Individualized Math Learning Through Post-Exam Reflection
Math exams are more than a snapshot of what students know at a given moment. They
can become powerful learning tools when students revisit their mistakes and engage
deeply with the material. At the University of Utah, Associate Professor Rebecca Noonan-Heale
from the Department of Mathematics is using AI to make this process more meaningful
and accessible.
Turning Exams into Learning Opportunities
In Rebecca’s classes, students complete a post-exam extra credit assignment where they analyze the mistakes they made. Part of the assignment involves having a conversation with a chatbot about the problems they missed. Suggested prompts are provided to help students explore the concepts in greater depth. This approach encourages reflection and active learning rather than simply moving on to the next topic.
In Rebecca’s classes, students complete a post-exam extra credit assignment where they analyze the mistakes they made. Part of the assignment involves having a conversation with a chatbot about the problems they missed. Suggested prompts are provided to help students explore the concepts in greater depth. This approach encourages reflection and active learning rather than simply moving on to the next topic.
Two Classes, Two Approaches
Rebecca is running this assignment in two different classes. One class has access to UBot and has been using it throughout the semester. The other class does not have UBot access, so students are instructed to discuss their exam with a knowledgeable friend, tutor, teacher, classmate, or an AI tool of their choice. Observing the differences in these conversations offers valuable insight into how students interact with AI compared to human peers.
Rebecca is running this assignment in two different classes. One class has access to UBot and has been using it throughout the semester. The other class does not have UBot access, so students are instructed to discuss their exam with a knowledgeable friend, tutor, teacher, classmate, or an AI tool of their choice. Observing the differences in these conversations offers valuable insight into how students interact with AI compared to human peers.
Why It Works
Students benefit from individualized attention, but in large classes, providing one-on-one feedback can be challenging. This assignment gives every student the opportunity to receive personalized guidance in a manageable way for the instructor. It also supports students who may be shy or unable to attend office hours, ensuring they still have access to meaningful feedback.
Students benefit from individualized attention, but in large classes, providing one-on-one feedback can be challenging. This assignment gives every student the opportunity to receive personalized guidance in a manageable way for the instructor. It also supports students who may be shy or unable to attend office hours, ensuring they still have access to meaningful feedback.
Early Results and Collaboration
Anecdotally, students who participate appear to have a better grasp of their mistakes and the underlying material. Rebecca, who serves as a course coordinator, is sharing this template with other instructors and refining it based on student responses. While this is a small project, it is proving to be a useful teaching tool that enhances learning during the semester.
Anecdotally, students who participate appear to have a better grasp of their mistakes and the underlying material. Rebecca, who serves as a course coordinator, is sharing this template with other instructors and refining it based on student responses. While this is a small project, it is proving to be a useful teaching tool that enhances learning during the semester.
For more information, contact: rebecca@math.utah.edu