Benjamin Xie he/they

Postdoctoral Scholar

University of Washington Information School

I design for data equity.

👋 I’m on the job market! Seeking postdoc or research scientist opportunities related to equitable interactions with data. Learn about my research interests.

I am a postdoc at the University of Washington Information School, advised by Prof. Amy J. Ko in the Code & Cognition Lab. My research interest is in designing interactive tools that support equity in computing education by contextualizing data about students with data from students.

During my PhD, I was a National Science Foundation (NSF) Graduate Research Fellow and also a research intern at non-profit Code.org. I was an MIT EECS-Google Research and Innovation Scholar during my time as a student at MIT researching with Prof. Hal Abelson and MIT App Inventor.

For more information, see about me, projects, or CV.

Interests

Human-Computer Interaction (HCI)
Computing Education
Critical Data Studies
Artificial Intelligence in Education
Psychometrics

Education

PhD in Information Science, 2021
University of Washington
MEng in Computer Science, 2016
Massachusetts Institute of Technology
BS in Computer Science, 2015
Massachusetts Institute of Technology

News

Nov 2021: Defended my dissertation! 🎓

I successfully defended my dissertation on ‘Stakeholders’ Interpretations of Data for Equitable Computing Education.’ more info

Nov 2021: Paper published to CSCW 2022 / PACMHCI!

Journal article titled ‘Surfacing Equity Issues in Large Computing Courses with Peer-Ranked, Demographically-Labeled Student Feedback’ published to PACMHCI and will be presented at CSCW 2022! about CSCW 2022

Jul 2021: Presented at UW DUB Seminar

I presented my work on curriculum designers’ interpretations of test bias data at the UW DUB seminar on HCI and design. see recording

May 2021: Awarded Husky 100

Awarded to 100 students across UW’s three campuses who make the most of their time. see announcement

Projects

Student Amp: Amplifying marginalized voices in computing courses

Tools to help learners share and instructors understand equity issues in a computing courses.

Improving equity of Code.org's CS Discoveries curriculum

Investigating how Code.org CS Discoveries curriculum serves different sub-populations to improve the equity of learning experiences and outcomes.

Codeitz: An adaptive learning experience that lets learners decide

Designing for learner agency in self-directed online learning experiences

Improving computer science education w/ explicit instruction

Providing explicit instrutions to make introductory programming more approachable.

Recent Papers

Stakeholders' Interpretations of Data for Equitable Computing Education

Interactions with data that consider prior knowledge, perceptions of power relationships, and cultural competency can enable computing education stakeholders to connect their interpretations of data with their domain expertise in service of equity-oriented goals.

Benjamin Xie

PDF Slides

Interpretations and Uses of Data for Equity in Computing Education

My submission and poster for the ICER 2021 Doctoral Consortium provided an overview of the three main projects of my dissertation. Combined, these projects are design explorations of how stakeholders (students, teachers, curriculum designers) can interpret and use data to support equity-oriented goals.

Benjamin Xie

PDF Poster

Domain Experts' Interpretations of Assessment Bias in a Scaled, Online Computer Science Curriculum

Explored a new use of Differential Item Functioning (DIF) where domain experts (Code.org curriculum designers) interpreted data on potential test bias by gender and race.

Benjamin Xie, Matt J. Davidson, Baker Franke, Emily McLeod, Min Li, Amy J Ko

PDF DOI supplementary info