Dive Brief:
- A web-based collaborative annotation tool developed by MIT professor David Karger creates a wealth of data in student posts that a team at Ben-Gurion University of the Nagev in Israel have begun to parse for predictive power.
- According to eCampus News, the Israeli team used machine learning to analyze student posts from one course, using their comments to predict where future students may have trouble, giving faculty a chance to clarify points before they become a problem.
- The project stems from a BGU-MIT International Science and Technology Initiative Seed Fund the two universities launched last year to enhance collaboration among researchers at the two institutions.
Dive Insight:
Colleges and universities are finding nearly infinite uses for data analytics as they face pressure to improve student outcomes. More than half of the states now allocate higher education funding based on performance, not just enrollment. This has contributed to the rush of new programs backed by data analytics, including early warning systems that track student engagement and progress to give faculty, staff, and students themselves an assessment of expected success in a course.
Ivy Tech, like many schools, is using data analytics in all parts of the organization, finding ways to track faculty outcomes and financial aid fraud, among other things. Pressure to reduce the costs of higher education will not soon fade, giving colleges and universities strong motivation to use data analysis to improve efficiency. In many cases, the data is already being collected; administrators just need to develop ways to analyze it.