Educational data mining (EDM) tools provide interesting possibilities for more in-depth exploration of learning processes.
The tools used to teach basics of EDM should be powerful but at the same time easy enough to learn and operate. The students necessarily do not have skills to modify the functionality of the tools. In many cases, the tools provide mainly pre-defined set of rules and models [5] and modifications are impossible to apply without a complicated and time-costly process. Empirical approach of the OME and hands-on experiments with real data sets in learning environments help the students to gain understanding about causations that follow their choices in different parts of the data mining process. Based on the positive results of previous research [5], we envisage that the OME principles could be applied also when teaching basics of educational data mining and learning analytics. The OME uses the following identifiable steps in the data mining process.