Project Rationale
Declining enrollments and high attrition rates of undergraduate students at a U.S institution's School of Information Technology (IT) has resulted in increased pressure on faculty to become more actively involved in identifying at-risk students and choosing and initiating appropriate interventions. The decision support system (DSS) proposed herein will provide those responsible for retention with the business intelligence they need to make timely and effective intervention decisions.
The Present Decision Making Process
The present decision making process relevant to retention and intervention activities is ineffective for several reasons. First, a faculty member typically only becomes aware of an at-risk situation when a student stops participating and has already fallen behind. Oftentimes it is too late to do any meaningful outreach.
Second, a student advisor gets involved only when a student contacts him or her directly or when a student fails to respond to a faculty’s outreach attempt. In such cases, the faculty informs the student’s advisor who presumably makes further attempts to intervene. At this stage, relatively few intervention attempts are successful (an assumption if the advisor never gets back with the faculty) and those that are successful generally result in requesting that the faculty extend due dates and, if necessary, issue the student an incomplete. Few students who have been granted incompletes actually complete the course.
Third, advisors are typically better informed about students’ personal situation than faculty. Under the Federal Educational Rights and Privacy Act (FERPA), sharing of student data is restricted to a need to know basis. Consequently, advisors do not necessarily share what they know about a potentially at-risk student with faculty, such as past academic performance, financial and health issues, and other personal problems; and faculty members are not permitted to elicit such personal information directly from a student whether or not he or she is deemed to be at-risk. A faculty member only becomes privy to a student’s personal situation if the student voluntarily shares it.
The Problem
The problem is that faculty and advisors need actionable intelligence if they are to be held accountable for retention. In addition, in order for them to effectively make decisions on how to best support at-risk students and choose intervention strategies, they need this intelligence way before the student reaches the point of no return. Lack of collaboration and little to no understanding of the factors that drive retention and influence a student’s at-risk status exacerbate the problem.
Objectives of the DSS
The objectives of the proposed DSS is to predict attrition and identify those students who are most likely to drop-out using pre-defined risk factors known to influence attrition. Examples include factors related to the student’s financial status, pre-college education, post-secondary academic performance, and extra-curricular obligations.