Educational Data Mining is a field of researcg specialize on collecting, analyzing, and interpreting large sets of educational data. It focuses on discvering patterns in educational data to better understand learning and improve instruction. The following are the possibilities provided by Educational data mining; detection of learning difficulties, personalized learning, improved instruction and curriculum design, supports continuous feddback, and policymakers can make informed decisions using the mined data. The issues may arise due to privacy and ethical concerns of the data collected. It can also shows biases disadvantaging certian group of people, and implementing requires resources and teacher training that may not be available.

Find a piece of research that uses educational data mining as a source of evidence. What kinds of things can educational data mining tell us, or not tell us?

Yagci, M. (2022). Educational data mining: Prediction of students' academic performance using machine learning algorithms. Smart learning Environments, 9(11).

In this research, the researcher applies machine learning and data mining algorithms to a dataset of undergraduate student records to predict final exam performance based on earlier indicators such as midterm grades, department, and faculty data. It achieves 70-75% classification accuracy and it is used to identify students at risk of poor performance.