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.

Some key words for my research are: self-efficacy, belonging, identity, learning pathways, accessibility, and human computer interaction.

Some of my past 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.
  • Understanding storylines students use when evaluating their belonging in computer science and when self-assessing during the programming process.
  • Creating a model AI assignment for middle and high school students to learn about bias and ethical concerns with large language models.

Currently, I am working on:

  • Identifying moments that influence students’ sense of belonging and self-assessments while they collaboratively program with a peer.
  • Scoping a project to understand how students with disabilties use and create their own assistive technologies to engage with computer science learning.

Publications

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, Forthcoming

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

Large Language Madlibs Model AI Assignment

Kristin Fasiang, Duri Long
EAAI 2025, Model AI Assignments