Early Prediction of Student Success Using a Data Mining Classification Technique (Mohamed Hegazy Mohamed & Hoda Mohamed Waguih, 2015) https://www.ijsr.net/archive/v6i10/ART20177029.pdf

The above research title is an example of research study that uses educational data mining. The said study applies decision tree algorithms like ID3 and C4.5 to analyze data from engineering students, such as their board exams results, high school performance and entrance exam scores. By analyzing this data, the researchers aimed to identify students who might struggle and provide early interventions. They found that the decision tree algorithms achieved a prediction accuracy of over 75%.

EDM can be of great advantage to educational platforms and even crafting educational programs and policies to improve further the educational system of the country. However, we need to be conscious on how these EDM are being utilized by following the ethical considerations of every data that we are dealing. Data Privacy Act 2012 in the Philippines strongly uphold the privacy of every Filipino people.

But, EDM does not tell all about the totality of learning of the students because there are a lot of factors to consider why such student gain for example a low score in the exam. Maybe that student were not able to study well due to some reasons, maybe not feeling well or going through some personal problems that might affect his state of mind while taking the exam. Therefore, ethics and equity must always be observed when dealing with EDM.