Students offered an AI tutor got lower grades and disengaged from course materials, University of Maryland trial finds
A large University of Maryland trial has produced a striking result for universities rolling AI into teaching: students offered a course-integrated AI tutor performed worse in matched classes and engaged substantially less with existing course materials.
The randomized study involved 2,379 undergraduate students and 30 instructors across multiple disciplines during fall 2025.
In the clearest comparison, between sections of the same course, students given access to the AI tutor finished around four percentage points lower in their final grades, equivalent to 0.37 standard deviations.
Their use of the university’s learning management system dropped even more sharply. Recorded participation fell by 0.90 standard deviations, while page views and active days also declined.
One detail makes the result particularly interesting: only around 15% of students offered the tutor actually used it.
The researchers say introducing an approved AI tool into a course may also have changed how students approached other learning activities and their wider use of generative AI.
Most students used the AI for answers, not tutoring
The University of Maryland’s Virtual Study Assistant was built into the university learning platform and powered by GPT-4o.
It used retrieval-augmented generation, or RAG, to draw primarily on course materials selected by individual instructors. In practical terms, that meant students could ask questions inside their course and receive responses grounded in materials such as lecture content and readings.
But how students used it is revealing. Nearly 74% of requests were for information, explanations or solutions. Around 11% involved practice or test preparation, while fewer than 1% asked the tutor to give feedback on a student’s own attempt.
So although the tool was presented as a study assistant, students were much more likely to ask it for an answer or explanation than to use it as a back-and-forth tutor.
Jing Liu, Associate Professor and Director of the Center for Educational Data Science and Innovation and lead author of the paper, stressed on LinkedIn that the findings should not be read as evidence against all AI tutoring.
“These findings do not establish that purpose-built AI tutoring tools are not beneficial,” he wrote.
Instructors could choose between a direct instruction mode, which provided more explicit answers and explanations, and a tutoring mode designed to guide students toward an answer. Most retained the default direct instruction setting.
...