Benjamin Xie he/they

PhD Candidate

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

I am a National Science Foundation (NSF) Graduate Research Fellow. I was previously 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
Artificial Intelligence in Education
Psychometrics

Education

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

News

Jun 2021: Paper published to Learning @ Scale 2021

In collaboration with Code.org, I explored how domain experts interperted data on test bias for equitable action. see article

May 2021: Awarded Husky 100

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

Dec 2020: Google Cloud Research Grant for Student Amp

My advisor and I were awarded a grant by Google Cloud for Student Amp, a tool to help instructors address equity issues in CS courses. about Student Amp

Dec 2020: Article published in ACM Crossroads (XRDS) Magazine

I describe techniques I am exploring in my dissertation to use data to support equity in computing education. see article

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

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