ARMath

Quick Info

Project Date Jan. 1, 2018 - June 1, 2020
PIs: Jon E. Froehlich (PI)
Sponsors: NSF UW Reality Lab
Keywords: collaborative learning, educational technology, embodied learning, math, tangibles

News

Announcing Dr. Seokbin Kang

Nov 10, 2020 | Jon

Announcing Dr. Seokbin Kang—Seokbin successfully defended his PhD dissertation entitled Augmented Reality Systems and USer Interaction Techniques for STEM Learning." Seokbin is my last UMD CS advisee and it was an enormous honor working with him. Thanks also to the amazing commitee, which included Professors David Jacobs, Tamara Clegg, Huaishu Peng, and David Weintrop.

Four Papers Accepted to CHI2020!

Dec 09, 2019 | Jon

The Makeability Lab had four papers accepted to CHI this year. The acceptance rate was 24% (760 accepts of 3126 submissions). Congrats to the lead PhD students: Steven Goodman (HCDE), Dhruv Jain (CSE), Seokbin Kang (CS), Wendy Roldan (HCDE), and all our wonderful collaborators. Goodman, S., Kirchner, S., Guttman, R., Jain, D., Froehlich, J., Findlater, L. Evaluating Smartwatch-based Sound Feedback for Deaf and Hard-of-hearing Users Across Contexts, CHI2020 Jain D., Mack., K., Amrous, A., Wright, M., Goodman, S., Findlater, L., Froehlich, J. HomeSound: An Iterative Field Deployment of an In-Home Sound Awareness System for Deaf or Hard of Hearing Users, CHI2020 Kang, S., Shokeen, E., Byrne, V., Norooz, L., Bonsignore, E., Williams-Pierce, C., Froehlich, J. ARMath: Augmenting Everyday Life with Math Learning, CHI2020 Roldan, W., Gao, X., Marie, A., Hishikawa, T, Li, Z., Zhang, E., Froehlich, J., Yip, J. Opportunities and Challenges in Involving Users in Project-Based HCI Education, CHI2020 We plan to post the camera-ready versions of the papers and some videos in January!

About

Children using ARMath

ARMath is mobile AR system, which recognizes everyday objects and enacts a life-relevant situation where children can discover and solve math problems. For example, in the image above, a virtual agent presents a story about needing batteries to turn on animated Christmas trees. The children then interactively perform a multiplication problem using tangible manipulatives and AR.

We introduce ARMath, a mobile Augmented Reality (AR) system that allows children to discover mathematical concepts in familiar, ordinary objects and engage with math problems in meaningful contexts. Leveraging advanced computer vision, ARMath recognizes everyday objects, visualizes their mathematical attributes, and turns them into tangible or virtual manipulatives. Using the manipulatives, children can solve problems that situate math operations or concepts in specific everyday contexts. Informed by four participatory design sessions with teachers and children, we developed five ARMath modules to support basic arithmetic and 2D geometry. We also conducted an exploratory evaluation of ARMath with 27 children (ages 5-8) at a local children’s museum. Our findings demonstrate how ARMath engages children in math learning, how failures in AI can be used as learning opportunities, and challenges that children face when using ARMath.