting information in large volumes. This is done with the development of four phases (Virseda Benito & Carrillo, 2008), which are usually: 1. Filtering data. 2. Selection of variables. 3. Extracting knowledge. 4. Interpretation and evaluation. In general, all techniques have been proved in educational settings (G. Siemens & G. Siemens, 2012), and different case studies have been developed to evaluate the performance of different techniques and to meet the main goals of data mining for education, which seek to identify of behavior patterns of students in their academic environments, classify the types of students according to the recorded performance, classify teachers according to the activities and the use of platforms, identifying successful patternsin the use of virtual learning environments among many others.

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