CURI AI Tutor Voice Agent

Exploring how a voice-based adaptive tutoring agent can provide one-to-one instruction
Role: UX Research
Team: Gen Marconette & Grace Kim (Instructional design), Roza Atarod (UX design)
Duration: 3 months (Jan - May 2021)
Tools: Figma and Voiceflow (for prototyping), Zoom (to conduct usability study)
This research aimed to explore how a voice-based adaptive tutoring system may close the equity gap for access to human tutors by providing one-to-one instruction. This was a class project from the Human-AI Interaction course in the School of Information at UT Austin taught by Dr. Min Lee.
Personalized 1-on-1 learning is inaccessible.
A lot of accessible, cost-friendly learning platforms right now are 1-to-many, such as videos on Khan Academy. Meanwhile, human tutors that provide 1-on-1 guidance can be very expensive and geographically inaccessible.
To address the weaknesses of both methods of learning, we looked to AI as a way that can provide 1-on-1 help anywhere at anytime.
Improve a learner's motivation, self-efficacy, and metacognition of learning through an AI tutor
Read the final report:
AI Tutor Report.pdf
1.9 MB

Want to print your doc?
This is not the way.
Try clicking the ⋯ next to your doc name or using a keyboard shortcut (
) instead.