Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief

In depth discussion of how data mining and data analytics can be used for “improving the services they provide and for increasing student grades and retention.”

“Robust applications of educational data mining and learning analytics techniques come with costs and challenges. Information technology (IT) departments will understand the costs associated with collecting and storing logged data, while algorithm developers will recognize the computational costs these techniques still require. Another technical challenge is that educational data systems are not interoperable, so bringing together administrative data and classroom-level data remains a challenge. Yet combining these data can give algorithms better predictive power. Combining data about student performance—online tracking, standardized tests, teacher-generated tests—to form one simplified picture of what a student knows can be difficult and must meet acceptable standards for validity. It also requires careful attention to student and teacher privacy and the ethical obligations associated with knowing and acting on student data.” (from executive summary)