Kristin Fasiang

Research

In my research, I try to understand how students work at the edges of formal computer science learning environments to create spaces where they can belong and succeed. To do this, I focus on students' (sometimes unsanctioned and unorthodox) interactions with their peers and appropriations of technologies.

Key words: self-efficacy, belonging, identity, learning pathways, accessibility, and human computer interaction.

Some of my work includes:

  • Investigating the interactions students have with peers and technology “to the side” of a main activity in their computer science classes and how they contribute to learning and belonging.
  • Identifying moments that influence students’ sense of belonging and self-assessments while they collaboratively program with a peer.
  • Scoping a project to understand how why and how sighted and blind/low-vision students break norms around AI use and the impacts this has on their identities and learning trajectories.

Peer-Reviewed Publications

Talk, Tech, and Togetherness: Ethnographic Insights into Siding in Introductory Undergraduate Computer Science

Kristin Fasiang, Melissa Chen, Darren Gergle, Eleanor O'Rourke
Under Review

Starting From Scratch Again and Again: Tracing the Origins of High Schoolers’ Negative Perceptions of Block-Based Programming.

Caryn Tran, Kristin Fasiang, Max Kanwal, Eleanor O'Rourke
CHI 2026, Forthcoming

Exploring Student-Perceived Dimensions of Authenticity in High School Computer Science

Caryn Tran, Max Kanwal, Kristin Fasiang, Eleanor O'Rourke
ICER 2025, ACM Digital Library

The Interrelated Nature of Belonging and Self-Assessments in Computing Students' Decisions to Persist

Kristin Fasiang, Melissa Chen, Eleanor O'Rourke
ISLS 2025, ISLS Repository

Workshops Etc.

Hello World: Grounding the Design of Generative AI in Learning Communities and Contexts with Sociocultural Theories

Kristin Fasiang*, Melissa Chen*, Eleanor O'Rourke
CHI 2026 Workshop: Understanding and Engaging Critical Resistance to AI in Education, Link

Large Language Madlibs Model AI Assignment

Kristin Fasiang, Duri Long
EAAI 2025, Model AI Assignments