Boosting Admissions Efficiency with Machine Learning

When we look back on the last couple years in college admissions, the issue of staff morale will be one of the hallmarks of the post-pandemic era.  That's why I was excited to host this important conversation with Elizabeth Kirby about how - specifically - she was paying attention to this issue for her team.

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The full conversation is available on demand: https://www.crowdcast.io/c/morale

For many admissions teams, FAFSA submissions have traditionally been viewed as a strong signal of student interest. However, in reality, not all FAFSA submissions indicate serious intent to enroll. As competition for students increases, it's critical to re-evaluate how FAFSA data is interpreted, especially in light of the information colleges can't access.

One important data element that has been affected is FAFSA Position, eliminated about a decade ago, which provided insights into where a student listed a particular college relative to others on their application. For years, many institutions used FAFSA Position to infer a student’s level of interest—assuming that being listed first or second meant the student was highly likely to enroll. While this wasn't a formal tool, the position was often treated as an important clue in the enrollment puzzle. However, due to concerns from the Department of Education about how colleges were using this information, FAFSA Position is no longer available. This change forces institutions to rely on other indicators of interest, and it underscores the need to diversify strategies for assessing commitment.

Why FAFSA Submissions Alone Don't Reflect Engagement

While none of us have assumed that every FAFSA submission equals similar levels of intent - this data blindspot has left us no alternative way of measuring this signal by student. Students now apply to more schools than ever before, and many submit FAFSAs to schools they’re considering only as “backup” options. Completing the FAFSA is simply a procedural step for many students, not a declaration of their commitment to attend a particular institution.

As a result, colleges that heavily weigh FAFSA submissions may end up focusing resources on students who have no serious intention of enrolling. Without the added layer of insight from FAFSA Position, schools are left with less context, making it more difficult to gauge genuine interest based on FAFSA data alone.

The Changing Landscape of College Decision-Making

The dynamics of student decision-making have evolved over the years, but FAFSA submissions are no longer a reliable indicator of where a student will eventually commit. In today’s environment, students submit multiple applications and FAFSA forms, often as a matter of precaution rather than as an expression of intent. In this climate, admissions teams need to be more cautious about assuming that FAFSA submissions equate to real interest.

Additionally, the inability to access FAFSA Position means schools can no longer know where they stand relative to other institutions. This lack of visibility into a student’s preferences highlights the growing importance of using additional methods—such as behavioral data, engagement metrics, and predictive modeling—to better understand and prioritize students who are truly interested in enrolling.

Prioritizing Engagement Over FAFSA Data

The shift away from relying on FAFSA Position presents an opportunity for admissions teams to reframe how they assess student intent. Rather than focusing on FAFSA submissions as a primary indicator, schools should shift their attention to other forms of student engagement. Metrics such as website visits, participation in virtual tours, attendance at campus events, and interactions with admissions officers can provide far more reliable insights into a student’s commitment to your institution.

In addition, colleges can leverage machine learning and predictive analytics to better understand how engagement behaviors correlate with enrollment decisions. By analyzing patterns in student interactions—such as the frequency of communication, the types of inquiries made, or the timing of their engagement—admissions teams can develop a more nuanced understanding of student intent. These insights help schools prioritize their outreach efforts toward students who are most likely to matriculate, rather than relying solely on the submission of financial aid forms.

Diversifying Your Approach to Student Commitment

The end of FAFSA Position data had forced an abandonment of nuance in interpreting the signal of FAFSA submissions. The rise of high-level data science now allows for a reassessment of how colleges interpret FAFSA submissions, making it clear that this form alone should not be the main driver of admissions decisions. While FAFSA remains an important part of the financial aid process, it is no longer a reliable indicator of student commitment. By focusing more on engagement behaviors and leveraging data-driven insights, admissions teams can make smarter, more informed decisions about how to allocate their resources and shape their admit pool.

In today’s competitive landscape, relying on a single metric—like FAFSA—can result in missed opportunities and misallocated efforts. Schools that embrace a broader, more holistic approach to understanding student commitment will be better equipped to build strong, resilient incoming classes.

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If there’s one takeaway from the AI buzz at NACAC, it’s that while robots aren’t going to be reading your transcripts or taking over your job anytime soon, they can certainly help make it easier. Let’s face it, AI is not the admissions counselor of the future—but it can be the best assistant you’ve ever had. Imagine having a tool that frees you up from guessing games, helps you focus on the right students, and gives you the confidence to approach each interaction with clarity.

But as we wrap up this series, let's look ahead: How will AI continue to reshape admissions? Spoiler alert—it’s not about robot overlords writing your acceptance letters. It’s about making your job more effective, efficient, and, dare we say, a little bit more enjoyable. Here’s how.

AI Enhances Your Expertise, Not Replaces It

At this point, we’ve debunked the myth that AI is coming to steal your job. Instead, AI is here to help you shine. Think of AI as your trusty sidekick, the Robin to your Batman. You’ve got the people skills, intuition, and experience—AI just gives you the data to back up your instincts. By analyzing student behavior and predicting outcomes, AI lets you make smarter decisions, faster.

Imagine knowing exactly when a student is ready to apply or needs a gentle nudge. Instead of wasting time on broad, generic communications, AI helps you focus on personalized, data-driven outreach that matters. You still get to build relationships with students; AI just makes sure you’re doing it at the right time with the right message.

A Future with More Fun, Less Guesswork

One of the greatest things about AI is that it takes the guesswork out of your day-to-day tasks. No more wondering whether a student is serious about applying or what message will resonate. AI has done the heavy lifting, analyzing behavior patterns, predicting next steps, and flagging the students who need your attention most. What does that mean for you? Less time staring at spreadsheets and more time doing the part of the job you love—actually connecting with students.

And let’s be real: AI can also spare you some of the more tedious parts of the job. Did a student suddenly go quiet after showing early interest? AI can tell you when to re-engage, so you're not left in the dark. It’s like having a crystal ball for admissions, except without all the mysterious fog.

The Human Touch Still Matters

As we look to the future, one thing is certain: the human touch will always matter in admissions. Sure, AI can help pinpoint student needs, predict behavior, and personalize outreach, but it can’t replace the empathy, understanding, and personal connection that admissions professionals bring to the table. AI doesn’t get excited about campus tours, and it won’t cheer when a student gets accepted—that’s all you.

AI gives you the insights, but you get to make the magic happen. The future of admissions is not about choosing between humans and machines—it’s about leveraging AI to help you be the best counselor you can be.

The Best of Both Worlds

So, what’s the future of AI in admissions? It’s not about replacing people—it’s about creating a seamless partnership where AI takes care of the data crunching, and you focus on what really matters: building relationships and supporting students as they navigate their educational journey.

In the end, AI isn’t about making things colder or more robotic; it’s about freeing up your time and making your job more human. The future of admissions is brighter (and more efficient) with AI by your side. So go ahead, embrace the partnership—and maybe even have a little fun while you’re at it.

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