Effective Personalization: Student Mindsets Matter Most

By Keith P. O’Brien

8 minutes estimated time to read

Part two  of a two-part series

Summer melt remains a persistent issue for heads of enrollment at colleges and universities. Even a few admitted students failing to turn up or dropping out can undermine headcount, academic profile, diversity, and tuition revenue objectives. Admitted students choose one college over another for an array of reasons; institutions that demonstrate they “get” the student on some personal level tend to win out. Personalizing outreach and interactions builds affinity and mitigates melt.  My previous blog proposes that the most effective personalization aligns to a student’s attitudes. The following case study shows how one university engaged student attitudes to cut FAFSA verification melt..

What is Verification Melt?

“Each year, approximately one in three aid applicants gets another chore. The U.S. Department of Education requires millions of new and returning students to submit additional information to colleges, which then must verify the accuracy of each FAFSA flagged for review. Students must comply to get their money. If you haven’t been through the time-consuming procedure, then you’re probably not poor.”   — Eric Hoover, Chronicle of Higher Ed

The federal government requires every institution to verify selected student’s FAFSA information. Verification melt occurs when students fail to initiate or complete this (laborious) process and don’t qualify for Title IV grants and loans. Underrepresented and first-generation students are disproportionately affected

Case Study: Identifying Student Mindsets    

At the university, 150 students from the Fall 2019 cohort were selected for FAFSA verification. The VP for Financial Aid partnered with Discourse Analytics (DA) to help these students—the target population—complete the process and enroll.  DA used a four-step process to profile the attitudes of these students towards verification and develop nudges targeting these attitudes.)

1. Use existing student data as indicators for attitudes: for each student in the target population, DA’s artificial intelligence (AI) platform ingested 18 data fields from the CRM (Slate) and financial aid software (PowerFAIDS). These data included the number of AP classes; household debt to income ratio; and social club participation. No Personally Identifiable Information (PII) was used.
2. Pinpoint each student’s attitudes: the AI-platform evaluated 12 non-cognitive attributes (capacity, growth mindset, proactivity, resiliency, self-awareness, self-confidence, self-discipline, social intelligence, comfort with technology, etc.) to create an attitudinal profile of every student. The profiles pinpointed a student’s attitudes that drive their behavior regarding FAFSA verification.
3. Cluster like-minded students: DA’s “Think-alike” engine identified three clusters of students with shared mindsets. Each mindset cluster predicts how its students will behave and prescribes nudges towards the desired action. Clustering enables personalization at scale by tailoring interventions to shared mindsets. (See Exhibit for details of one mindset cluster.
4. Nudge student mindsets: DA and Financial Aid created nudges for each mindset cluster. The nudges help students make better decisions for themselves by changing the context in which they make choices. The nudges were sent via the university’s email platform to streamline access to students and maintain confidentiality. DA’s platform uses machine learning to assess student responses and continuously refine the mindset clusters; each nudge shapes attitudes so re-calibration is essential. 

Motivating Student Attitudes Boosts FAFSA Verification

DA created a randomized control group of students going through verification to benchmark the results. The target group students receiving attitudinal nudges were much more likely to complete verification: 25% increase versus the control group.  

The Personalization Imperative

Consumer habits shape a student’s approach to decision making: how to parse information sources, consider options, and make choices. This consumer orientation and its expectations around responsiveness, convenience and personalization will rarely, if ever, cease at the campus gate, or on the college website. And students’ needs are increasingly distinct as societal and demographic trends blur the distinctions between traditional and nontraditional students. Institutions serve cohorts with highly disparate characteristics and needs: using personalization has become a non-negotiable for every institution, from the most selective to open access.

Data are indispensable for personalization and institutions have ever-growing data sets for the entire student lifecycle. AI and data science grant universities the opportunity to turn student data into attitudinal profiles and deliver personalization at scale—the right mindset message on the right channel at the right time. Attitudinal personalization helps an institution rise above today’s buyers’ market by boosting student and institutional outcomes. 

Two free resources to learn more about:

1. Personalization, mindsets, the FASA Verification project, and AI’s game-changing potential:  download Discourse Analytics’  free eBook, Artificial Intelligence and Higher Ed
2. How attitudes, “think-alike” mindsets and nudging drive human decision making: get our free whitepaper,  Why Attitudes Drive Decision Making: Reimagining Personalization