Is predictive analytics a step too far in student assistance?
- The University System of Maryland is using predictive analytics to monitor student behavior and academic performance to better deploy intervention resources for struggling students.
- Some say that knowing how often a student swipes in and out of facilities, uses the library or logs into learning systems trends dangerously close to an invasion of privacy, and could develop consequential effects for future students with similar profiles.
- Privacy advocates argue schools should be more transparent about data usage to more carefully refine outcomes for struggling students.
The concept of academic intrusion isn't novel, but the usage of monitoring technology invites a lot of questions and possibilities for things that can go wrong. Institutions should be extraordinarily careful not to paint a particular type of student with data points on academic performance, without the investment in the human resources to help these students manage the issues which may be causing poor performance.
Factors like how often one visits the cafeteria or swipes into the library could be indicators of how much time a student spends on campus, and since national data show more students are opting out of dorms, they could lead to false correlations.