activity
20242026
collaborators

13 papers

cs.HC2026

Understanding teens' self-beliefs when learning to construct and deconstruct AI/ML systems: Developing a survey instrument

Luis Morales-Navarro, Deborah Fields, Michael T. Giang +3

Despite growing calls to foster AI literacy, there are few available survey instruments designed for children and youth that study computational empowerment alongside construction…

cs.HC2026

Building to Understand: Examining Teens' Technical and Socio-Ethical Pieces of Understandings in the Construction of Small Generative Language Models

Luis Morales-Navarro, Daniel J. Noh, Lucianne Servat +3

The rising adoption of generative AI/ML technologies increases the need to support teens in developing AI/ML literacies. Child-computer interaction research argues that constructio…

cs.HC2026

Rapid Testing, Duck Lips, and Tilted Cameras: Youth Everyday Algorithm Auditing Practices with Generative AI Filters

Lauren Vogelstein, Vedya Konda, Deborah Fields +3

Today's youth have extensive experience interacting with artificial intelligence and machine learning applications on popular social media platforms, putting youth in a unique posi…

cs.CY2026

CreateAI Insights from an NSF Workshop on K12 Students, Teachers, and Families as Designers of Artificial Intelligence and Machine Learning Applications

Yasmin Kafai, José Ramón Lizárraga, R. Benjamin Shapiro

In response to the exponential growth in the use of artificial intelligence and machine learning applications, educators, researchers and policymakers have taken steps to integrate…

cs.CY2026

Expanding the Scope of Computational Thinking in Artificial Intelligence for K-12 Education

Yasmin Kafai, Shuchi Grover

The introduction of generative artificial intelligence applications to the public has led to heated discussions about its potential impacts and risks for K-12 education. One partic…

cs.HC2025

Learning AI Auditing: A Case Study of Teenagers Auditing a Generative AI Model

Luis Morales-Navarro, Michelle Gan, Evelyn Yu +3

This study investigates how high school-aged youth engage in algorithm auditing to identify and understand biases in artificial intelligence and machine learning (AI/ML) tools they…