The Discovery of Knowledge in Educational Databases: A Literature Review with Emphasis on Preprocessing and Postprocessing

In educational data mining (EDM), preprocessing is an arduous and complex task and must promote an appropriate treatment of data to solve each specific educational problem. In the same way, the parameters used in the evaluation of postprocessing results are decisive in the interpretation of the results and decision-making in the future. These two steps have as much influence on obtaining good results in EDM as the algorithms used. However, in the dissemination of the results of studies on this topic, emphasis is placed only on the evaluation of the algorithms used. Thus, the present study sought to carry out a systematic review of the literature on this topic, focusing on the exploration of the preprocessing performed and on the metrics for evaluating the results. It is observed in many studies that the description and evaluation of the preprocessing and the use of several metrics to evaluate the algorithms used are negligible. However, without a proper explanation of the meaning of each metric to reach the proposed objective.