Using sequential pattern mining to increase graph comprehension in intelligent tutoring system student data (abstract only). - Aaron Springer; Matthew W. Johnson 001; Michael Eagle; Tiffany Barnes (SIGCSE, 2013)

QuickResponseHost: Enabling crowdsourced disaster response stations. - Rakshit Agrawal; Aaron Springer; Emily Lovell (GHTC, 2015)

Dice in the Black Box: User Experiences with an Inscrutable Algorithm. - Aaron Springer; Victoria Hollis; Steve Whittaker 001 (AAAI Spring Symposia, 2017)

What Does All This Data Mean for My Future Mood? Actionable Analytics and Targeted Reflection for Emotional Well-Being. - Victoria Hollis; Artie Konrad; Aaron Springer; Matthew Antoun; Christopher Antoun; Rob Martin; Steve Whittaker 001 (Hum. Comput. Interact., 2017)

Assessing and Addressing Algorithmic Bias - But Before We Get There... - Aaron Springer; Jean Garcia-Gathright; Henriette Cramer (AAAI Spring Symposia, 2018)

What Are You Hiding? Algorithmic Transparency and User Perceptions. - Aaron Springer; Steve Whittaker 001 (AAAI Spring Symposia, 2018)

"Play PRBLMS": Identifying and Correcting Less Accessible Content in Voice Interfaces. - Aaron Springer; Henriette Cramer (CHI, 2018)

"I had a solid theory before but it's falling apart": Polarizing Effects of Algorithmic Transparency. - Aaron Springer; Steve Whittaker 001 (CoRR, 2018)

Progressive Disclosure: Designing for Effective Transparency. - Aaron Springer; Steve Whittaker 001 (CoRR, 2018)

Assessing and addressing algorithmic bias in practice. - Henriette Cramer; Jean Garcia-Gathright; Aaron Springer; Sravana Reddy (Interactions, 2018)

Mood modeling: accuracy depends on active logging and reflection. - Aaron Springer; Victoria Hollis; Steve Whittaker 001 (Pers. Ubiquitous Comput., 2018)

Enabling Effective Transparency: Towards User-Centric Intelligent Systems. - Aaron Springer (AIES, 2019)

Translation, Tracks & Data: an Algorithmic Bias Effort in Practice. - Henriette Cramer; Jean Garcia-Gathright; Sravana Reddy; Aaron Springer; Romain Takeo Bouyer (CHI Extended Abstracts, 2019)

Progressive disclosure: empirically motivated approaches to designing effective transparency. - Aaron Springer; Steve Whittaker 001 (IUI, 2019)

Making Transparency Clear: The Dual Importance of Explainability and Auditability. - Aaron Springer; Steve Whittaker 001 (IUI Workshops, 2019)

Accurate, Fair, and Explainable: Building Human-Centered AI. - Aaron Springer (2019)

Progressive Disclosure: When, Why, and How Do Users Want Algorithmic Transparency Information? - Aaron Springer; Steve Whittaker 001 (ACM Trans. Interact. Intell. Syst., 2020)

Scaffolding the Mastery of Healthy Behaviors with Fittle+ Systems: Evidence-Based Interventions and Theory. - Peter Pirolli; G. Michael Youngblood; Honglu Du; Artie Konrad; Les Nelson; Aaron Springer (Hum. Comput. Interact., 2021)

Recommending Activities for Mental Health and Well-Being: Insights From Two User Studies. - Darius A. Rohani; Aaron Springer; Victoria Hollis; Jakob E. Bardram; Steve Whittaker 001 (IEEE Trans. Emerg. Top. Comput., 2021)