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This Week in Student Success
Frictions, foundations, and first-gen futures

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This week, I mostly found myself questioning why I chose to launch a new newsletter during a week shortened by a public holiday. Instead of writing, I spent Monday baking a cake and bringing it to a party. Admittedly, the cake was a hit. It was a Lazy Daisy cake (with an unpronounceable Danish name) that’s quickly becoming the ur-cake in my household and among my friends.
But what happened in student success?
Pulp frictions
A new National Bureau of Economic Research (NBER) paper by Esteban Aucejo, Jacob French, Paola Ugalde Araya, and Basit Zafar argues that first-generation status (being the first in a family to attend college) explains more about student attrition than any other factor—including socioeconomic status or prior academic preparation.
The evidence is stark. NCES data show that first-generation students are far less likely to earn a bachelor’s degree within six years at a four-year institution: just 44%, compared to 74.3% of their continuing-generation peers.
To explain this, Aucejo and colleagues draw on an innovative survey panel of 145,000 first-time students at Arizona State University and propose a new framework: information frictions. In their view, first-gen students don’t just lack resources, they lack the insider knowledge needed to navigate the university system. I love this phrase (I may start saying I missed meetings due to “information frictions”). Joking aside, it’s a useful way of framing the problem.
The mechanism the authors highlight is major switching. Their data suggest that first-gen students who earn poor grades early on are more likely to drop out, while continuing-generation students in the same situation tend to switch majors and persist. The difference? First-gen students often don’t know that switching majors is a viable option, or what it entails. The authors explain the problem.
some first-generation students are dropping out prematurely, even though they might have successfully pursued a different major
The information frictions that hinder students’ ability to navigate the bureaucracy and logistics of college are multifaceted. The authors define them as follows.
Compared to continuing-generation students, they [first generation students] : (1) arrive with more biased and overly optimistic expectations, (2) revise their beliefs downwards more over time, (3) adjust more aggressively to similar GPA expectation shocks, (4) hold greater uncertainty about their future grades, (5) are less likely to anticipate switching majors and perceive greater similarity in expected earnings across majors, and (6) possess smaller social networks with fewer sources of informed guidance.
To test this theory, the paper examines ASU’s LEAD program (Learn Explore Advance Design), designed for first-time students with weaker incoming academic credentialsa group that disproportionately includes first-gen students. LEAD participants take smaller, interactive courses, earn required credits in a more supportive environment, and receive mentoring alongside soft-skill development. The results are clear: students in LEAD persist at higher rates and switch majors more often, lending strong support to the “information friction” hypothesis.
We do all at some level know that a good part of why students dont succeed is because they have trouble navigating the system. But this research does help prove that and add some detail to our hunch. It is also a compelling framing. But I see at least two blind spots.
First, self-belief. Many first-gen students doubt whether they belong in college at all. Early poor grades can confirm those doubts and push them toward leaving, regardless of whether they know switching majors is an option. We see a similar dynamic with early alert systems, where some students interpret “you’re at risk” not as a call to action but as confirmation that they don’t belong. This dimension of confidence and belonging deserves more attention than the paper gives it.
Second, scalability. Programs like LEAD are impressive, but they are resource-intensive. My concern is the same one I have with ASAP programs: they succeed by changing everything, smaller classes, intensive advising, extra supports, and unsurprisingly, outcomes improve. But this is like saying I’m terrible about going to the gym (true) but would get fit if you built me a personal gym at home and sent a trainer by daily who refused to take no for an answer. As they say in The Simpsons, “well, duh.” This point is made compellingly in the book Redesigning America’s Community Colleges and More Essential Than Ever (which I think of as the Community College Book and Son of Community College Book). What we need are scalable approaches that can be implemented widely without completely overhauling the system.
All that said, the “information frictions” framing is a significant step forward in how we think about the first-gen challenge. The real test will be whether institutions can reduce those frictions at scale without relying solely on boutique, high-touch programs.
A different route
In a post I wish I had written, Josh Brake from The Absent-Minded Professor takes aim at how we think about AI literacy.
I have some real concerns with the way AI literacy is currently conceptualized and discussed. Two aspects, in particular, trouble me.
First, much of what currently passes for AI literacy seems better described as teaching students to use AI. To me, a critical component is inherent in the concept of literacy: it’s not just about being able to use something, but also about making good choices and distinguishing between better, good, and bad uses. That dimension seems largely missing.
Second, AI literacy is often wielded like a vaccine, or a “get out of jail free” card, as though it eliminates the need for further critical questioning of AI. The implication seems to be that if we simply “inoculate” students with some AI literacy, everything will be fine.
I’m not opposed to AI literacy; far from it. I just don’t think the current conversations around it are fit for purpose.
That’s why I enjoyed Josh’s post, in which he uses the analogy of F1 drivers learning to master the art of piloting powerful cars around the track
Perhaps the way F1 drivers prepare to drive the fastest race cars in the world has something to offer us in the other areas where we are preparing students to thrive.
[snip] a Formula One car is an amplifier for driving ability. To squeeze out every last drop of performance from the car requires an incredible amount of skill. Any small mistake is magnified and any weaknesses in the driver's racing fundamentals get exposed.
So to train kids to drive in Formula 1, we expose them as early as we can to F1 cars, right? Wrong. If you look at the stories of almost all of the current crop of F1 drivers, you'll start to see a familiar pattern in their journeys to the F1 paddock. Almost without exception, they started out karting as kids.
At first glance, you may think that karts are just a scaled-down version of F1 cars. Much less powerful, but the same basic idea.
The karts are designed to strip away some of the more technical aspects that are a part of more advanced stages of racing to narrow the focus on the fundamental skills that are the cornerstone of a successful driver.
Similarly, with AI, literacy isn’t something that naturally develops through use, it has to be intentionally cultivated.
What students most desperately need [snip] is not some new courses about how LLMs work or a totally revamped curriculum that embraces LLMs throughout their cognitive processes. What they need is a renewed focus on the patterns of thought and habits that build true human intelligence and the wisdom to understand how to engage well with intelligence amplifiers [such as AI] and the distortions that are part and parcel of how they work. It might seem like a subtle point, but it has a significant influence on when and where we introduce generative AI into our teaching
Josh identifies these patterns of thought and wisdom as qualities such as “curiosity, reasoning, resourcefulness, determination, integrity, honesty, teamwork, communication, and empathy, among others.”
I think this is absolutely right, but I do have a couple of points of disagreement and one area of concern.
Concern. Josh frames these patterns of thought and wisdom as virtues. I don’t like that phrasing, and I think it weakens the argument. “Virtues” as a term carries baggage: your virtue may not be mine, and too often, people’s rights have been infringed in the name of virtue. I believe we should call these qualities what they are, fundamental skills.
Questions. How can we best cultivate these skills in an intentional and effective way? And what do we need to do differently in this age of AI, when the ways we acquire, use, and share knowledge are shifting? Surely those changes affect the development of these fundamental skills as well.
Maybe that brings me back to where I started, but it underscores the point: these are conversations we need to be having.
From replica to redesign
Wendy Palmer, over at Lifelong Learning Edge, published a post this week contrasting the traditional on-campus student experience with a learner experience that is “efficient, affordable, and focused on their goals.”
Her reflections were sparked by questions about the cost of online learning.
if online learning is outpacing campus enrollments, then it is time to rethink what we are really offering. Do online learners want us to replicate the campus experience virtually? Or do they simply want a high quality learning experience that is efficient, affordable, and focused on their goals?
This opens up new models. We could design a baseline online learning experience, curriculum, academic support, digital library, priced more accessibly. Then offer additional services as opt-ins for additional fee. Some learners might choose virtual networking, wellbeing support, or even digital fitness programs. Others will simply want to get on with the learning.
I think Wendy is absolutely spot on in arguing that we shouldn’t simply replicate the on-campus experience with a virtual (and usually inferior) online experience. The two need to be distinct.
That said, I disagree with her on two points.
First, student supports. While not every student needs every support service, it’s hard to predict when a student will need help, and students aren’t always the best judges of what they need. I’ve seen this play out too often with institutions in fee-for-service OPM contracts. To cut costs, they reduce student support, only to pay the price later in low retention and graduation rates.
Second, the scope of learning. Learning is about far more than courses alone. It can’t be contained within a formal curriculum; it happens through a wide range of experiences, and its value often emerges in unexpected ways. We would be selling online students short if we narrowed learning to a purely course-based definition.
Still, we need to rethink the online learning experience from the ground up, rather than treating it as a digital replica of the on-campus student experience.
Musical coda
This week I’ve been thinking a lot about open universities, including the University of South Africa (UNISA), where I began my higher education career. An earlier draft of this post included a discussion of retention in open universities, which I cut for brevity—I’ll save that for another time.
When I worked at UNISA in the late 1980s, it was a period of intense political change, but also a time when many were working to reclaim Afrikaans from its association with apartheid and oppression. This effort was especially visible in poetry, literature, and music.
I remember one evening at the laundromat, where I spotted a hand-drawn poster for a band called Johannes Kerkorrel and the Gereformeerde Blues Band. I went to the concert, and they were among the groups using music to reclaim Afrikaans. They went on to become big.
This is one of their more upbeat, less cynical and critical songs. But it is also bone-crushingly depressing, including the line.
We survive with a lot of pain in this country.
Enjoy.
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