Some of my research as a Ph.D. candidate has involved educational data mining, a relatively new field that (in my opinion) offers exciting possibilities for untangling old questions related to learning.
Educational data mining uses some of the typical data included in state longitudinal databases, such as test scores and attendance, but researchers often spend more time analyzing the detritus cast off during normal classroom data-collection practices, such as student interactions in a chat log or the length of responses to homework assignments—information that researchers call “data exhaust.”
Analysis of massive databases isn’t new to fields like finance and physics, but it has started to gain traction in education only recently, with the first international conference on the subject held in 2008 and the first academic journal launched a year later. Experts say such data mining allows faster and more fine-grained answers to education questions and ultimately might change the way students are tested and taught.
Read more about the Journal of Educational Data Mining here.