Think instant granular analysis of transcripts. Think about your ability to identify the specific classes and grades indicating future student success. Think about automatically excluding that A in Phys Ed from the overall GPA calculation.
For the sake of speed and efficiency, institutions rely on the overall GPA, an SAT score (if submitted), or the presence of AP classes on a transcript. All helpful shortcuts as indicators of future success, to a point. And we’re not going to get into the SAT debate right now, though we have some strong opinions on that one.
But now, along comes AI and admissions teams are apt to place some hope in the promise of what it can do to streamline unwieldy processes that tend to get in the way of enrollment yield. But there’s so much more edtech can now do.
Opportunities to Meet the Intead Team
- AIEA in March, ASU+GSV in April, and NAFSA in May. We'll be presenting our latest findings with colleagues from Chronicle of Higher Ed, IIE, AIEA, University of Tulsa, University of Memphis, Northeastern, and others. Let us know if you want to connect at any of these events.
Bookmark this: Intead’s Resource Center
Access 800+ articles, slides decks, reports with relevant content on any topic important to enrollment management and student recruiting. Check it out.
In our last post, we highlighted an edtech venture worth watching – especially if you’re among the AI curious. MyDocs is the brainchild of entrepreneur John Reese, whose name you may recognize from Parchment, the company that moved our industry from paper to digital transcripts (PDFs). That little startup originally founded by John grew up and just sold a year ago for more than $800M (all cash). Now, John is taking admissions capabilities a step further – moving institutions beyond digital transcripts into admissions data processing. And last year, he reached out to the Intead team for product launch support.
MyDocs uses advanced OCR (optical character reader) and machine learning to evolve the tedious tasks of transcript analysis and processing. With application volumes rising thanks in part to the student efficiency tool Common App (don’t get us started), this new edtech helps smooth a specific task – and frequent bottleneck – in the admissions process. MyDocs' AI-powered platform scans and analyzes digital transcripts (PDFs, JPEGs, photos) to make them both human and machine-readable.
That means the school of origin and every class, every grade, all become actionable data, instantly. Are you starting to see the possibilities? Oh, and if the transcript happens to be in another language, the tool translates to English.
You can see why we were excited when John approached us and asked for our help with his entrepreneurial approach to transcript evaluation. The data analysis possibilities got the whole team here buzzing.
For institutions, this kind of AI assist is more than welcome. One forward-thinking private New England institution we work with recently used this edtech tool to evaluate and process 11,000 applications in a single day. That’s just one anecdote, but the expediency is something to behold for anyone who’s ever managed admissions processes and credential evaluation. 24 hours vs. 1,500 hours (when done by humans). Something to think about.
On the surface, technology like MyDocs seems like a game-change. Still, a challenge remains: institutions may find they are swimming in data without a clear strategy for leveraging it beyond this singular task of admissions efficiency: accept or reject?
But, we have ideas. So many ideas. Read on…
Streamlining Admissions
Let’s take a step back. A little back of the envelope math will help make the opportunity more real.
Every year, the US sees roughly 3M high school students graduate. Roughly 61% of them enroll in some kind of higher education program. And on average they apply to seven institutions. Anecdotally, we hear stories of students applying to 15 to 20. (Thanks, Common App! You folks do some amazing things and, at the same time, you’ve actually scuttled institutions’ ability to identify student intent, in addition to creating other admissions challenges. But that’s a blog post for another day...)
So, 3M x 61% x 7 = 13M domestic undergraduate applications and transcripts to process.
At the graduate level, roughly 1.5M students start a program and on average they apply to 4 institutions. So, 1.5M x 4 = 6M domestic graduate applications and transcripts to process.
Add to that roughly 300K international students completing an average of 4 applications each and you get another 1M applications and transcripts.
So, our working total is 20M applications and transcripts being processed by US higher ed institutions annually. Again, back of the envelope. Exact figures here won’t change the story.
What if (here’s the entrepreneurial thinking), you could run all 20M applications through an AI-powered tool that digitized absolutely all the data contained there? Yeah, what if that?
Using Admissions Data to Predict Student Success
Our data excitement is growing. So, just imagine having every applicant’s transcript and data at your fingertips. Imagine the ability to know which high school transcripts, which combination of classes and grades pointed to success at different institutions. Are you following the possibilities here?
We could align every student cohort with the coursework that would set them up for graduation and future success. We could align admissions with student resiliency. Retention rates would flourish. Transfer rates would likely drop.
OK, so let go of the 20M applications figure and consider just the applications and transcripts flowing into your institution each year. Let’s consider some concrete examples of the questions you could answer instantly beyond simply looking at a student’s overall GPA or “honors student” status.
Imagine the filters you could set up to find student cohorts with specific combinations of academic experience, instantly.
Let’s start with the simple and then get more invested:
- What is the high school GPA that performs best in our undergraduate business program? What is the undergraduate GPA that performs best in our fintech master’s degree program?
- If a prospective student has a grade of B or better in AP Biology, how likely are they to succeed here regardless of their overall GPA?
- Is there a single high school class that is common to our recent cohorts of successful students?
- If I calculate a student GPA only from their science classes, can I identify a stronger admit benchmark?
- If I calculate a student GPA without counting Phys Ed or other extra curriculars, or only using math classes, or science classes, can I more accurately predict their success here?
- Is there a unique set of high school classes that is common to those students who have graduated in 4 years? In 5 years? In those who fail to complete?
- Which students can we place out of our Gen Ed classes and still see success?
- …and so many other questions important to the health of your academic programs and viability of your institution.
Consider this: you could calibrate your evaluation of every candidate based on the institution they applied from. In other words, if you knew that a set of high schools were more rigorous than others, you might put them into a group where you boost student GPAs by 20% as compared to schools that your experience tells you have lower academic rigor. You are then able to see that a 2.5 GPA from the rigorous set of schools is equivalent to a 3.0 from the less rigorous. You can make these adjustments and filter all applicants en masse with instant results.
This is all about fine-tuning our ability to predict student success based on massive troves of machine-readable data.
Your admissions team just became far more strategic as they evaluate which filters are the true indicators of success. Overall GPA and SAT scores are the old shortcuts. AI analyzed transcripts are the new.
But wait, there’s more on the recruiting edge. This kind of transcript evaluation can be deployed at student fairs and other intake points. A simple photo of a student transcript, uploaded to this tool could put you in a confident position as you instantly answer to the student and parent: “Yes, students like you succeed here. Based on your transcript, we can offer you a conditional admit now along with a scholarship award of $,$$$.”
Imagine the stress relief on the faces of that family across the table from you when you show them the data that supports your admit decision and why you are confident in their future.
Imagine their confidence in their future at your institution.
Need help thinking through how your admissions processes might take a step into the future? Be in touch.
