At one elite university, over 80% of students currently use AI, but it's not just about outsourcing their work

More than 80% of Middlebury University students use generated AI for their coursework, according to a recent survey conducted with colleagues and economist Zara contractors. This was one of the fastest technology adoption rates on record, far surpassing the adoption rate of 40% of US adults, and less than two years after ChatGPT's release.

We investigated only one university, but our results are consistent with similar research and provide new photos of the use of technology in higher education.

Between December 2024 and February 2025, we surveyed over 20% of Middlebury College student organizations (634 students) to better understand how students use artificial intelligence and publish the results in a working paper that has not yet been peer-reviewed.

What we find challenges the panic-driven narrative of AI in higher education, suggesting that institutional policies should instead focus on how AI is used.

It's not just homework

Contrary to the surprising headlines that suggest “ChatGpt unraveled the entire academic project” and “AI fraud is getting worse,” students have found that rather than using AI primarily to enhance learning, rather than avoiding work.

When I asked students about 10 different academic uses of AI, concept descriptions and proofreading summary, programming code creation, and yes, even writing essays, the concept tops the list. Students frequently described AI as “on-demand tutors.” This is a resource that was especially valuable when opening hours were unavailable or when you needed immediate help late at night.

AI usage was grouped into two types. It describes “enhancement” and describes usages that enhance learning and “automation” that generates work with minimal effort. 61% of students using AI use these tools for augmentation purposes, while 42% use them for automated tasks such as writing essays and generating code.

They also showed judgment, even if students used AI to automate tasks. Open-ended responses said that when students automate their work, they often have low-stakes tasks, such as bibliographic formatting or drafting regular emails, rather than the default approach to completing meaningful coursework during crunch times like exam week.

Of course, Middlebury is a small liberal arts college, with a relatively large majority of wealthy students. How about anywhere else? To investigate, we analyzed data from other researchers covering over 130 universities in over 50 countries. The results reflect Middlebury's findings. Globally, students using AI tend to be more likely to use it to increase coursework rather than automate it.

But do you need to trust that students will teach you how to use AI? An obvious concern with research data is that students overreport legitimate uses that get explanations while underestimating what they deem as inappropriate, like writing an essay. To examine the findings, they were compared with data from humanity from AI companies. This analyzed actual usage patterns from the chatbot's Claude AI university email address.

Anthropic's data shows that “technical explanations” represent a major application, consistent with the finding that students most often use AI to explain concepts. Similarly, Anthropic found that by designing practice questions, editing essays, and summarizing the material, it constitutes a significant portion of student use that matches the results.

In other words, our self-reported survey data matches the actual AI conversation log.

Why is it important?

As author and academic Hua HSU recently stated, “There are no reliable numbers for American students using AI. It's just a story about how everyone is doing it.” These stories tend to highlight extreme examples, like Columbian students who used AI to “deceive almost every assignment.”

However, these anecdotes can confuse widespread adoption with universal misconduct. Our data confirms that the use of AI is indeed widespread, but students do not primarily use it to enhance learning and replace it. This distinction is important. By portraying all AI use as fraud, vigilance coverage can normalize academic injustice, and responsible students feel naive in following the rules when they believe “everyone else is doing that.”

Furthermore, this distorted image provides biased information for university administrators who need accurate data on actual student AI usage patterns to create effective evidence-based policies.

What's next?

Our findings suggest that extreme policies, such as the ban on blankets and unlimited use, are risky. The ban can disproportionately hurt students who benefit most from AI's tutoring capabilities, while creating unfair benefits for rule breakers. However, unlimited use may allow harmful automation practices that can undermine learning.

Instead of a policy of all sizes, our findings will lead us to believe that institutions should focus on helping them distinguish between potentially harmful and beneficial AI use. Unfortunately, research on the real impact of AI on learning remains in the early stages. Research I know systematically tested how different types of AI use affect students' learning outcomes, or whether the impact of AI may be positive for some students but negative for others.

Until that evidence becomes available, everyone interested in how this technology is changing must use their best judgment to determine how AI can promote learning.

This article will be republished from the conversation under a Creative Commons license. Please read the original article.