Carrie Cai

Publications

Carrie J. Cai, Emily Reif, Narayan Hegde, Jason Hipp, Been Kim, Daniel Smilkov, Martin Wattenberg, Fernanda Viegas, Greg Corrado, Martin Stumpe, Michael Terry. Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making. CHI 2019. Best Paper Honorable Mention

Carrie J. Cai, Jonas Jongejan, Jess Holbrook. The Effects of Example-based Explanations in a Machine Learning Interface. IUI 2019. Best Paper Award (short papers)

Been Kim, Martin Wattenberg, Justin Gilmer, Carrie J. Cai, James Wexler, Fernanda Viegas, Rory Sayres. Interpretability beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors. ICML 2018.

Carrie J. Cai, Anji Ren, and Robert C. Miller. WaitSuite: Productive Use of Diverse Waiting Moments. TOCHI 2017.

Pablo Paredes, Nur Hamdan, Dav Clark, Carrie J. Cai, Wendy Ju, and James Landay. Evaluating In-Car Movements in the Design of Mindful Commute Interventions: Exploratory Study. Journal of Medical Internet Research 2017.

Carrie J. Cai, Shamsi Iqbal, and Jaime Teevan. Chain Reactions: The Impact of Order on Microtask Chains. CHI 2016.Best Paper Honorable Mention

Carrie J. Cai. Wait-Learning: Leveraging Wait Time for Education. UIST 2015 Doctoral Symposium.

Elena L. Glassman, Aaron Lin, Carrie J. Cai, and Robert C. Miller. Learnersourcing Personalized Hints. CSCW 2016.

Carrie J. Cai, Philip J. Guo, James R. Glass, and Robert C. Miller. Wait-Learning: Leveraging Wait Time for Second Language Education. CHI 2015. | video

Carrie J. Cai, Philip J. Guo, James R. Glass, and Robert C. Miller. Wait-Learning: Leveraging Conversational Dead Time for Second Language Education. CHI 2014 Extended Abstracts.

Juho Kim, Philip J. Guo, Carrie J. Cai, Shang-Wen (Daniel) Li, Krzysztof Z. Gajos, and Robert C. Miller. Data-Driven Interaction Techniques for Improving Navigation of Educational Videos. UIST 2014.

Juho Kim, Shang-Wen Li, Carrie J. Cai, Krzysztof Z. Gajos, and Robert C. Miller. Leveraging Video Interaction Data and Content Analysis to Improve Video Learning. CHI 2014 Workshop on Learning Innovation at Scale.

Zhen Yue, Eden Litt, Carrie J. Cai, Jeff Stern, Kathy Baxter, Zhiwei Guan, Nikhil Sharma, and George Zhang. Photographing Information Needs: The Role of Photos in Experience Sampling Method-Style Research. CHI 2014.

Carrie J. Cai, Robert C. Miller, and Stephanie Seneff. Enhancing Speech Recognition in Fast-Paced Educational Games using Contextual Cues. Speech and Language Technology in Education 2013.

Carrie J. Cai. Adapting Arcade Games for Learning. CHI 2013 Extended Abstracts 2013.

Anuj Tewari, Ingrid Liu, Carrie Cai, and John Canny. An Analysis of the Dialogic Complexities in Designing a Question/Answering Based Conversational Agent for Preschoolers. Intelligent Virtual Agents. Springer Berlin Heidelberg, 2012.

Projects

Wait-Learning

People who want to casually learn a language are often unable to find time for practice due to many competing priorities. In this project, I introduce the concept of wait-learning: automatically detecting micro-waiting moments and encouraging people to wait-learn desired habits during this time. WaitChatter is an extension of instant messaging that presents learning exercises while a user is awaiting an IM response.

paper (CHI 2015) | video
TechCrunch | Boston Globe | MIT news

WaitSuite

WaitSuite is a suite of diverse wait-learning systems that each target a different kind of waiting moment to encourage micro-productivity. Examples include: waiting for the elevator, waiting for wifi to connect, waiting for email to load, and waiting for instant message replies. In a study conducted on WaitSuite, we found that the kinds of waiting most appropriate for microtasks are ones where the switch time (switching between the primary task and secondary task) is less than the waiting duration, and when cognitive demand is low while waiting.

paper (UIST Doctoral Symposium)

Chain Reactions

This project explores how chains of microtasks can be re-ordered to maximize efficiency, minimize mental demand, and ease people into bigger tasks. We found that high-complexity microtasks are less mentally demanding when chained on the same content, whereas low-complexity microtasks are done more efficiently when chained on the same operation. We also found that medium-complexity microtasks help people start on difficult tasks sooner.

paper (CHI 2016, best paper honorable mention)

Adapting Existing Games for Learning

Although fast-paced arcade games are popular and highly engaging, most educational games are custom-made rather than derived from existing ones. To explore how to modify simple mini-games for learning, I augmented a web-based Tetris game with speech recognition so that a learner could play while practicing word-picture associations: speaking the correct word allows the player to rotate the falling block. The goal of this research is to identify methods for 1) adapting the user interface of fast-paced game interfaces to be more amenable for learning, and 2) enhancing speech recognition by leveraging game context.

paper (CHI EA 2013) | paper (SLaTe 2013) | video